Posts Tagged Upper Extremity

[Abstract] A soft supernumerary robotic finger and mobile arm support for grasping compensation and hemiparetic upper limb rehabilitation


In this paper, we present the combination of our soft supernumerary robotic finger i.e. Soft-SixthFinger with a commercially available zero gravity arm support, the SaeboMAS. The overall proposed system can provide the needed assistance during paretic upper limb rehabilitation involving both grasping and arm mobility to solve task-oriented activities. The Soft-SixthFinger is a wearable robotic supernumerary finger designed to be used as an active assistive device by post stroke patients to compensate the paretic hand grasp. The device works jointly with the paretic hand/arm to grasp an object similarly to the two parts of a robotic gripper. The SaeboMAS is a commercially available mobile arm support to neutralize gravity effects on the paretic arm specifically designed to facilitate and challenge the weakened shoulder muscles during functional tasks. The proposed system has been designed to be used during the rehabilitation phase when the arm is potentially able to recover its functionality, but the hand is still not able to perform a grasp due to the lack of an efficient thumb opposition. The overall system also act as a motivation tool for the patients to perform task-oriented rehabilitation activities.

With the aid of proposed system, the patient can closely simulate the desired motion with the non-functional arm for rehabilitation purposes, while performing a grasp with the help of the Soft-SixthFinger. As a pilot study we tested the proposed system with a chronic stroke patient to evaluate how the mobile arm support in conjunction with a robotic supernumerary finger can help in performing the tasks requiring the manipulation of grasped object through the paretic arm. In particular, we performed the Frenchay Arm Test (FAT) and Box and Block Test (BBT). The proposed system successfully enabled the patient to complete tasks which were previously impossible to perform.

Source: A soft supernumerary robotic finger and mobile arm support for grasping compensation and hemiparetic upper limb rehabilitation

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[Conference paper] Upper-Limb Kinematics During Feeding and Drinking – Abstract+References


Feeding and drinking are Activities of Daily Living which can be used to assess the motor control and functional ability of the upper limb. This paper presents the upper-limb kinematics during the execution of feeding and drinking activities, such analysis consisted in the measurement of angles of flexion for trunk and arm. Eight healthy subjects performed these activities in a simulated-environment while they were video recorded. Markers on anatomical landmarks were used to analyze the kinematics of the upper limb in the sagittal plane. Additionally an electro-hydraulic sensor was attached to each upper limb to assess the vertical position of the wrist relative to the shoulder. Results showed a difference on the angles of the elbow and trunk. The electro-hydraulic sensor showed to be an efficient way to record the vertical position of wrist.


Source: Upper-Limb Kinematics During Feeding and Drinking | SpringerLink

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[ARTICLE] Body-Machine Interfaces after Spinal Cord Injury: Rehabilitation and Brain Plasticity – Full Text HTML


The purpose of this study was to identify rehabilitative effects and changes in white matter microstructure in people with high-level spinal cord injury following bilateral upper-extremity motor skill training. Five subjects with high-level (C5–C6) spinal cord injury (SCI) performed five visuo-spatial motor training tasks over 12 sessions (2–3 sessions per week). Subjects controlled a two-dimensional cursor with bilateral simultaneous movements of the shoulders using a non-invasive inertial measurement unit-based body-machine interface. Subjects’ upper-body ability was evaluated before the start, in the middle and a day after the completion of training. MR imaging data were acquired before the start and within two days of the completion of training. Subjects learned to use upper-body movements that survived the injury to control the body-machine interface and improved their performance with practice. Motor training increased Manual Muscle Test scores and the isometric force of subjects’ shoulders and upper arms. Moreover, motor training increased fractional anisotropy (FA) values in the cingulum of the left hemisphere by 6.02% on average, indicating localized white matter microstructure changes induced by activity-dependent modulation of axon diameter, myelin thickness or axon number. This body-machine interface may serve as a platform to develop a new generation of assistive-rehabilitative devices that promote the use of, and that re-strengthen, the motor and sensory functions that survived the injury.

