Posts Tagged post stroke
The impairment of finger movements after a stroke results in a significant deficit in hands everyday performances. To face this kind of problems different rehabilitation techniques have been developed, nevertheless, they require the presence of a therapist to be executed. To overcome this issue have been designed several apparatuses that allow the patient to perform the training by itself. Thus, an easy to use and effective device is needed to provide the right training and complete the rehabilitation techniques in the best way. In this paper, a review of state of the art in this field is provided, along with an introduction to the problems caused by a stroke and the consequences for the mobility of the hand. Then follows a complete review of the low cost home based exoskeleton project design. The objective is to design a device that can be used at home, with a lightweight and affordable structure and a fast mounting system. For implementing all these features, many aspects have been analysed, starting from the rehabilitation requirements and the ergonomic issues. This device should be able to reproduce the training movements on an injured hand without the need for assistance by an external tutor.
In the United States more than 700,000 people suffer a stroke each year, and approximately two-thirds of these individuals survive and require rehabilitation. The goals of rehabilitation are to help survivors become as independent as possible and to attain the best possible quality of life. Even though rehabilitation does not “cure” the effects of stroke in that it does not reverse brain damage, rehabilitation can substantially help people achieve the best possible long-term outcome.
Rehabilitation helps stroke survivors relearn skills that are lost when part of the brain is damaged. For example, these skills can include coordinating leg movements in order to walk or carrying out the steps involved in any complex activity. Rehabilitation also teaches survivors new ways of performing tasks to circumvent or compensate for any residual disabilities. Individuals may need to learn how to bathe and dress using only one hand, or how to communicate effectively when their ability to use language has been compromised. There is a strong consensus among rehabilitation experts that the most important element in any rehabilitation program is carefully directed,well-focused, repetitive practice—the same kind of practice used by all people when they learn a new skill, such as playing the piano or pitching a baseball.
Rehabilitative therapy begins in the acute-care hospital after the person’s overall condition has been stabilized, often within 24 to 48 hours after the stroke. The first steps involve promoting independent movement because many individuals are paralyzed or seriously weakened. Patients are prompted to change positions frequently while lying in bed and to engage in passive or active range of motion exercises to strengthen their stroke-impaired limbs. (“Passive” range-of-motion exercises are those in which the therapist actively helps the patient move a limb repeatedly, whereas “active” exercises are performed by the patient with no physical assistance from the therapist.) Depending on many factors—including the extent of the initial injury—patients may progress from sitting up and being moved between the bed and a chair to standing, bearing their own weight, and walking, with or without assistance. Rehabilitation nurses and therapists help patients who are able to perform progressively more complex and demanding tasks, such as bathing, dressing, and using a toilet, and they encourage patients to begin using their stroke-impaired limbs while engaging in those tasks. Beginning to reacquire the ability to carry out these basic activities of daily living represents the first stage in a stroke survivor’s return to independence.
For some stroke survivors, rehabilitation will be an ongoing process to maintain and refine skills and could involve working with specialists for months or years after the stroke.
The types and degrees of disability that follow a stroke depend upon which area of the brain is damaged. Generally, stroke can cause five types of disabilities: paralysis or problems controlling movement; sensory disturbances including pain; problems using or understanding language; problems with thinking and memory; and emotional disturbances.
Paralysis or problems controlling movement (motor control)
Paralysis is one of the most common disabilities resulting from stroke. The paralysis is usually on the side of the body opposite the side of the brain damaged by stroke, and may affect the face, an arm, a leg, or the entire side of the body. This one-sided paralysis is called hemiplegia (one-sided weakness is called hemiparesis). Stroke patients with hemiparesis or hemiplegia may have difficulty with everyday activities such as walking or grasping objects. Some stroke patients have problems with swallowing, called dysphagia, due to damage to the part of the brain that controls the muscles for swallowing. Damage to a lower part of the brain, the cerebellum, can affect the body’s ability to coordinate movement, a disability called ataxia, leading to problems with body posture, walking, and balance.
Sensory disturbances including pain
Stroke patients may lose the ability to feel touch, pain, temperature, or position. Sensory deficits also may hinder the ability to recognize objects that patients are holding and can even be severe enough to cause loss of recognition of one’s own limb. Some stroke patients experience pain, numbness or odd sensations of tingling or prickling in paralyzed or weakened limbs, a symptom known as paresthesias.
The loss of urinary continence is fairly common immediately after a stroke and often results from a combination of sensory and motor deficits. Stroke survivors may lose the ability to sense the need to urinate or the ability to control bladder muscles. Some may lack enough mobility to reach a toilet in time. Loss of bowel control or constipation also may occur. Permanent incontinence after a stroke is uncommon, but even a temporary loss of bowel or bladder control can be emotionally difficult for stroke survivors.
Stroke survivors frequently have a variety of chronic pain syndromes resulting from stroke-induced damage to the nervous system (neuropathic pain). In some stroke patients, pathways for sensation in the brain are damaged, causing the transmission of false signals that result in the sensation of pain in a limb or side of the body that has the sensory deficit. The most common of these pain syndromes is called “thalamic pain syndrome” (caused by a stroke to the thalamus, which processes sensory information from the body to the brain), which can be difficult to treat even with medications. Finally, some pain that occurs after stroke is not due to nervous system damage, but rather to mechanical problems caused by the weakness from the stroke. Patients who have a seriously weakened or paralyzed arm commonly experience moderate to severe pain that radiates outward from the shoulder. Most often, the pain results from lack of movement in a joint that has been immobilized for a prolonged period of time (such as having your arm or shoulder in a cast for weeks) and the tendons and ligaments around the joint become fixed in one position. This is commonly called a “frozen” joint; “passive” movement (the joint is gently moved or flexed by a therapist or caregiver rather than by the individual) at the joint in a paralyzed limb is essential to prevent painful “freezing” and to allow easy movement if and when voluntary motor strength returns.
Problems using or understanding language (aphasia)
At least one-fourth of all stroke survivors experience language impairments, involving the ability to speak, write, and understand spoken and written language. A stroke-induced injury to any of the brain’s language-control centers can severely impair verbal communication. The dominant centers for language are in the left side of the brain for right-handed individuals and many left-handers as well. Damage to a language center located on the dominant side of the brain, known as Broca’s area, causes expressive aphasia. People with this type of aphasia have difficulty conveying their thoughts through words or writing. They lose the ability to speak the words they are thinking and to put words together in coherent, grammatically correct sentences. In contrast, damage to a language center located in a rear portion of the brain, called Wernicke’s area, results in receptive aphasia. People with this condition have difficulty understanding spoken or written language and often have incoherent speech. Although they can form grammatically correct sentences, their utterances are often devoid of meaning. The most severe form of aphasia, global aphasia, is caused by extensive damage to several areas of the brain involved in language function. People with global aphasia lose nearly all their linguistic abilities; they cannot understand language or use it to convey thought.
Problems with thinking and memory
Stroke can cause damage to parts of the brain responsible for memory, learning, and awareness. Stroke survivors may have dramatically shortened attention spans or may experience deficits in short-term memory. Individuals also may lose their ability to make plans, comprehend meaning, learn new tasks, or engage in other complex mental activities. Two fairly common deficits resulting from stroke are anosognosia, an inability to acknowledge the reality of the physical impairments resulting from stroke, and neglect, the loss of the ability to respond to objects or sensory stimuli located on the stroke-impaired side. Stroke survivors who develop apraxia (loss of ability to carry out a learned purposeful movement) cannot plan the steps involved in a complex task and act on them in the proper sequence. Stroke survivors with apraxia also may have problems following a set of instructions. Apraxia appears to be caused by a disruption of the subtle connections that exist between thought and action.
Many people who survive a stroke feel fear, anxiety, frustration, anger, sadness, and a sense of grief for their physical and mental losses. These feelings are a natural response to the psychological trauma of stroke. Some emotional disturbances and personality changes are caused by the physical effects of brain damage. Clinical depression, which is a sense of hopelessness that disrupts an individual’s ability to function, appears to be the emotional disorder most commonly experienced by stroke survivors. Signs of clinical depression include sleep disturbances, a radical change in eating patterns that may lead to sudden weight loss or gain, lethargy, social withdrawal, irritability, fatigue, self-loathing, and suicidal thoughts. Post-stroke depression can be treated with antidepressant medications and psychological counseling.
Post-stroke rehabilitation involves physicians; rehabilitation nurses; physical, occupational, recreational, speech-language, and vocational therapists; and mental health professionals.
Physicians have the primary responsibility for managing and coordinating the long-term care of stroke survivors, including recommending which rehabilitation programs will best address individual needs. Physicians also are responsible for caring for the stroke survivor’s general health and providing guidance aimed at preventing a second stroke, such as controlling high blood pressure or diabetes and eliminating risk factors such as cigarette smoking, excessive weight, a high-cholesterol diet, and high alcohol consumption.
Neurologists usually lead acute-care stroke teams and direct patient care during hospitalization. They sometimes participate on the long-term rehabilitation team. Other subspecialists often lead the rehabilitation stage of care, especially physiatrists, who specialize in physical medicine and rehabilitation.
Nurses specializing in rehabilitation help survivors relearn how to carry out the basic activities of daily living. They also educate survivors about routine health care, such as how to follow a medication schedule, how to care for the skin, how to move out of a bed and into a wheelchair, and special needs for people with diabetes. Rehabilitation nurses also work with survivors to reduce risk factors that may lead to a second stroke, and provide training for caregivers.
Nurses are closely involved in helping stroke survivors manage personal care issues, such as bathing and controlling incontinence. Most stroke survivors regain their ability to maintain continence, often with the help of strategies learned during rehabilitation. These strategies include strengthening pelvic muscles through special exercises and following a timed voiding schedule. If problems with incontinence continue, nurses can help caregivers learn to insert and manage catheters and to take special hygienic measures to prevent other incontinence-related health problems from developing.
Physical therapists specialize in treating disabilities related to motor and sensory impairments. They are trained in all aspects of anatomy and physiology related to normal function, with an emphasis on movement. They assess the stroke survivor’s strength, endurance, range of motion, gait abnormalities, and sensory deficits to design individualized rehabilitation programs aimed at regaining control over motor functions.
Physical therapists help survivors regain the use of stroke-impaired limbs, teach compensatory strategies to reduce the effect of remaining deficits, and establish ongoing exercise programs to help people retain their newly learned skills. Disabled people tend to avoid using impaired limbs, a behavior called learned non-use. However, the repetitive use of impaired limbs encourages brain plasticity and helps reduce disabilities.
Strategies used by physical therapists to encourage the use of impaired limbs include selective sensory stimulation such as tapping or stroking, active and passive range-of-motion exercises, and temporary restraint of healthy limbs while practicing motor tasks.
In general, physical therapy emphasizes practicing isolated movements, repeatedly changing from one kind of movement to another, and rehearsing complex movements that require a great deal of coordination and balance, such as walking up or down stairs or moving safely between obstacles. People too weak to bear their own weight can still practice repetitive movements during hydrotherapy (in which water provides sensory stimulation as well as weight support) or while being partially supported by a harness. A recent trend in physical therapy emphasizes the effectiveness of engaging in goal-directed activities, such as playing games, to promote coordination. Physical therapists frequently employ selective sensory stimulation to encourage use of impaired limbs and to help survivors with neglect regain awareness of stimuli on the neglected side of the body.
Occupational and recreational therapists
Like physical therapists, occupational therapists are concerned with improving motor and sensory abilities, and ensuring patient safety in the post-stroke period. They help survivors relearn skills needed for performing self-directed activities (also called occupations) such as personal grooming, preparing meals, and housecleaning. Therapists can teach some survivors how to adapt to driving and provide on-road training. They often teach people to divide a complex activity into its component parts, practice each part, and then perform the whole sequence of actions. This strategy can improve coordination and may help people with apraxia relearn how to carry out planned actions.
Occupational therapists also teach people how to develop compensatory strategies and change elements of their environment that limit activities of daily living. For example, people with the use of only one hand can substitute hook and loop fasteners (such as Velcro) for buttons on clothing. Occupational therapists also help people make changes in their homes to increase safety, remove barriers, and facilitate physical functioning, such as installing grab bars in bathrooms.
Recreational therapists help people with a variety of disabilities to develop and use their leisure time to enhance their health, independence, and quality of life.
Speech-language pathologists help stroke survivors with aphasia relearn how to use language or develop alternative means of communication. They also help people improve their ability to swallow, and they work with patients to develop problem-solving and social skills needed to cope with the after-effects of a stroke.
Many specialized therapeutic techniques have been developed to assist people with aphasia. Some forms of short-term therapy can improve comprehension rapidly. Intensive exercises such as repeating the therapist’s words, practicing following directions, and doing reading or writing exercises form the cornerstone of language rehabilitation. Conversational coaching and rehearsal, as well as the development of prompts or cues to help people remember specific words, are sometimes beneficial. Speech-language pathologists also help stroke survivors develop strategies for circumventing language disabilities. These strategies can include the use of symbol boards or sign language. Recent advances in computer technology have spurred the development of new types of equipment to enhance communication.
Speech-language pathologists use special types of imaging techniques to study swallowing patterns of stroke survivors and identify the exact source of their impairment. Difficulties with swallowing have many possible causes, including a delayed swallowing reflex, an inability to manipulate food with the tongue, or an inability to detect food remaining lodged in the cheeks after swallowing. When the cause has been pinpointed, speech-language pathologists work with the individual to devise strategies to overcome or minimize the deficit. Sometimes, simply changing body position and improving posture during eating can bring about improvement. The texture of foods can be modified to make swallowing easier; for example, thin liquids, which often cause choking, can be thickened. Changing eating habits by taking small bites and chewing slowly can also help alleviate dysphagia.
Approximately one-fourth of all strokes occur in people between the ages of 45 and 65. For most people in this age group, returning to work is a major concern. Vocational therapists perform many of the same functions that ordinary career counselors do. They can help people with residual disabilities identify vocational strengths and develop résumés that highlight those strengths. They also can help identify potential employers, assist in specific job searches, and provide referrals to stroke vocational rehabilitation agencies.
Most important, vocational therapists educate disabled individuals about their rights and protections as defined by the Americans with Disabilities Act of 1990. This law requires employers to make “reasonable accommodations” for disabled employees. Vocational therapists frequently act as mediators between employers and employees to negotiate the provision of reasonable accommodations in the workplace.
Rehabilitation should begin as soon as a stroke patient is stable, sometimes within 24 to 48 hours after a stroke. This first stage of rehabilitation can occur within an acute-care hospital; however, it is very dependent on the unique circumstances of the individual patient.
Recently, in the largest stroke rehabilitation study in the United States, researchers compared two common techniques to help stroke patients improve their walking. Both methods—training on a body-weight supported treadmill or working on strength and balance exercises at home with a physical therapist—resulted in equal improvements in the individual’s ability to walk by the end of one year. Researchers found that functional improvements could be seen as late as one year after the stroke, which goes against the conventional wisdom that most recovery is complete by 6 months. The trial showed that 52 percent of the participants made significant improvements in walking, everyday function and quality of life, regardless of how severe their impairment was, or whether they started the training at 2 or 6 months after the stroke.
At the time of discharge from the hospital, the stroke patient and family coordinate with hospital social workers to locate a suitable living arrangement. Many stroke survivors return home, but some move into some type of medical facility.
Inpatient rehabilitation units
Inpatient facilities may be freestanding or part of larger hospital complexes. Patients stay in the facility, usually for 2 to 3 weeks, and engage in a coordinated, intensive program of rehabilitation. Such programs often involve at least 3 hours of active therapy a day, 5 or 6 days a week. Inpatient facilities offer a comprehensive range of medical services, including full-time physician supervision and access to the full range of therapists specializing in post-stroke rehabilitation.
Outpatient facilities are often part of a larger hospital complex and provide access to physicians and the full range of therapists specializing in stroke rehabilitation. Patients typically spend several hours, often 3 days each week, at the facility taking part in coordinated therapy sessions and return home at night. Comprehensive outpatient facilities frequently offer treatment programs as intense as those of inpatient facilities, but they also can offer less demanding regimens, depending on the patient’s physical capacity.
Rehabilitative services available at nursing facilities are more variable than are those at inpatient and outpatient units. Skilled nursing facilities usually place a greater emphasis on rehabilitation, whereas traditional nursing homes emphasize residential care. In addition, fewer hours of therapy are offered compared to outpatient and inpatient rehabilitation units.
Home-based rehabilitation programs
Home rehabilitation allows for great flexibility so that patients can tailor their program of rehabilitation and follow individual schedules. Stroke survivors may participate in an intensive level of therapy several hours per week or follow a less demanding regimen. These arrangements are often best suited for people who require treatment by only one type of rehabilitation therapist. Patients dependent on Medicare coverage for their rehabilitation must meet Medicare’s “homebound” requirements to qualify for such services; at this time lack of transportation is not a valid reason for home therapy. The major disadvantage of home-based rehabilitation programs is the lack of specialized equipment. However, undergoing treatment at home gives people the advantage of practicing skills and developing compensatory strategies in the context of their own living environment. In the recent stroke rehabilitation trial, intensive balance and strength rehabilitation in the home was equivalent to treadmill training at a rehabilitation facility in improving walking.
The National Institute of Neurological Disorders and Stroke (NINDS), a component of the U.S. National Institutes of Health (NIH), has primary responsibility for sponsoring research on disorders of the brain and nervous system, including the acute phase of stroke and the restoration of function after stroke. The NIH’s Eunice Kennedy Shriver National Institute of Child Health and Human Development, through its National Center for Medical Rehabilitation Research, funds work on mechanisms of restoration and repair after stroke, as well as development of new approaches to rehabilitation and evaluation of outcomes. Most of the NIH-funded work on diagnosis and treatment of dysphagia is through the National Institute on Deafness and Other Communication Disorders. The National Institute of Biomedical Imaging and Bioengineering collaborates with NINDS and NICHD in developing new instrumentation for stroke treatment and rehabilitation. The National Eye Institute funds work directed at restoration of vision and rehabilitation for individuals with impaired or low vision that may be due to vascular disease or stroke.
The NINDS supports research on ways to enhance repair and regeneration of the central nervous system. Scientists funded by the NINDS are studying how the brain responds to experience or adapts to injury by reorganizing its functions (plasticity)—using noninvasive imaging technologies to map patterns of biological activity inside the brain. Other NINDS-sponsored scientists are looking at brain reorganization after stroke and determining whether specific rehabilitative techniques, such as constraint-induced movement therapy and transcranial magnetic stimulation, can stimulate brain plasticity, thereby improving motor function and decreasing disability. Other scientists are experimenting with implantation of neural stem cells, to see if these cells may be able to replace the cells that died as a result of a stroke.
*An ischemic stroke or “brain attack” occurs when brain cells die because of inadequate blood flow. When blood flow is interrupted, brain cells are robbed of vital supplies of oxygen and nutrients. About 80 percent of strokes are caused by the blockage of an artery in the neck or brain. A hemorrhagic stroke is caused by a burst blood vessel in the brain that causes bleeding into or around the brain.
NIH Publication No. 14 1846
More than 1.5 million people suffer a stroke in Europe per year and more than 70% of stroke survivors experience limited functional recovery of their upper limb, resulting in diminished quality of life. Therefore, interventions to address upper-limb impairment are a priority for stroke survivors and clinicians. While a significant body of evidence supports the use of conventional treatments, such as intensive motor training or constraint-induced movement therapy, the limited and heterogeneous improvements they allow are, for most patients, usually not sufficient to return to full autonomy. Various innovative neurorehabNIBSilitation strategies are emerging in order to enhance beneficial plasticity and improve motor recovery. Among them, robotic technologies, brain-computer interfaces, or noninvasive brain stimulation (NIBS) are showing encouraging results. These innovative interventions, such as NIBS, will only provide maximized effects, if the field moves away from the “one-fits all” approach toward a “patient-tailored” approach. After summarizing the most commonly used rehabilitation approaches, we will focus on and highlight the factors that limit its widespread use in clinical settings. Subsequently, we will propose potential biomarkers that might help to stratify stroke patients in order to identify the individualized optimal therapy. We will discuss future methodological developments, which could open new avenues for poststroke rehabilitation, toward more patient-tailored precision medicine approaches and pathophysiologically motivated strategies.