1. Introduction

Despite progress in the field of assistive technologies for people who suffered an injury to the spinal cord, most of the current devices to control computers and wheelchairs are set in place to require as little physical effort from the user as possible, and little attention has been paid to maintaining and strengthening the neural and muscular resources that survived the injury [1,2,3,4]. Spinal cord injury (SCI) leads to motor impairment, weakness, muscular and cortical atrophy and altered reflexes, and these have been shown to progress further with lack of exercise [5,6,7,8,9,10]. Even in individuals with injuries to the cervical spinal cord, some motor and sensory capacities may remain available in the upper body. Several studies have shown that using their remaining functions and keeping an active body is critical for people with SCI in order to avoid the collateral effects of paralysis and to potentially recover some of the lost mobility [5,6,7,11]. Therefore, it is crucial to develop the next generation of assistive-rehabilitative devices that promote learning through upper-body coordination.
Acquisition, retention and refinement of motor skills all rely on the capability of the nervous system to create new patterns of neural activation for accomplishing new tasks and for recovering lost motor functions [12]. Recent advances in neural imaging have allowed learning studies on juggling [13], balance [14] and body-machine interfaces (BMIs) by our group [15], to demonstrate motor skill learning-induced structural changes of cortical and subcortical areas in both gray matter and white matter by using diffusion tensor imaging (DTI). DTI non-invasively measures the direction and rate of water diffusion within tissue. White matter integrity is commonly measured by fractional anisotropy (FA), a normalized measure of the variance of the diffusion ellipsoid at each voxel [16]. FA values for white matter tissue have been shown to be affected by physiological parameters, such as axon diameter, axon number and myelin thickness [17].
Loss of somatosensory afference leads to functional cortical reorganization [18,19,20]. SCI has been shown to lead to spinal cord atrophy, cortical atrophy of primary and sensory cortex [8], descending motor tracts [9] and cortical reorganization of the sensorimotor system [8,10], and the degree of cortical reorganization is associated with the level of disability. Although the goal of most SCI treatments is to re-establish neural connections in order to restore motor function, it is unclear whether the anatomical and functional changes that follow injury can be reversed.
In this study, we investigated the rehabilitative effects and learning-induced changes in the brain white matter microstructure of people with high-level SCI after they practiced coordinated upper-body movements to control a computer cursor through a novel body-machine interface. Subjects learned to use the remaining ability of their shoulders and upper arms to perform movements that controlled a computer cursor to complete different related tasks. Complementary to [15], the purpose of this study was to identify changes in motor function and white matter by comparing clinical scores and FA values pre- and post-bilateral upper-body motor skill training in people with a high-level spinal cord injury. We started from the assumption that motor learning is likely to be associated with different brain reorganization in unimpaired subjects compared to subjects with tetraplegia, in consideration also of the greater need for the reorganization of motor functions in the latter group.

Continue —> Brain Sciences | Free Full-Text | Body-Machine Interfaces after Spinal Cord Injury: Rehabilitation and Brain Plasticity | HTML

Figure 5. Regions showing lower fractional anisotropy (FA) in spinal cord injury (SCI) subjects compared to controls. (A) Brain regions associated with motor function used to perform tract-based spatial statistics (TBSS) and ROI analyses; (B) TBSS results. Regions showing significantly higher (red-yellow) and lower (blue-light blue) FA values in SCI versus control subjects overlaid over the standard Montreal Neurological Institute (MNI)152 T1-weighted anatomical scan (p < 0.05, uncorrected). The location of each slice in Montreal Neurological Institute space is shown at the lower left section. a-s-pCR, anterior, superior and posterior corona radiata; CG, cingulum; g-bCC, genu and body of corpus callosum; a-pIC, anterior and posterior limbs of internal capsule.

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[WEB SITE] The Rehabilitation Gaming System

slideshow 1RGS is a highly innovative Virtual Reality (VR) tool for the rehabilitation of deficits that occur after brain lesions and has been successfully used for the rehabilitation of the upper extremities after stroke.
The RGS is based on the neurobiological considerations that plasticity of the brain remains  throughout life and therefore can be utilized to achieve functional reorganization of the brain areas affected by stroke. This can be realized by means of activation of secondary motor areas such as the so called mirror neurons system.

RGS deploys a deficit oriented training approach. Specifically, while training with RGS the patient is playing individualized games where movement execution is combined with the observation of correlated actions performed by a virtual body. The system optimizes the user’s training by analyzing the qualitative and quantitative aspects of the user’s performance. This warranties a detailed assessment of the deficits of the patient and their recovery dynamics.