|Adeyemo BO, Simis M, Macea DD, Fregni F. 2012. Systematic review of parameters of stimulation, clinical trial design characteristics, and motor outcomes in non-invasive brain stimulation in stroke. Front Psychiatry 3:88. Google Scholar Crossref,
MedlineAltschuler EL, Wisdom SB, Stone L, Foster C, Galasko D, Llewellyn DM, and others. 1999. Rehabilitation of hemiparesis after stroke with a mirror. Lancet 353(9169):2035–6. Google Scholar Crossref, Medline
|Ang KK, Chua KS, Phua KS, Wang C, Chin ZY, Kuah CW, and others. 2015. A randomized controlled trial of EEG-based motor imagery brain-computer interface robotic rehabilitation for stroke. Clin EEG Neurosci 46(4):310–20. Google Scholar Link|
|Basmajian JV, Gowland CA, Finlayson MA, Hall AL, Swanson LR, Stratford PW, and others. 1987. Stroke treatment: comparison of integrated behavioral-physical therapy vs traditional physical therapy programs. Arch Phys Med Rehabil 68(5 Pt 1):267–72. Google Scholar Medline|
|Bergmann TO, Groppa S, Seeger M, Molle M, Marshall L, Siebner HR. 2009. Acute changes in motor cortical excitability during slow oscillatory and constant anodal transcranial direct current stimulation. J Neurophysiol 102(4):2303–11. Google Scholar Crossref, Medline|
|Bhagat NA, Venkatakrishnan A, Abibullaev B, Artz EJ, Yozbatiran N, Blank AA, and others. 2016. Design and optimization of an EEG-based brain machine interface (BMI) to an upper-limb exoskeleton for stroke survivors. Front Neurosci 10:122. Google Scholar Crossref, Medline|
|Birbaumer N, Murguialday AR, Cohen L. 2008. Brain-computer interface in paralysis. Curr Opin Neurol 21(6):634–8. Google Scholar Crossref, Medline|
|Borich MR, Wheaton LA, Brodie SM, Lakhani B, Boyd LA. 2016. Evaluating interhemispheric cortical responses to transcranial magnetic stimulation in chronic stroke: a TMS-EEG investigation. Neurosci Lett618:25–30. Google Scholar|
|Brown JA, Lutsep HL, Weinand M, Cramer SC. 2008. Motor cortex stimulation for the enhancement of recovery from stroke: a prospective, multicenter safety study. Neurosurgery 62(Suppl 2):853–62. Google Scholar Crossref, Medline|
|Buetefisch CM. 2015. Role of the contralesional hemisphere in post-stroke recovery of upper extremity motor function. Front Neurol 6:214. Google Scholar Crossref, Medline|
|Burke Quinlan E, Dodakian L, See J, McKenzie A, Le V, Wojnowicz M, and others. 2015. Neural function, injury, and stroke subtype predict treatment gains after stroke. Ann Neurol 77(1):132–45. Google Scholar Crossref, Medline|
|Butler AJ, Shuster M, O’Hara E, Hurley K, Middlebrooks D, Guilkey K. 2013. A meta-analysis of the efficacy of anodal transcranial direct current stimulation for upper limb motor recovery in stroke survivors. J Hand Ther 26(2):162–70. Google Scholar Crossref, Medline|
|Capogrosso M, Milekovic T, Borton D, Wagner F, Moraud EM, Mignardot JB, and others. 2016. A brain-spine interface alleviating gait deficits after spinal cord injury in primates. Nature 539(7628):284–8. Google ScholarCrossref, Medline|
|Carey JR, Deng H, Gillick BT, Cassidy JM, Anderson DC, Zhang L, and others. 2014. Serial treatments of primed low-frequency rTMS in stroke: characteristics of responders vs. nonresponders. Restor Neurol Neurosci 32(2):323–35. Google Scholar Medline|
|Carter AR, Shulman GL, Corbetta M. 2012. Why use a connectivity-based approach to study stroke and recovery of function? Neuroimage 62(4):2271–80. Google Scholar Crossref, Medline|
|Cassidy JM, Gillick BT, Carey JR. 2014. Priming the brain to capitalize on metaplasticity in stroke rehabilitation. Phys Ther 94(1):139–50. Google Scholar Crossref, Medline|
|Cecere R, Rees G, Romei V. 2015. Individual differences in alpha frequency drive crossmodal illusory perception. Curr Biol 25(2):231–5. Google Scholar Crossref, Medline|
|Chang WD, Lai PT. 2015. New design of home-based dynamic hand splint for hemiplegic hands: a preliminary study. J Phys Ther Sci 27(3):829–31. Google Scholar Crossref, Medline|
|Chaudhary U, Birbaumer N, Curado MR. 2015. Brain-machine interface (BMI) in paralysis. Ann Phys Rehabil Med 58(1):9–13. Google Scholar Crossref, Medline|
|Chechlacz M, Humphreys GW, Sotiropoulos SN, Kennard C, Cazzoli D. 2015. Structural organization of the corpus callosum predicts attentional shifts after continuous theta burst stimulation. J Neurosci 35(46):15353–68. Google Scholar Crossref, Medline|
|Collinger JL, Wodlinger B, Downey JE, Wang W, Tyler-Kabara EC, Weber DJ, and others. 2013. High-performance neuroprosthetic control by an individual with tetraplegia. Lancet 381(9866):557–64. Google Scholar Crossref, Medline|
|Conde V, Vollmann H, Sehm B, Taubert M, Villringer A, Ragert P. 2012. Cortical thickness in primary sensorimotor cortex influences the effectiveness of paired associative stimulation. Neuroimage 60(2):864–70. Google Scholar Crossref, Medline|
|Corbetta D, Sirtori V, Castellini G, Moja L, Gatti R. 2015. Constraint-induced movement therapy for upper extremities in people with stroke. Cochrane Database Syst Rev (10):CD004433. Google Scholar Medline|
|Coupar F, Pollock A, Rowe P, Weir C, Langhorne P. 2012. Predictors of upper limb recovery after stroke: a systematic review and meta-analysis. Clin Rehabil 26(4):291–313. Google Scholar Link|
|Dahl AE, Askim T, Stock R, Langorgen E, Lydersen S, Indredavik B. 2008. Short- and long-term outcome of constraint-induced movement therapy after stroke: a randomized controlled feasibility trial. Clin Rehabil 22(5):436–47. Google Scholar Link|
|De Vico Fallani F, Richiardi J, Chavez M, Achard S. 2014. Graph analysis of functional brain networks: practical issues in translational neuroscience. Philos Trans R Soc Lond B Biol Sci 369(1653):0521. Google Scholar Crossref|
|Di Carlo A. 2009. Human and economic burden of stroke. Age Ageing 38(1):4–5. Google Scholar Crossref, Medline|
|Dickstein R, Hocherman S, Pillar T, Shaham R. 1986. Stroke rehabilitation. Three exercise therapy approaches. Phys Ther 66(8):1233–8. Google Scholar Crossref, Medline|
|Donati AR, Shokur S, Morya E, Campos DS, Moioli RC, Gitti CM, and others. 2016. Long-term training with a brain-machine interface-based gait protocol induces partial neurological recovery in paraplegic patients. Sci Rep 6:30383. Google Scholar Crossref, Medline|
|Dromerick AW, Edwardson MA, Edwards DF, Giannetti ML, Barth J, Brady KP, and others. 2015. Critical periods after stroke study: translating animal stroke recovery experiments into a clinical trial. Front Hum Neurosci 9:231. Google Scholar Crossref, Medline|
|Dromerick AW, Lang CE, Birkenmeier RL, Wagner JM, Miller JP, Videen TO, and others. 2009. Very Early Constraint-Induced Movement during Stroke Rehabilitation (VECTORS): a single-center RCT. Neurology 73(3):195–201. Google Scholar Crossref, Medline|
|Duncan PW. 1997. Synthesis of intervention trials to improve motor recovery following stroke. Top Stroke Rehabil 3(4):1–20. Google Scholar Crossref, Medline|
|Duque J, Hummel F, Celnik P, Murase N, Mazzocchio R, Cohen LG. 2005. Transcallosal inhibition in chronic subcortical stroke. Neuroimage 28(4):940–6. Google Scholar Crossref, Medline|
|Feigin VL, Norrving B, Mensah GA. 2017. Global burden of stroke. Circ Res 120(3):439–48. Google ScholarCrossref, Medline|
|Fox MD, Buckner RL, Liu H, Chakravarty MM, Lozano AM, Pascual-Leone A. 2014. Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases. Proc Natl Acad Sci U S A 111(41):E4367–75. Google Scholar Crossref, Medline|
|Fox MD, Liu H, Pascual-Leone A. 2013. Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity. Neuroimage 66:151–60. Google Scholar Crossref, Medline|
|Friston KJ, Harrison L, Penny W. 2003. Dynamic causal modelling. Neuroimage 19(4):1273–302. Google Scholar Crossref, Medline|
|Fritz SL, Light KE, Patterson TS, Behrman AL, Davis SB. 2005. Active finger extension predicts outcomes after constraint-induced movement therapy for individuals with hemiparesis after stroke. Stroke 36(6):1172–7. Google Scholar Crossref, Medline|
|Gaggioli A, Morganti F, Walker R, Meneghini A, Alcaniz M, Lozano JA, and others. 2004. Training with computer-supported motor imagery in post-stroke rehabilitation. Cyberpsychol Behav 7(3):327–32. Google Scholar Crossref, Medline|
|Gamito P, Oliveira J, Coelho C, Morais D, Lopes P, Pacheco J, and others. 2017. Cognitive training on stroke patients via virtual reality-based serious games. Disabil Rehabil 39(4):385–8. Google Scholar Crossref, Medline|
|Geranmayeh F, Leech R, Wise RJ. 2016. Network dysfunction predicts speech production after left hemisphere stroke. Neurology 86(14):1296–305. Google Scholar Crossref|
|Gerardin E, Sirigu A, Lehericy S, Poline JB, Gaymard B, Marsault C, and others. 2000. Partially overlapping neural networks for real and imagined hand movements. Cereb Cortex 10(11):1093–104. Google Scholar Crossref, Medline|
|Gharabaghi A, Kraus D, Leao MT, Spuler M, Walter A, Bogdan M, and others. 2014a. Coupling brain-machine interfaces with cortical stimulation for brain-state dependent stimulation: enhancing motor cortex excitability for neurorehabilitation. Front Hum Neurosci 8:122. Google Scholar Crossref, Medline|
|Gharabaghi A, Naros G, Walter A, Grimm F, Schuermeyer M, Roth A and others. 2014b. From assistance towards restoration with epidural brain-computer interfacing. Restor Neurol Neurosci 32(4):517–25. Google Scholar Medline|
|Giraux P, Sirigu A. 2003. Illusory movements of the paralyzed limb restore motor cortex activity. Neuroimage 20(Suppl 1):S107–11. Google Scholar Crossref, Medline|
|Graef P, Dadalt ML, Rodrigues DA, Stein C, Pagnussat Ade S. 2016. Transcranial magnetic stimulation combined with upper-limb training for improving function after stroke: a systematic review and meta-analysis. J Neurol Sci 369:149–58. Google Scholar Crossref, Medline|
|Grefkes C, Nowak DA, Eickhoff SB, Dafotakis M, Kust J, Karbe H, and others. 2008. Cortical connectivity after subcortical stroke assessed with functional magnetic resonance imaging. Ann Neurol 63(2):236–46. Google Scholar Crossref, Medline|
|Grimm F, Naros G, Gharabaghi A. 2016. Closed-loop task difficulty adaptation during virtual reality reach-to-grasp training assisted with an exoskeleton for stroke rehabilitation. Front Neurosci 10:518. Google Scholar Crossref, Medline|
|Groisser BN, Copen WA, Singhal AB, Hirai KK, Schaechter JD. 2014. Corticospinal tract diffusion abnormalities early after stroke predict motor outcome. Neurorehabil Neural Repair 28(8):751–60. Google Scholar Link|
|Groppa S, Oliviero A, Eisen A, Quartarone A, Cohen LG, Mall V, and others. 2012. A practical guide to diagnostic transcranial magnetic stimulation: report of an IFCN committee. Clin Neurophysiol 123(5):858–82. Google Scholar Crossref, Medline|
|Hamzei F, Liepert J, Dettmers C, Weiller C, Rijntjes M. 2006. Two different reorganization patterns after rehabilitative therapy: an exploratory study with fMRI and TMS. Neuroimage 31(2):710–20. Google Scholar|
|Hao Z, Wang D, Zeng Y, Liu M. 2013. Repetitive transcranial magnetic stimulation for improving function after stroke. Cochrane Database Syst Rev 5:CD008862. Google Scholar|
|Harris J, Hebert A. 2015. Utilization of motor imagery in upper limb rehabilitation: a systematic scoping review. Clin Rehabil 29(11):1092–107. Google Scholar Link|
|Harvey RL, Winstein CJ, Everest Trial Group. 2009. Design for the everest randomized trial of cortical stimulation and rehabilitation for arm function following stroke. Neurorehabil Neural Repair 23(1):32–44. Google Scholar Link|
|Hatem SM, Saussez G, Della Faille M, Prist V, Zhang X, Dispa D, and others. 2016. Rehabilitation of motor function after stroke: a multiple systematic review focused on techniques to stimulate upper extremity recovery. Front Hum Neurosci 10:442. Google Scholar Crossref, Medline|
|Helfrich RF, Schneider TR, Rach S, Trautmann-Lengsfeld SA, Engel AK, Herrmann CS. 2014. Entrainment of brain oscillations by transcranial alternating current stimulation. Curr Biol 24(3):333–9. Google Scholar Crossref, Medline|
|Hoffman HB, Blakey GL. 2011. New design of dynamic orthoses for neurological conditions. NeuroRehabilitation 28(1):55–61. Google Scholar Medline|
|Hoyer EH, Celnik PA. 2011. Understanding and enhancing motor recovery after stroke using transcranial magnetic stimulation. Restor Neurol Neurosci 29(6):395–409. Google Scholar Medline|
|Huang M, Harvey RL, Stoykov ME, Ruland S, Weinand M, Lowry D, and others. 2008. Cortical stimulation for upper limb recovery following ischemic stroke: a small phase II pilot study of a fully implanted stimulator. Top Stroke Rehabil 15(2):160–72. Google Scholar Crossref, Medline|
|Hummel FC, Celnik P, Pascual-Leone A, Fregni F, Byblow WD, Buetefisch CM, and others. 2008. Controversy: noninvasive and invasive cortical stimulation show efficacy in treating stroke patients. Brain Stimul 1(4):370–82. Google Scholar Crossref, Medline|
|Hummel FC, Cohen LG. 2006. Non-invasive brain stimulation: a new strategy to improve neurorehabilitation after stroke? Lancet Neurol 5(8):708–12. Google Scholar Crossref, Medline|
|Ibrahim IK, Berger W, Trippel M, Dietz V. 1993. Stretch-induced electromyographic activity and torque in spastic elbow muscles. Differential modulation of reflex activity in passive and active motor tasks. Brain 116(Pt 4):971–89. Google Scholar Crossref, Medline|
|Ietswaart M, Johnston M, Dijkerman HC, Joice S, Scott CL, Macwalter RS, and others. 2011. Mental practice with motor imagery in stroke recovery: randomized controlled trial of efficacy. Brain 134(Pt 5):1373–86. Google Scholar Crossref, Medline|
|Jackson A, Mavoori J, Fetz EE. 2006. Long-term motor cortex plasticity induced by an electronic neural implant. Nature 444(7115):56–60. Google Scholar Crossref, Medline|
|Jackson PL, Lafleur MF, Malouin F, Richards C, Doyon J. 2001. Potential role of mental practice using motor imagery in neurologic rehabilitation. Arch Phys Med Rehabil 82(8):1133–41. Google Scholar Crossref, Medline|
|Jiang R, Jansen BH, Sheth BR, Chen J. 2013. Dynamic multi-channel TMS with reconfigurable coil. IEEE Trans Neural Syst Rehabil Eng 21(3):370–5. Google Scholar Crossref, Medline|
|Jo JY, Lee A, Kim MS, Park E, Chang WH, Shin Y, Kim YH. 2016. Prediction of motor recovery using quantitative parameters of motor evoked potential in patients with stroke. Ann Rehabil Med 40(5):806–15. Google Scholar Crossref, Medline|
|Jongbloed L, Stacey S, Brighton C. 1989. Stroke rehabilitation: sensorimotor integrative treatment versus functional treatment. Am J Occup Ther 43(6):391–7. Google Scholar Crossref, Medline|
|Kamke MR, Ryan AE, Sale MV, Campbell ME, Riek S, Carroll TJ, and others. 2014. Visual spatial attention has opposite effects on bidirectional plasticity in the human motor cortex. J Neurosci 34(4):1475–80. Google Scholar Crossref, Medline|
|Karabanov A, Jin SH, Joutsen A, Poston B, Aizen J, Ellenstein A, and others. 2012. Timing-dependent modulation of the posterior parietal cortex-primary motor cortex pathway by sensorimotor training. J Neurophysiol 107(11):3190–9. Google Scholar Crossref, Medline|
|Karabanov A, Siebner HR. 2012. Unravelling homeostatic interactions in inhibitory and excitatory networks in human motor cortex. J Physiol 590(Pt 22):5557–8. Google Scholar Crossref, Medline|
|Karabanov A, Thielscher A, Siebner HR. 2016. Transcranial brain stimulation: closing the loop between brain and stimulation. Curr Opin Neurol 29(4):397–404. Google Scholar Crossref, Medline|
|Karabanov AN, Raffin E, Siebner HR. 2015. The resting motor threshold—restless or resting? A repeated threshold hunting technique to track dynamic changes in resting motor threshold. Brain Stimul 8(6):1191–4. Google Scholar Crossref, Medline|
|Koch PJ, Schulz R, Hummel FC. 2016. Structural connectivity analyses in motor recovery research after stroke. Ann Clin Transl Neurol 3(3):233–44. Google Scholar Crossref, Medline|
|Koch PJ, Hummel FC. 2017. Toward precision medicine: tailoring interventional strategies based on noninvasive brain stimulation for motor recovery after stroke. Curr Opin Neurol 30(4):388–97. Google ScholarCrossref, Medline|
|Kraus D, Naros G, Bauer R, Leao MT, Ziemann U, Gharabaghi A. 2016. Brain-robot interface driven plasticity: distributed modulation of corticospinal excitability. Neuroimage 125:522–-32. Google Scholar Crossref, Medline|
|Kwakkel G, van Peppen R, Wagenaar RC, Wood Dauphinee S, Richards C, Ashburn A, and others. 2004. Effects of augmented exercise therapy time after stroke: a meta-analysis. Stroke 35(11):2529–39. Google Scholar Crossref, Medline|
|Lang CE, Bland MD, Bailey RR, Schaefer SY, Birkenmeier RL. 2013. Assessment of upper extremity impairment, function, and activity after stroke: foundations for clinical decision making. J Hand Ther 26(2):104–14. Google Scholar Crossref, Medline|
|Langhorne P, Legg L. 2003. Evidence behind stroke rehabilitation. J Neurol Neurosurg Psychiatry 74(Suppl 4):iv18–21. Google Scholar Crossref, Medline|
|Lannin NA, Cusick A, Hills C, Kinnear B, Vogel K, Matthews K, and others. 2016. Upper limb motor training using a Saebo orthosis is feasible for increasing task-specific practice in hospital after stroke. Aust Occup Ther J 63(6):364–372. Google Scholar Crossref, Medline|
|Laver B, Diwan M, Nobrega JN, Hamani C. 2014. Augmentative therapies do not potentiate the antidepressant-like effects of deep brain stimulation in rats. J Affect Disord 161:87–90. Google Scholar Crossref, Medline|
|Lee KB, Lim SH, Kim KH, Kim KJ, Kim YR, Chang WN and others. 2015. Six-month functional recovery of stroke patients: a multi-time-point study. Int J Rehabil Res 38(2):173–80. Google Scholar Crossref, Medline|
|Legg LA, Quinn TJ, Mahmood F, Weir CJ, Tierney J, Stott DJ and others. 2011. Non-pharmacological interventions for caregivers of stroke survivors. Cochrane Database Syst Rev (10):CD008179. Google Scholar Medline|
|Levy RM, Harvey RL, Kissela BM, Winstein CJ, Lutsep HL, Parrish TB, and others. 2016. Epidural electrical stimulation for stroke rehabilitation: results of the prospective, multicenter, randomized, single-blinded Everest Trial. Neurorehabil Neural Repair 30(2):107–19. Google Scholar Link|
|Li LM, Uehara K, Hanakawa T. 2015. The contribution of interindividual factors to variability of response in transcranial direct current stimulation studies. Front Cell Neurosci 9:181. Google Scholar Crossref, Medline|
|Li W, Li Y, Zhu W, Chen X. 2014. Changes in brain functional network connectivity after stroke. Neural Regen Res 9(1):51–60. Google Scholar Crossref, Medline|
|Liew SL, Rana M, Cornelsen S, Fortunato de Barros Filho M, Birbaumer N, Sitaram R, and others. 2016. Improving motor corticothalamic communication after stroke using real-time fMRI connectivity-based neurofeedback. Neurorehabil Neural Repair 30(7):671–5. Google Scholar Link|
|Lindenberg R, Renga V, Zhu LL, Betzler F, Alsop D, Schlaug G. 2010a. Structural integrity of corticospinal motor fibers predicts motor impairment in chronic stroke. Neurology 74(4):280–7. Google Scholar Crossref, Medline|
|Lindenberg R, Renga V, Zhu LL, Nair D, Schlaug G. 2010b. Bihemispheric brain stimulation facilitates motor recovery in chronic stroke patients. Neurology 75(24):2176–84. Google Scholar Crossref, Medline|
|Lindenberg R, Zhu LL, Ruber T, Schlaug G. 2012. Predicting functional motor potential in chronic stroke patients using diffusion tensor imaging. Hum Brain Mapp 33(5):1040–51. Google Scholar Crossref, Medline|