Key articles and Recent publications

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Source: The Rehabilitation Gaming System | Rehabilitation Gaming System

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[Research Poster] Upper Limb Virtual Reality Training Provides Increased Activity Compared With Conventional Training for Severely Affected Subacute Patients After Stroke

To compare amount of activity of virtual reality (VR) and conventional task-oriented training (CT).

Source: Upper Limb Virtual Reality Training Provides Increased Activity Compared With Conventional Training for Severely Affected Subacute Patients After Stroke – Archives of Physical Medicine and Rehabilitation

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[Abstract+References] Development of a tool to facilitate real life activity retraining in hand and arm therapy

Successful recovery of upper extremity function after stroke is more likely when the affected limb is used regularly in daily life. We developed an iPad (Apple) application called the ‘Aid for Decision-Making in Occupation Choice for Hand’ to facilitate daily upper extremity use. This study examined the suitability of items and pictures in the Aid for Decision-Making in Occupation Choice for Hand, and tested a paper prototype of the application (which has since been produced).

We used a Delphi method with 10 expert occupational therapists to refine the items in the aid. Next, we prepared pictures of items in the aid and confirmed their suitability by testing them with 10 patients (seven stroke, three cervical spondylotic myelopathy). Nine occupational therapists conducted field tests with a paper prototype of the aid in clinical practice to examine its utility.

After four Delphi rounds, we selected 130 items representing activities of daily living, organized into 16 categories. Of 130 pictures, 128 were recognizable to patients as representing the intended activities. Based on testing of the paper prototype, we found the Aid for Decision-Making in Occupation Choice for Hand process was suitable for clinical practice, and could be organized into six steps.

The Aid for Decision-Making in Occupation Choice for Hand process may promote daily upper extremity use. This application, since developed, now needs to be clinically tested in its digital form.


Ally BA, Budson AE (2007) The worth of pictures: Using high density event-related potentials to understand the memorial power of pictures and the dynamics of recognition memory. NeuroImage 35(1): 378395. Google Scholar CrossRef, Medline
Ally BA, Gold CA, Budson AE (2009) The picture superiority effect in patients with Alzheimer’s disease and mild cognitive impairment. Neuropsychologia 47(2): 595598. Google Scholar CrossRef, Medline
Ally BA, Waring JD, Beth EH, (2008) Aging memory for pictures: Using high-density event-related potentials to understand the effect of aging on the picture superiority effect. Neuropsychologia 46(2): 679689. Google Scholar CrossRef, Medline
Atwal A, Money A, Harvey M (2014) Occupational therapists’ views on using a virtual reality interior design application within the pre-discharge home visit process. Journal of Medical Internet Research 16(12): e283. Google Scholar CrossRef, Medline
Barecca S, Bohannon RW, Charness AL, (2001) Management of the Post Stroke Hemiplegic Arm and Hand: Treatment Recommendations of the 2001 Consensus Panel, Ontario, Canada: Heart and Stroke Foundation of Ontario. Google Scholar
Bouvat L, Kangas AJ, Szczech Moser C (2014) iPad apps in early intervention and school-based practice. Journal of Occupational Therapy, Schools & Early Intervention 7(1): 115. Google Scholar CrossRef
Che Daud AZ, Yau MK, Barnett F, (2016) Integration of occupation based intervention in hand injury rehabilitation: A randomized controlled trial. Journal of Hand Therapy 29(1): 3040. Google Scholar CrossRef
Curran T, Doyle J (2011) Picture superiority doubly dissociates the ERP correlates of recollection and familiarity. Journal of Cognitive Neuroscience 23(5): 12471262. Google Scholar CrossRef, Medline
Elwyn G, O’Connor A, Stacey D, (2006) International Patient Decision Aids Standards (IPDAS) collaboration. Developing a quality criteria framework for patient decision aid: Online international Delphi consensus process. British Medical Journal 333(7565): 417419. Google Scholar CrossRef, Medline
Embree LM, Budson AE, Ally BA (2012) Memorial familiarity remains intact for pictures but not for words in patients with amnestic mild cognitive impairment. Neuropsychologia 50(9): 23332340. Google Scholar CrossRef, Medline
Fujiwara Y, Shinkai S, Amano H, (2003) Test–retest variation in the Tokyo Metropolitan Institute of Gerontology Index of Competence in community-dwelling older people independent in daily living toward individual assessment of functional capacity. [Nihon Koshu Eisei Zasshi] 50(4): 360367. Google Scholar Medline
Gowland C, Stratford P, Ward M, (1993) Measuring physical impairment and disability with the Chedoke-McMaster Stroke Assessment. Stroke 24(1): 5863. Google Scholar CrossRef, Medline
Graham ID, Logan J, Bennett CL, (2007) Physicians’ intentions and use of three patient decision aids. BMC Medical Informatics and Decision Making 7(1): 20. Google Scholar CrossRef, Medline
Gummesson C, Atroshi I, Ekdahl C (2003) The disabilities of the arm, shoulder and hand (DASH) outcome questionnaire: Longitudinal construct validity and measuring self-rated health change after surgery. BMC Musculoskeletal Disorders 4(1): 11. Google Scholar CrossRef, Medline
Gummesson C, Ward MM, Atroshi I (2006) The shortened disabilities of the arm, shoulder and hand questionnaire (QuickDASH): Validity and reliability based on responses within the full-length DASH. BMC Musculoskeletal Disorders 7: 44. Google Scholar CrossRef, Medline
Klein RM, Bell B (1982) Self-care skills: Behavioral measurement with Klein-Bell ADL scale. Archives of Physical Medicine and Rehabilitation 63(7): 335338. Google Scholar Medline
Kopp B, Kunkel A, Flor H, (1997) The Arm Motor Ability Test: Reliability, validity, and sensitivity to change of an instrument for assessing disabilities in activities of daily living. Archives of Physical Medicine and Rehabilitation 78(6): 615620. Google Scholar CrossRef, Medline
Kurimoto S (2007) Validity and Reliability of the Hand 20. [Nihon Tegeka Gakkai Zasshi] 24(2): 14. Google Scholar
Lawton MP and Brody EM (1969) Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist 9(3): 179–186.
Lorah ER, Tincani M, Dodge J, (2013) Evaluating picture exchange and the iPad™ as a speech generating device to teach communication to young children with autism. Journal of Developmental and Physical Disabilities 25(6): 637649. Google Scholar CrossRef
Morris DM, Taub E, Mark VW (2006) Constraint-induced movement therapy: Characterizing the intervention protocol. Europa Medicophysica 42(3): 257–268. Google Scholar
O’Connor AM, Bennett CL, Stacey D, (2009) Decision aids for people facing health treatment or screening decisions. Cochrane Database Systematic Review 3: CD001431. Google Scholar
Ottenbacher KJ, Hsu Y, Granger CV, (1996) The reliability of the functional independence measure: A quantitative review. Archives of Physical Medicine and Rehabilitation 77(12): 12261232. Google Scholar CrossRef, Medline
Pollock A, Farmer SE, Brady MC, (2014) Interventions for improving upper limb function after stroke. Cochrane Database Systematic Review 11: CD010820. Google Scholar
Saposnik G, Chow CM, Gladstone D, (2014) iPad technology for home rehabilitation after stroke (iHOME): A proof-of-concept randomized trial. International Journal of Stroke 9(7): 956962. Google Scholar Link
Shepard RN (1967) Recognition memory for words, sentences, and pictures. Journal of Verbal Learning and Verbal Behavior 6(1): 156163. Google Scholar CrossRef
Shi YX, Tian JH, Yang KH, (2011) Modified constraint-induced movement therapy versus traditional rehabilitation in patients with upper-extremity dysfunction after stroke: A systematic review and meta-analysis. Archives of Physical Medicine and Rehabilitation 92(6): 972982. Google Scholar CrossRef, Medline
Sumsion T (1998) The Delphi technique: An adaptive research tool. The British Journal of Occupational Therapy 61(4): 153156. Google Scholar Link
Takebayashi T, Amano S, Hanada K, (2015) A one-year follow-up after modified constraint-induced movement therapy for chronic stroke patients with paretic arm: A prospective case series study. Topics in Stroke Rehabilitation 22(1): 1825. Google Scholar CrossRef, Medline
Takebayashi T, Koyama T, Amano S, (2013) A 6-month follow-up after constraint-induced movement therapy with and without transfer package for patients with hemiparesis after stroke: A pilot quasi-randomized controlled trial. Clinical Rehabilitation 27(5): 418426. Google Scholar Link
Taub E, Uswatte G, King DK, (2006) A placebo-controlled trial of constraint-induced movement therapy for upper extremity after stroke. Stroke 37(4): 10451049. Google Scholar CrossRef, Medline
Taub E, Uswatte G, Mark VW, (2013) Method for enhancing real-world use of a more affected arm in chronic stroke: Transfer package of constraint-induced movement therapy. Stroke 44(5): 13831388. Google ScholarCrossRef, Medline
Tomori K, Nagayama H, Saito Y, (2015) Examination of a cut-off score to express the meaningful activity of people with dementia using iPad application (ADOC). Disability and Rehabilitation: Assistive Technology 10(2): 126131. Google Scholar CrossRef, Medline
Tomori K, Saito Y, Nagayama H, (2013) Reliability and validity of individualized satisfaction score in aid for decision-making in occupation choice. Disability and Rehabilitation 35(2): 113117. Google Scholar CrossRef, Medline
Tomori K, Uezu S, Kinjo S, (2012) Utilization of the iPad application: Aid for decision-making in occupation choice. Occupational Therapy International 19(2): 8897. Google Scholar CrossRef, Medline
Uswatte G, Taub E, Morris D, (2005) Reliability and validity of the upper-extremity Motor Activity Log-14 for measuring real-world arm use. Stroke 36(11): 24932496. Google Scholar CrossRef, Medline
Watanabe T, Kinoshita S, Takahashi C (2010) Further investigation of validity of the Paralytic arm Participation Measure (PPM) and its level of difficulty with each item. [Sagyo Ryoho Journal] 44(6): 489494.Google Scholar
Whiting P, Rutjes AW, Reitsma JB, (2003) The development of QUADAS: A tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Medical Research Methodology 3(Suppl 1): 25. Google Scholar CrossRef, Medline