|Liu KP, Chan CC, Wong RS, Kwan IW, Yau CS, Li LS and others. 2009. A randomized controlled trial of mental imagery augment generalization of learning in acute poststroke patients. Stroke 40(6):2222–5. Google Scholar Crossref, Medline|
|Lo AC, Guarino PD, Richards LG, Haselkorn JK, Wittenberg GF, Federman DG, and others. 2010. Robot-assisted therapy for long-term upper-limb impairment after stroke. N Engl J Med 362(19):1772–83. Google Scholar Crossref, Medline|
|Lum PS, Godfrey SB, Brokaw EB, Holley RJ, Nichols D. 2012. Robotic approaches for rehabilitation of hand function after stroke. Am J Phys Med Rehabil 91(11 Suppl 3):S242–54. Google Scholar Crossref, Medline|
|Masiero S, Celia A, Rosati G, Armani M. 2007. Robotic-assisted rehabilitation of the upper limb after acute stroke. Arch Phys Med Rehabil 88(2):142–9. Google Scholar Crossref, Medline|
|Massie CL, White C, Pruit K, Freel A, Staley K, Backes M. 2017. Influence of motor cortex stimulation during motor training on neuroplasticity as a potential therapeutic intervention. J Mot Behav 49(1):111–6. Google Scholar Crossref, Medline|
|McKeown MJ, Hansen LK, Sejnowsk TJ. 2003. Independent component analysis of functional MRI: what is signal and what is noise? Curr Opin Neurobiol 13(5):620–9. Google Scholar Crossref, Medline|
|Memberg WD, Polasek KH, Hart RL, Bryden AM, Kilgore KL, Nemunaitis GA, and others. 2014. Implanted neuroprosthesis for restoring arm and hand function in people with high level tetraplegia. Arch Phys Med Rehabil 95(6):1201–1211.e1. Google Scholar Crossref, Medline|
|Minjoli S, Saturnino GB, Blicher JU, Stagg CJ, Siebner HR, Antunes A, and others. 2017. The impact of large structural brain changes in chronic stroke patients on the electric field caused by transcranial brain stimulation. Neuroimage Clin 15:106–17. Google Scholar Crossref, Medline|
|Morganti F, Gaggioli A, Castelnuovo G, Bulla D, Vettorello M, Riva G. 2003. The use of technology-supported mental imagery in neurological rehabilitation: a research protocol. Cyberpsychol Behav 6(4):421–7. Google Scholar Crossref, Medline|
|Morishita T, Hummel FC. 2017. Non-invasive brain stimulation (NIBS) in motor recovery after stroke: concepts to increase efficacy. Curr Behav Neurosci Rep 4:280–9. Google Scholar Crossref|
|Mulder T. 2007. Motor imagery and action observation: cognitive tools for rehabilitation. J Neural Transm (Vienna) 114(10):1265–78. Google Scholar Crossref, Medline|
|Murase N, Duque J, Mazzocchio R, Cohen LG. 2004. Influence of interhemispheric interactions on motor function in chronic stroke. Ann Neurol 55(3):400–9. Google Scholar Crossref, Medline|
|Muratori LM, Lamberg EM, Quinn L, Duff SV. 2013. Applying principles of motor learning and control to upper extremity rehabilitation. J Hand Ther 26(2):94–102. Google Scholar Crossref, Medline|
|Nakazono H, Ogata K, Kuroda T, Tobimatsu S. 2016. Phase and frequency-dependent effects of transcranial alternating current stimulation on motor cortical excitability. PLoS One 11(9):e0162521. Google Scholar Crossref, Medline|
|Naros G, Gharabaghi A. 2015. Reinforcement learning of self-regulated beta-oscillations for motor restoration in chronic stroke. Front Hum Neurosci 9:391. Google Scholar Crossref, Medline|
|Nitsche MA, Cohen LG, Wassermann EM, Priori A, Lang N, Antal A, and others. 2008. Transcranial direct current stimulation: state of the art 2008. Brain Stimul 1(3):206–23. Google Scholar Crossref, Medline|
|Nouri S, Cramer SC. 2011. Anatomy and physiology predict response to motor cortex stimulation after stroke. Neurology 77(11):1076–83. Google Scholar Crossref, Medline|
|Nudo RJ. 2003. Functional and structural plasticity in motor cortex: implications for stroke recovery. Phys Med Rehabil Clin N Am 14(1 Suppl):S57–76. Google Scholar Crossref, Medline|
|O’Doherty JE, Lebedev MA, Hanson TL, Fitzsimmons NA, Nicolelis MA. 2009. A brain-machine interface instructed by direct intracortical microstimulation. Front Integr Neurosci 3:20. Google Scholar Crossref, Medline|
|Opitz A, Paulus W, Will S, Antunes A, Thielscher A. 2015. Determinants of the electric field during transcranial direct current stimulation. Neuroimage 109:140–50. Google Scholar Crossref, Medline|
|Page SJ, Levine P, Leonard A. 2007. Mental practice in chronic stroke: results of a randomized, placebo-controlled trial. Stroke 38(4):1293–7. Google Scholar Crossref, Medline|
|Penny WD, Stephan KE, Mechelli A, Friston KJ. 2004. Modelling functional integration: a comparison of structural equation and dynamic causal models. Neuroimage 23(Suppl 1):S264–74. Google Scholar Crossref, Medline|
|Plow EB, Carey JR, Nudo RJ, Pascual-Leone A. 2009. Invasive cortical stimulation to promote recovery of function after stroke: a critical appraisal. Stroke 40(5):1926–31. Google Scholar Crossref, Medline|
|Pollock A, Baer G, Campbell P, Choo PL, Forster A, Morris J, and others. 2014. Physical rehabilitation approaches for the recovery of function and mobility following stroke. Cochrane Database Syst Rev (4):CD001920. Google Scholar Medline|
|Posteraro F, Mazzoleni S, Aliboni S, Cesqui B, Battaglia A, Dario P, and others. 2009. Robot-mediated therapy for paretic upper limb of chronic patients following neurological injury. J Rehabil Med 41(12):976–80. Google Scholar Crossref, Medline|
|Qiu M, Darling WG, Morecraft RJ, Ni CC, Rajendra J, Butler AJ. 2011. White matter integrity is a stronger predictor of motor function than BOLD response in patients with stroke. Neurorehabil Neural Repair 25(3):275–84. Google Scholar Link|
|Ramachandran VS, Rogers-Ramachandran D. 1996. Synaesthesia in phantom limbs induced with mirrors. Proc Biol Sci 263(1369):377–86. Google Scholar Crossref, Medline|
|Ramos-Murguialday A, Broetz D, Rea M, Laer L, Yilmaz O, Brasil FL, and others. 2013. Brain-machine interface in chronic stroke rehabilitation: a controlled study. Ann Neurol 74(1):100–8. Google ScholarCrossref, Medline|
|Rebesco JM, Stevenson IH, Körding KP, Solla SA, Miller LE. 2010. Rewiring neural interactions by micro-stimulation. Front Syst Neurosci 4:39. Google Scholar Crossref, Medline|
|Rossi S, Hallett M, Rossini PM, Pascual-Leone A, Safety of TMS Consensus Group. 2009. Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research. Clin Neurophysiol 120(12):2008–39. Google Scholar Crossref, Medline|
|Rossiter HE, Boudrias MH, Ward NS. 2014. Do movement-related beta oscillations change after stroke? J Neurophysiol 112(9):2053–8. Google Scholar Crossref, Medline|
|Ruber T, Schlaug G, Lindenberg R. 2012. Compensatory role of the cortico-rubro-spinal tract in motor recovery after stroke. Neurology 79(6):515–22. Google Scholar Crossref, Medline|
|Ruffini G, Fox MD, Ripolles O, Miranda PC, Pascual-Leone A. 2014. Optimization of multifocal transcranial current stimulation for weighted cortical pattern targeting from realistic modeling of electric fields. Neuroimage 89:216–25. Google Scholar Crossref, Medline|
|Rusjan PM, Barr MS, Farzan F, Arenovich T, Maller JJ, Fitzgerald PB, and others. 2010. Optimal transcranial magnetic stimulation coil placement for targeting the dorsolateral prefrontal cortex using novel magnetic resonance image-guided neuronavigation. Hum Brain Mapp 31(11):1643–52. Google Scholar Medline|
|Saposnik G, Cohen LG, Mamdani M, Pooyania S, Ploughman M, Cheung D, and others. 2016. Efficacy and safety of non-immersive virtual reality exercising in stroke rehabilitation (EVREST): a randomised, multicentre, single-blind, controlled trial. Lancet Neurol 15(10):1019–27. Google Scholar Crossref, Medline|
|Saposnik G, Levin M, Outcome Research Canada Working G. 2011. Virtual reality in stroke rehabilitation: a meta-analysis and implications for clinicians. Stroke 42(5):1380–6. Google Scholar Crossref, Medline|
|Sato S, Bergmann TO, Borich MR. 2015. Opportunities for concurrent transcranial magnetic stimulation and electroencephalography to characterize cortical activity in stroke. Front Hum Neurosci 9:250. Google ScholarCrossref, Medline|
|Sauseng P, Klimesch W, Gerloff C, Hummel FC. 2009. Spontaneous locally restricted EEG alpha activity determines cortical excitability in the motor cortex. Neuropsychologia 47(1):284–8. Google Scholar Crossref, Medline|
|Schulz R, Braass H, Liuzzi G, Hoerniss V, Lechner P, Gerloff C, and others. 2015a. White matter integrity of premotor-motor connections is associated with motor output in chronic stroke patients. Neuroimage Clin 7:82–6. Google Scholar Crossref, Medline|
|Schulz R, Frey BM, Koch P, Zimerman M, Bonstrup M, Feldheim J, and others. 2017a. Cortico-cerebellar structural connectivity is related to residual motor output in chronic stroke. Cereb Cortex 27(1):635–45. Google Scholar Medline|
|Schulz R, Koch P, Zimerman M, Wessel M, Bonstrup M, Thomalla G, and others. 2015b. Parietofrontal motor pathways and their association with motor function after stroke. Brain 138(Pt 7):1949–60. Google Scholar Crossref, Medline|
|Schulz R, Park CH, Boudrias MH, Gerloff C, Hummel FC, Ward NS. 2012. Assessing the integrity of corticospinal pathways from primary and secondary cortical motor areas after stroke. Stroke 43(8):2248–51. Google Scholar Crossref, Medline|
|Schulz R, Park E, Lee J, Chang WH, Lee A, Kim YH, and others. 2017b. Synergistic but independent: the role of corticospinal and alternate motor fibers for residual motor output after stroke. Neuroimage Clin 15:118–24. Google Scholar Crossref, Medline|
|Shafi MM, Brandon Westover M, Oberman L, Cash SS, Pascual-Leone A. 2014. Modulation of EEG functional connectivity networks in subjects undergoing repetitive transcranial magnetic stimulation. Brain Topogr 27(1):172–91. Google Scholar Crossref, Medline|
|Sitaram R, Veit R, Stevens B, Caria A, Gerloff C, Birbaumer N, and others. 2012. Acquired control of ventral premotor cortex activity by feedback training: an exploratory real-time FMRI and TMS study. Neurorehabil Neural Repair 26(3):256–65. Google Scholar Link|
|Smajlovic D. 2015. Strokes in young adults: epidemiology and prevention. Vasc Health Risk Manag 11:157–64. Google Scholar Crossref, Medline|
|Small SL, Buccino G, Solodkin A. 2012. The mirror neuron system and treatment of stroke. Dev Psychobiol 54(3):293–310. Google Scholar Crossref, Medline|
|Stevens JA, Stoykov ME. 2003. Using motor imagery in the rehabilitation of hemiparesis. Arch Phys Med Rehabil 84(7):1090–2. Google Scholar Crossref, Medline|
|Stinear CM, Barber PA, Petoe M, Anwar S, Byblow WD. 2012. The PREP algorithm predicts potential for upper limb recovery after stroke. Brain 135(Pt 8):2527–35. Google Scholar Crossref, Medline|
|Stinear CM, Byblow WD. 2014. Predicting and accelerating motor recovery after stroke. Curr Opin Neurol 27(6):624–30. Google Scholar Medline|
|Stinear CM, Byblow WD, Ackerley SJ, Barber PA, Smith MC. 2017. Predicting recovery potential for individual stroke patients increases rehabilitation efficiency. Stroke 48(4):1011–9. Google Scholar Crossref, Medline|
|Strens LH, Asselman P, Pogosyan A, Loukas C, Thompson AJ, Brown P. 2004. Corticocortical coupling in chronic stroke: its relevance to recovery. Neurology 63(3):475–84. Google Scholar Crossref, Medline|
|Stuck RA, Marshall LM, Sivakumar R. 2014. Feasibility of SaeboFlex upper-limb training in acute stroke rehabilitation: a clinical case series. Occup Ther Int 21(3):108–14. Google Scholar Crossref, Medline|
|Takeuchi N, Izumi S. 2015. Combinations of stroke neurorehabilitation to facilitate motor recovery: perspectives on Hebbian plasticity and homeostatic metaplasticity. Front Hum Neurosci 9:349. Google Scholar Crossref, Medline|
|Tang C, Zhao Z, Chen C, Zheng X, Sun F, Zhang X and others. 2016. Decreased functional connectivity of homotopic brain regions in chronic stroke patients: a resting state fMRI study. PLoS One 11(4):e0152875. Google Scholar Crossref, Medline|
|Taub E, Miller NE, Novack TA, Cook EW3rd, Fleming WC, Nepomuceno CS, and others. 1993. Technique to improve chronic motor deficit after stroke. Arch Phys Med Rehabil 74(4):347–54. Google Scholar Medline|
|Thut G, Veniero D, Romei V, Miniussi C, Schyns P, Gross J. 2011. Rhythmic TMS causes local entrainment of natural oscillatory signatures. Curr Biol 21(14):1176–85. Google Scholar Crossref, Medline|
|Truelsen T, Piechowski-Jozwiak B, Bonita R, Mathers C, Bogousslavsky J, Boysen G. 2006. Stroke incidence and prevalence in Europe: a review of available data. Eur J Neurol 13(6):581–98. Google Scholar Crossref, Medline|
|Turolla A, Dam M, Ventura L, Tonin P, Agostini M, Zucconi C, and others. 2013. Virtual reality for the rehabilitation of the upper limb motor function after stroke: a prospective controlled trial. J Neuroeng Rehabil 10:85. Google Scholar Crossref, Medline|
|Uswatte G, Taub E. 2013. Constraint-induced movement therapy: a method for harnessing neuroplasticity to treat motor disorders. Prog Brain Res 207:379–401. Google Scholar Crossref, Medline|
|Van Peppen RP, Kwakkel G, Wood-Dauphinee S, Hendriks HJ, Van der Wees PJ, Dekker J. 2004. The impact of physical therapy on functional outcomes after stroke: what’s the evidence? Clin Rehabil 18(8):833–62. Google Scholar Link|
|Varkuti B, Guan C, Pan Y, Phua KS, Ang KK, Kuah CW, and others. 2013. Resting state changes in functional connectivity correlate with movement recovery for BCI and robot-assisted upper-extremity training after stroke. Neurorehabil Neural Repair 27(1):53–62. Google Scholar Link|
|Veerbeek JM, Kwakkel G, van Wegen EE, Ket JC, Heymans MW. 2011. Early prediction of outcome of activities of daily living after stroke: a systematic review. Stroke 42(5):1482–8. Google Scholar|
|Vourvopoulos A, Bermudez IBS. 2016. Motor priming in virtual reality can augment motor-imagery training efficacy in restorative brain-computer interaction: a within-subject analysis. J Neuroeng Rehabil 13(1):69. Google Scholar Crossref, Medline|
|Wagner T, Fregni F, Eden U, Ramos-Estebanez C, Grodzinsky A, Zahn M, and others. 2006. Transcranial magnetic stimulation and stroke: a computer-based human model study. Neuroimage 30(3):857–70. Google Scholar Crossref, Medline|
|Westlake KP, Nagarajan SS. 2011. Functional connectivity in relation to motor performance and recovery after stroke. Front Syst Neurosci 5:8. Google Scholar Crossref, Medline|
|Winstein CJ, Stein J, Arena R, Bates B, Cherney LR, Cramer SC, and others. 2016. Guidelines for adult stroke rehabilitation and recovery: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 47(6):e98–e169. Google Scholar Crossref, Medline|
|Wolf SL, Thompson PA, Winstein CJ, Miller JP, Blanton SR, Nichols-Larsen DS, and others. 2010. The EXCITE stroke trial: comparing early and delayed constraint-induced movement therapy. Stroke 41(10):2309–15. Google Scholar Crossref, Medline|
|Wolf SL, Winstein CJ, Miller JP, Taub E, Uswatte G, Morris D, and others. 2006. Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA 296(17):2095–104. Google Scholar Crossref, Medline|
|World Health Organization. 2016. World health statistics. http://www.who.int/gho/publications/world_health_statistics/2016/en/. Google Scholar|
|Wu CY, Chen YA, Lin KC, Chao CP, Chen YT. 2012. Constraint-induced therapy with trunk restraint for improving functional outcomes and trunk-arm control after stroke: a randomized controlled trial. Phys Ther 92(4):483–92. Google Scholar Crossref, Medline|
|Wu CY, Chuang LL, Lin KC, Chen HC, Tsay PK. 2011. Randomized trial of distributed constraint-induced therapy versus bilateral arm training for the rehabilitation of upper-limb motor control and function after stroke. Neurorehabil Neural Repair 25(2):130–9. Google Scholar Link|
|Young BM, Nigogosyan Z, Remsik A, Walton LM, Song J, Nair VA, and others. 2014. Changes in functional connectivity correlate with behavioral gains in stroke patients after therapy using a brain-computer interface device. Front Neuroeng 7:25. Google Scholar Medline|
|Zeiler SR, Krakauer JW. 2013. The interaction between training and plasticity in the poststroke brain. Curr Opin Neurol 26(6):609–16. Google Scholar Crossref, Medline|
|Zimerman M, Heise KF, Hoppe J, Cohen LG, Gerloff C, Hummel FC. 2012. Modulation of training by single-session transcranial direct current stimulation to the intact motor cortex enhances motor skill acquisition of the paretic hand. Stroke 43(8):2185–91. Google Scholar Crossref, Medline|
|Zrenner C, Belardinelli P, Muller-Dahlhaus F, Ziemann U. 2016. Closed-loop neuroscience and non-invasive brain stimulation: a tale of two loops. Front Cell Neurosci 10:92. Google Scholar Crossref, Medline|
[ARTICLE] Brain regions important for recovery after severe post-stroke upper limb paresis – Full Text
Background The ability to predict outcome after stroke is clinically important for planning treatment and for stratification in restorative clinical trials. In relation to the upper limbs, the main predictor of outcome is initial severity, with patients who present with mild to moderate impairment regaining about 70% of their initial impairment by 3 months post-stroke. However, in those with severe presentations, this proportional recovery applies in only about half, with the other half experiencing poor recovery. The reasons for this failure to recover are not established although the extent of corticospinal tract damage is suggested to be a contributory factor. In this study, we investigated 30 patients with chronic stroke who had presented with severe upper limb impairment and asked whether it was possible to differentiate those with a subsequent good or poor recovery of the upper limb based solely on a T1-weighted structural brain scan.
Methods A support vector machine approach using voxel-wise lesion likelihood values was used to show that it was possible to classify patients as good or poor recoverers with variable accuracy depending on which brain regions were used to perform the classification.
Results While considering damage within a corticospinal tract mask resulted in 73% classification accuracy, using other (non-corticospinal tract) motor areas provided 87% accuracy, and combining both resulted in 90% accuracy.
Conclusion This proof of concept approach highlights the relative importance of different anatomical structures in supporting post-stroke upper limb motor recovery and points towards methodologies that might be used to stratify patients in future restorative clinical trials.
Stroke is one of the the most common causes of physical disability worldwide and about 80% of stroke survivors experience impairment of movement on one side of the body.1 Hand and arm impairment in particular is often persistent, disabling and a major contributor to reduced quality of life.2 The main predictor of long-term outcome of upper limb function is the level of initial impairment.3 This can be quantified as the proportional recovery rule which states that by 3 months, patients with stroke will recover about 70% of the initial upper limb motor impairment that has been observed on day 3 post-stroke.4–6 The prediction works extremely well for those presenting with mild to moderate upper limb impairment, but in only about half of those with initially severe upper limb impairment.4–6 In the other half, patients do worse than predicted, that is, there is a failure of proportional recovery. A key question then is, what is the difference between patients with stroke matched for initial severity who go on and have different recovery trajectories? The answer to this will point to the factors that are important for the dynamic process of recovery independent from the causes of initial impairment.