Source: Development of a tool to facilitate real life activity retraining in hand and arm therapy – Mar 28, 2017

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[Abstract+References] Movement Kinematics of the Ipsilesional Upper Extremity in Persons With Moderate or Mild Stroke

Background. An increasing number of studies have indicated that the ipsilesional arm may be impaired after stroke. There is, however, a lack of knowledge whether ipsilesional deficits influence movement performance during purposeful daily tasks.

Objective. The aim of this study was to investigate whether, and to what extent, movement impairments are present while performing an ipsilesional upper extremity task during the first 3 months after stroke.

Methods. Movement kinematics describing movement time, smoothness, velocity, strategy, and pattern were captured during a standardized drinking task in 40 persons with first-ever stroke and 20 controls. Kinematics were measured early and at 3 months poststroke, and sensorimotor impairment was assessed with Fugl-Meyer Assessment in stroke.

Results. Half of the ipsilesional kinematics showed significant deficits early after stroke compared to controls, and the stroke severity had a significant impact on the kinematics. Movements of the ipsilesional arm were slower, less smooth, demonstrated prolonged relative time in deceleration, and increased arm abduction during drinking. Kinematics improved over time and reached a level comparable with controls at 3 months, except for angular velocity of the elbow and deceleration time in reaching for those with more severe motor impairment.

Conclusions. This study demonstrates that movements of the ipsilesional arm, during a purposeful daily task, are impaired after stroke. These deficits are more prominent early after stroke and when the motor impairment is more severe. In clinical studies and praxis, the use of less-affected arm as a reference may underestimate the level of impairment and extent of recovery.