One possibility is the anatomy of the damage may be different in each group. A number of recent studies have proposed that the corticospinal tract (CST) plays a decisive role in this categorical difference7–11 as cortical reorganisation for improved motor function ultimately requires access for cortical motor areas to muscles. However, CST lesion load correlates with initial motor impairment,12 which is the major predictor of long-term outcome. It is therefore reasonable to ask how much CST lesion load can improve prediction of long-term outcome over and above initial severity. Furthermore, most of the patients involved in these studies had suffered from subcortical stroke and recent work has suggested that taking account of cortical damage after stroke can improve prediction of the motor clinical consequences.13 14
In this study, we investigated 30 patients with chronic stroke with a range of lesion locations (cortical and/or subcortical involvement) known to have presented with severe initial upper limb impairment but who had gone on to have quite different recovery trajectories. We applied a support vector machine approach to data representing lesion likelihood derived from structural T1-weighted MRI to answer the following questions. First, how accurately can patients with stroke with severe initial upper limb impairment be classified as having either good or poor recovery using only data extracted from whole brain structural MRI? Second, which brain regions contribute most to the classification? The results have the potential to transform how prediction of long-term upper limb outcome after stroke is achieved in routine clinical practice in future. The ability to easily and accurately predict outcome with standard clinical neuroimaging would have important implications for planning of treatment but also for stratification in future trials of restorative therapies.15[…]
Objective: To assess, the duration of treatment effect for incobotulinumtoxinA treatment intervals using a pooled analysis of 2 phase 3 clinical studies in upper-limb post-stroke spasticity (ULPSS).
Background: The efficacy and safety of incobotulinumtoxinA in ULPSS has been confirmed in 2 phase 3 studies. Study 0410 included a randomized placebo-controlled period and an open-label extension (OLEX). OLEX reinjection intervals were flexible (≥12 week intervals with doses ≤400U). Study 3001 included fixed 12-week treatment intervals (TIs). In study 0410, investigators and subjects mutually determined the need for re-injection on the basis of pre-specified criteria (eg, Ashworth scale scores, investigator’s clinical impression).
Design/Methods: All TIs between 2 consecutive incobotulinumtoxinA injections were included, except TIs prior to the end of study visit and those with doses <300U. Outliers and factors other than a medical need for re-injection (eg, visit scheduling) were accounted for using duration thresholds applied during the analysis; the number of subjects with ≥1 TI above a threshold was calculated.
Results: A total of 347/437 incobotulinumtoxinA TIs met the inclusion criteria (range of re-injection intervals observed: 9–49 weeks). Over half (54.8%) of the re-injections were administered at week ≥14. The mean incobotulinumtoxinA TI was 15.46 weeks (standard devation: 4.63 weeks). A majority of subjects (59.1%) had ≥1 TI with re-injection at week ≥16; 33.1% of subjects had 1, 22.1% had 2 and 3.9% had 3. Many subjects (42.5%) had ≥1 TI with re-injection at week ≥18.
Conclusions: These results demonstrate variability in the duration of treatment effect, which supports the use of flexible and individualized dosing intervals for the treatment of ULPSS. The duration of treatment effect was ≥14 weeks after most treatments; however, a considerable proportion of patients experienced effects lasting up to 20 weeks.
[Thesis] Ubiquitous and Wearable Computing Solutions for Enhancing Motor Rehabilitation of the Upper Extremity Post-Stroke
Coffey, Aodhan L. (2016) Ubiquitous and Wearable Computing Solutions for Enhancing Motor Rehabilitation of the Upper Extremity Post-Stroke. PhD thesis, National University of Ireland Maynooth.
A stroke is the loss of brain function caused by a sudden interruption in the blood supply of the brain. The extent of damage caused by a stroke is dependent on many factors such as the type of stroke, its location in the brain, the extent of oxygen deprivation and the criticality of the neural systems affected. While stroke is a non-cumulative disease, it is nevertheless a deadly pervasive disease and one of the leading causes of death and disability worldwide. Those fortunate enough to survive stroke are often left with some form of serious long-term disability. Weakness or paralysis on one side of the body, or in an individual limb is common after stroke. This affects independence and can greatly limit quality of life.
Stroke rehabilitation represents the collective effort to heal the body following stroke and to return the survivor to as normal a life as possible. It is well established that rehabilitation therapy comprising task-specific, repetitive, prolonged movement training with learning is an effective method of provoking the necessary neuroplastic changes required which ultimately lead to the recovery of function after stroke. However, traditional means of delivering such treatments are labour intensive and constitute a significant burden for the therapist limiting their ability to treat multiple patients. This makes rehabilitation medicine a costly endeavour that may benefit from technological contributions. As such, stroke has severe social and economic implications, problems exasperated by its age related dependencies and the rapid ageing of our world. Consequently these factors are leading to a rise in the number living with stroke related complications. This is increasing the demand for post stroke rehabilitation services and places an overwhelming amount of additional stress on our already stretched healthcare systems.
Therefore, new innovative solutions are urgently required to support the efforts of healthcare professionals in an attempt to alleviate this stress and to ultimately improve the quality of care for stroke survivors. Recent innovations in computer and communication technology have lead to a torrent of research into ubiquitous, pervasive and distributed technologies, which might be put to great use for rehabilitative purpose. Such technology has great potential utility to support the rehabilitation process through the delivery of complementary, relatively autonomous rehabilitation therapy, potentially in the comfort of the patient’s own home.
This thesis describes concerted work to improve the current state and future prospects of stroke rehabilitation, through investigations which explore the utility of wearable, ambient and ubiquitous computing solutions for the development of potentially transformative healthcare technology. Towards this goal, multiple different avenues of the rehabilitation process are explored, tackling the full chain of processes involved in motor recovery, from brain to extremities. Subsequently, a number of cost effective prototype devices for use in supporting the ongoing rehabilitation process were developed and tested with healthy subjects, a number of open problems were identified and highlighted, and tentative solutions for home-based rehabilitation were put forward. It is envisaged that the use of such technology will play a critical role in abating the current healthcare crisis and it is hoped that the ideas presented in this thesis will aid in the progression and development of cost effective, efficacious rehabilitation services, accessible and affordable to all in need.
[ARTICLE] Effect of early use of AbobotulinumtoxinA after stroke on spasticity progression: Protocol for a randomised controlled pilot study in adult subjects with moderate to severe upper limb spasticity (ONTIME pilot) – Full Text
Approximately 15 million people suffer a stroke annually, up to 40% of which may develop spasticity, which can result in impaired limb function, pain and associated involuntary movements affecting motor control.
Robust clinical data on spasticity progression, associated symptoms development and functional impairment is scarce. Additionally, maximal duration of muscle tone reduction following botulinum toxin type A (BoNT-A) injections remains undetermined. The ONTIME pilot study aims to explore these issues and evaluate whether abobotulinumtoxinA 500 U (Dysport®; Ipsen) administered intramuscularly within 12 weeks following stroke delays the appearance or progression of symptomatic (disabling) upper limb spasticity (ULS).
ONTIME is a 28-week, phase 4, randomised, double-blind, placebo-controlled, exploratory pilot study initiated at four centres across Malaysia, the Philippines, Singapore and Thailand. Subjects (n = 42) with moderate to severe ULS (modified Ashworth scale [MAS] score ≥2) in elbow flexors or pronators, wrist flexors, or finger flexors will be recruited. Subjects will be randomised 2:1 to abobotulinumtoxinA 500 U or placebo (single dose 2–12 weeks after first-ever stroke).
Primary efficacy will be measured by time between initial injection and visit at which reinjection criteria (MAS score ≥2 in the primary targeted muscle group and appearance or reappearance of symptomatic ULS) are met. Follow-up visits will be 4-weekly to a maximum of 28 weeks.
This pilot study will facilitate the design and sample size calculation of further confirmatory studies, and is expected to provide insights into the optimal management of post-stroke patients, including timing of BoNT-A therapy and follow-up duration.
An estimated 15 million people suffer a stroke annually ; of whom, up to 40% develop post-stroke spasticity, a state of velocity-dependent increase in tonic stretch reflexes (‘muscle tone’) with exaggerated tendon jerks  most commonly affecting upper limbs ; ; ;  ; . Post-stroke spasticity impedes active and passive functioning of affected limb(s), impairs activities of daily living and requires long-term treatment; associated healthcare costs are up to four-fold greater than for stroke survivors without spasticity . Furthermore, spasticity may involve pain and involuntary movements, interfering with dressing, gait, balance and walking speed, and can disrupt rehabilitation . Without functional improvement, secondary musculoskeletal complications such as contractures and deformity may develop .
Data on the proportion of patients with post-stroke spasticity developing disability are scarce. One survey (N = 140) reported a prevalence of 17% spasticity and 4% disabling spasticity with a year . Upper limb involvement and age <65 years were associated with disabling spasticity in this study . In other studies, over a third of individuals developed spasticity within a year, including 20% with severe spasticity  ; , suggesting higher rates of disabling spasticity than those reported by Lundström et al. .
Studies evaluating the timeframe for developing spasticity symptoms post-stroke are also few, with small cohorts (around 100 patients), but suggest the prevalence and severity of spasticity increases within a year post-stroke ; ; ; ;  ; . Certain studies indicate that spasticity symptoms and muscle tone changes are apparent in up to 25% of stroke victims within 2 weeks ;  ; . One study reported increased muscle tone as an early risk factor for developing severe disabling spasticity, particularly if it affected more than two joints, or was associated with a modified Ashworth scale (MAS) score ≥2 in one affected joint within 6 weeks post-stroke . Indeed, spasticity may persist , and the severity of upper limb spasticity (ULS) may increase over time, most commonly affecting anti-gravity muscles, during the first 2 weeks and at 3 months post-stroke .
AbobotulinumtoxinA is an effective focal intervention for reducing ULS  and coupled with neurorehabilitation is recommended in standard clinical practice  ; . Treatment with botulinum toxin A (BoNT-A) is generally delayed in post-stroke spasticity until patients show clinical signs of increased muscle tone, usually about 3 months following stroke , despite evidence that symptoms begin much earlier.
Recent studies aimed to evaluate whether earlier post-stroke treatment with BoNT-A may prevent disabling spasticity development ;  ;  and demonstrate that BoNT-A administered within 3 months provides sustained improvement in muscle tone. However, there is a paucity of robust clinical data on spasticity progression timeframes, associated symptom development, functional impairment, and maximal duration of muscle tone reduction with BoNT-A.
The ONTIME pilot study explores these foregoing issues to establish whether treatment with abobotulinumtoxinA (Dysport®) within 2–12 weeks post-stroke might delay symptomatic or disabling spasticity development, and to assess the duration of this effect. Importantly, this study incorporates composite measure of active and passive functionality, involuntary movements and pain.
Continue —> Effect of early use of AbobotulinumtoxinA after stroke on spasticity progression: Protocol for a randomised controlled pilot study in adult subjects with moderate to severe upper limb spasticity (ONTIME pilot)
[Master Thesis] A smart brace to support spasticity management in post-stroke rehabilitation – Full Text PDF
A smart brace to support spasticity management in poststroke rehabilitation
This report covers the design of a product to help stroke survivors who are suffering from chronic spasticity manage their everyday activities. In the Netherlands alone, 44.000 people suffer from a Cerebro-Vascular Accident (CVA) each year. A CVA, more commonly known as a stroke, results in brain trauma with afflictions such as paralysis, fatigue and spasticity. It is possible to recover some, if not all, motor function though intensive physiotherapy, which requires long-term stay at a rehabilitation clinic in severe cases. Due to limited room and staff, only 12% of stroke survivors end up rehabilitating in a clinic. The remaining survivors are sent home, and will to travel to the clinic 3-5 times per week for therapy as part of the outpatient rehabilitation. Adjuvo Motion, a young start-up, aims to improve the situation of stroke survivors by bringing the rehabilitation centre to their home through the Adjuvo Platform, which allows them to perform exercises in the context of virtual tasks. They proposed an assignment to extend their product portfolio with a Range of Motion assessment device that is suited for those suffering from spasticity. Spasticity occurs in roughly 60% of stroke survivors with varying degrees of intensity. It is caused by the damaged parts of the brain sending conflicting signals to the muscles, causing them to contract. This inhibits the survivor’s ability to perform daily tasks, but can be solved temporarily with stretching exercises. A solution to compensate for these spastic forces using a passive-assist device was proposed at the start of this project. The project was divided into four stages: Analysis, Synthesis, Embodiment and Evaluation. During the Analysis stage, interviews with a Physiotherapist and stroke survivor and literature studies regarding anatomy, the state of the art and relevant technologies were used to create a framework for the design of a smart passive-assist glove. Looking at competing products, there is a demand for passive assist and Range of Motion assessment functionalities, yet a combination of these in a single device is not yet present in the market. During the Synthesis stage, the design problem of the passive assist device was split into three groups: Orthoses; the connections to the body, Passive Assist; the compensation medium, and RoM measurement; the sensing mechanism(s). These three groups were further split into sub-problems, the solutions to which were compiled into a Morphological Chart. By combining the solution within this chart, three promising concept designs were created: One upgrade to the existing sensor glove, one full integration of sensing and passive assist, and one passive assist glove with removeable sensors. To evaluate these concepts, eight criteria were established and weighted with the help of a physiotherapist. In order to create an objective assessment, the criteria were kept strictly quantitative and the three designs were first scored against the Raphael Smart Glove by Neofect using early prototypes. These scores were then used to evaluate the designs relative to each other, which resulted in an overall higher score for the concept with separable electronics. Making the sensor part of the brace removeable allowed the product to be used during daily life as well as physiotherpy exercises, and proved a key benefit in keeping the product clean. Based on the chosen design, four iterations of prototypes were made, which were tested with healthy subject. During this stage, it became clear that flex sensors are be best suited to create a range of motion assessment for spastic stroke patients, since it is less important to know how well they perform a task, and more important to know if they can actually perfrom it. Based on a quantified use case, the four sub-assemblies; the Wrist Wrap, Finger Modules and Sensor Module, and their connections were materialized in the Embodiment design stage. When selecting production methods, the main challenge was a small batch size of 1000 units, which made conventional techniques for mass production, such as Injection Molding, less attractive. This stage ended in an assesment of the product’s production price and durability: The product would cost €250 to make, and would last for 2.5 years before the Velcro connection on the Wrist Wrap would become too weak to sustain the spasticity forces. In the Evaluation stage, the product was evaluated on the seven most important requirements established during the analysis stage. For several of these, a user test was performed, again with healthy subject. While the Adjuvo Auxilius passed most theoretical requirements, the user tests on healthy subjects could not be used to draw any conclusions regarding its effectiveness on spastic stroke patients. However, since the product’s working principle is based on that of existing spasticity compensation products, the prediction is that the Auxilius will be an effective therapy supplement. The result of this project is the Adjuvo Auxilius; a spasticity-compensation glove with modular sensors, which can be added to allow virtual (stretching) exercises through the Adjuvo Motion’s platform. The results of these exercises are used to create a remote assessment of the patients motor skills, and to adjust the therapy if needed.
[THESIS] Returning to driving post-stroke: Identifying key factors for best practice decision making over the recovery trajectory -Full text PDF
The purpose of this thesis is to examine the process of returning to driving post-stroke in order to contribute to best practice decision making. A decision tree is suggested to build patient-centred procedures for returning to driving along the post-stroke recovery trajectory.
Part one reviews literature on the return to driving process post-stroke and identifies gaps in knowledge. The stroke recovery trajectory’s three main phases of recovery (acute, rehabilitation and community care) are outlined and act as a framework for the thesis structure. Part two of the thesis describes five separate but related studies carried out to address the research gaps identified.
The first study is a qualitative study that examines attitudes and perceptions of stroke survivors from one to 16 weeks post-stroke. Independence was found to be the primary motivator in stroke survivors’ decisions about fitness to drive. However, during the acute phase stroke survivors were focused on their physical recovery, not returning to driving. Study participants had little knowledge of return to driving procedures or legislation, despite information being available. Gender differences were apparent in factors affecting the return to driving decision making.
The second study examines the psychometric property of practice effect on the Useful Field of View (UFOV, Ball & Owsley, 1993) a pre-driving screening assessment. UFOV scores have been found to be associated with on-road driving assessment scores (George & Crotty, 2010) and used in medical recommendations. Study participants were all stroke survivors with a control group performing the UFOV at three months and assessment group at one, two and three months post-stroke. Findings suggest there was no practice effect in relation to a single three month post-stroke time point. Timing of reassessment was also examined.
The third study examined self-perceived driving confidence measured by the Adelaide Driving Self Efficacy Scale (ADSES, George et al., 2007; George & Crotty, 2010) and driving habits. Results indicated there was a significant statistical association between low self-perceived driving confidence and lower kilometres driven per week, reduce driving scope, driving closer to home and avoiding challenging driving situations.
The fourth study explored self-perceived driving confidence of post-stroke drivers and their non-stroke, aged-matched driving peers measured by the ADSES. No difference was found, suggesting once stroke survivors have returned to driving they have the same levels of selfperceived driving confidence and potential driving scope as their non-stroke driving peers.
The final study focused on decisions to relinquish a driver’s licence among the older Australian general population and used a novel Discrete Choice Experiment (DCE) methodological approach. A general population was used to establish a norm with which future research on specific chronic conditions such as stroke could make comparison. Recommendation of General Practitioners’ (GPs), participants’ local doctors was found to be the primary influencing factor in the decision of older Australians to relinquish their driver’s licence. Advice from family and friends, age and crash risk in the next year were also influencing factors. The costs and availability of public transport options were not influencing factors.
The last chapter of this thesis is the Discussion section which identifies the common themes emerging along with limitations and recommendations for future research directions.
[ARTICLE] When Does Return of Voluntary Finger Extension Occur Post-Stroke? A Prospective Cohort Study – Full Text
Objectives: Patients without voluntary finger extension early post-stroke are suggested to have a poor prognosis for regaining upper limb capacity at 6 months. Despite this poor prognosis, a number of patients do regain upper limb capacity. We aimed to determine the time window for return of voluntary finger extension during motor recovery and identify clinical characteristics of patients who, despite an initially poor prognosis, show upper limb capacity at 6 months post-stroke.
Methods: Survival analysis was used to assess the time window for return of voluntary finger extension (Fugl-Meyer Assessment hand sub item finger extension≥1). A cut-off of ≥10 points on the Action Research Arm Test was used to define return of some upper limb capacity (i.e. ability to pick up a small object). Probabilities for regaining upper limb capacity at 6 months post-stroke were determined with multivariable logistic regression analysis using patient characteristics.
Results: 45 of the 100 patients without voluntary finger extension at 8 ± 4 days post-stroke achieved an Action Research Arm Test score of ≥10 points at 6 months. The median time for regaining voluntary finger extension for these recoverers was 4 weeks (lower and upper percentile respectively 2 and 8 weeks). The median time to return of VFE was not reached for the whole group (N = 100). Patients who had moderate to good lower limb function (Motricity Index leg≥35 points), no visuospatial neglect (single-letter cancellation test asymmetry between the contralesional and ipsilesional sides of <2 omissions) and sufficient somatosensory function (Erasmus MC modified Nottingham Sensory Assessment≥33 points) had a 0.94 probability of regaining upper limb capacity at 6 months post-stroke.
Conclusions: We recommend weekly monitoring of voluntary finger extension within the first 4 weeks post-stroke and preferably up to 8 weeks. Patients with paresis mainly restricted to the upper limb, no visuospatial neglect and sufficient somatosensory function are likely to show at least some return of upper limb capacity at 6 months post-stroke.
Voluntary finger extension (VFE) is an important early predictor of recovery of upper limb capacity at 6 months post-stroke[1;2]. Patients without VFE within the first days post-stroke have been suggested to have a poor prognosis for regaining some upper limb capacity at 6 months[1–3]. Absence of VFE reflects the loss of functional corticospinal tract integrity, acknowledging that the hand muscles are almost solely innervated by contralateral corticospinal pathways. Indirect bilateral innervation of the hand muscles by the reticulospinal tract may also contribute to hand motor control after stroke. However, it remains unclear if the reticulospinal system can influence the digital extensor muscles of the paretic hand.
Despite an initially poor prognosis, some patients without VFE within the first days after stroke do regain upper limb capacity at 6 months. In view of the lack of evidence-based therapies for patients without VFE[7;8], this return of VFE seems most likely to be driven by spontaneous neurobiological processes such as alleviation of diaschisis. Unfortunately, the clinical characteristics as well as the optimal time window for recovery of VFE are unknown, due to lack of prospective cohort studies in which patients are assessed serially at fixed times post-stroke[10;11]. More knowledge regarding this time window is important for future prognostic algorithm development. Up till now, the most optimal timing and added value of neurophysiological and neuroimaging measurements with respect to clinical measurements like VFE are unclear.
The aims of the present study were therefore (1) to determine the clinical time window for return of VFE in ischemic stroke patients without VFE in the first days post-stroke, and (2) to identify clinical characteristics for the return of some upper limb capacity in these patients within the first 6 months after stroke. We hypothesized that return of VFE would occur within the purported time window of spontaneous neurobiological recovery between 0 and 10 weeks after stroke onset[10;12]. We also hypothesized that patients with lesions affecting upper limb function who exhibit no other neurological impairments such as visuospatial neglect and somatosensory dysfunction would have a high probability of regaining some upper limb capacity at 6 months[13–15].