1. Persson HC, Parziali M, Danielsson A, Sunnerhagen KS. Outcome and upper extremity function within 72 hours after first occasion of stroke in an unselected population at a stroke unit. A part of the SALGOT study. BMC Neurol. 2012;12:162. Google Scholar CrossRef, Medline
2. Nakayama H, Jorgensen HS, Raaschou HO, Olsen TS. Recovery of upper extremity function in stroke patients: the Copenhagen Stroke Study. Arch Phys Med Rehabil. 1994;75:394398. Google Scholar CrossRef, Medline
3. Lawrence ES, Coshall C, Dundas R, . Estimates of the prevalence of acute stroke impairments and disability in a multiethnic population. Stroke. 2001;32:12791284. Google Scholar CrossRef, Medline
4. Jorgensen HS, Nakayama H, Raaschou HO, Olsen TS. Stroke. Neurologic and functional recovery the Copenhagen Stroke Study. Phys Med Rehabil Clin N Am. 1999;10:887906. Google Scholar Medline
5. Parker VM, Wade DT, Langton Hewer R. Loss of arm function after stroke: measurement, frequency, and recovery. Int Rehabil Med. 1986;8:6973. Google Scholar CrossRef, Medline
6. Shumway-Cook A, Woollacott MH. Motor Control: Translating Research Into Clinical Practice. 4th ed.Philadelphia, PA: Lippincott Williams & Wilkins; 2012. Google Scholar
7. Morris JH, Van Wijck F. Responses of the less affected arm to bilateral upper limb task training in early rehabilitation after stroke: a randomized controlled trial. Arch Phys Med Rehabil. 2012;93:11291137. Google Scholar CrossRef, Medline
8. Grefkes C, Fink GR. Reorganization of cerebral networks after stroke: new insights from neuroimaging with connectivity approaches. Brain. 2011;134(pt 5):12641276. Google Scholar CrossRef, Medline
9. Grefkes C, Fink GR. Connectivity-based approaches in stroke and recovery of function. Lancet Neurol. 2014;13:206216. Google Scholar CrossRef, Medline
10. Suzuki M, Omori Y, Sugimura S, . Predicting recovery of bilateral upper extremity muscle strength after stroke. J Rehabil Med. 2011;43:935943. Google Scholar CrossRef, Medline
11. Favre I, Zeffiro TA, Detante O, Krainik A, Hommel M, Jaillard A. Upper limb recovery after stroke is associated with ipsilesional primary motor cortical activity: a meta-analysis. Stroke. 2014;45:10771083. Google Scholar CrossRef, Medline
12. Pohl PS, Winstein CJ. Practice effects on the less-affected upper extremity after stroke. Arch Phys Med Rehabil. 1999;80:668675. Google Scholar CrossRef, Medline
13. McCombe Waller S, Whitall J. Fine motor control in adults with and without chronic hemiparesis: baseline comparison to nondisabled adults and effects of bilateral arm training. Arch Phys Med Rehabil. 2004;85:10761083. Google Scholar CrossRef, Medline
14. Sunderland A. Recovery of ipsilateral dexterity after stroke. Stroke. 2000;31:430433. Google Scholar CrossRef, Medline
15. Haaland KY, Delaney HD. Motor deficits after left or right hemisphere damage due to stroke or tumor. Neuropsychologia. 1981;19:1727. Google Scholar CrossRef, Medline
16. Kitsos GH, Hubbard IJ, Kitsos AR, Parsons MW. The ipsilesional upper limb can be affected following stroke. TheScientificWorldJournal. 2013;2013:684860. Google Scholar CrossRef, Medline
17. Metrot J, Froger J, Hauret I, Mottet D, van Dokkum L, Laffont I. Motor recovery of the ipsilesional upper limb in subacute stroke. Arch Phys Med Rehabil. 2013;94:22832290. Google Scholar CrossRef, Medline
18. Jones RD, Donaldson IM, Parkin PJ. Impairment and recovery of ipsilateral sensory-motor function following unilateral cerebral infarction. Brain. 1989;112(pt 1):113132. Google Scholar CrossRef, Medline
19. Desrosiers J, Bourbonnais D, Bravo G, Roy PM, Guay M. Performance of the “unaffected” upper extremity of elderly stroke patients. Stroke. 1996;27:15641570. Google Scholar CrossRef, Medline
20. Sunderland A, Bowers MP, Sluman SM, Wilcock DJ, Ardron ME. Impaired dexterity of the ipsilateral hand after stroke and the relationship to cognitive deficit. Stroke. 1999;30:949955. Google Scholar CrossRef, Medline
21. Wetter S, Poole JL, Haaland KY. Functional implications of ipsilesional motor deficits after unilateral stroke. Arch Phys Med Rehabil. 2005;86:776781. Google Scholar CrossRef, Medline
22. Noskin O, Krakauer JW, Lazar RM, . Ipsilateral motor dysfunction from unilateral stroke: implications for the functional neuroanatomy of hemiparesis. J Neurol Neurosurg Psychiatry. 2008;79:401406. Google Scholar CrossRef, Medline
23. Alt Murphy M, Häger CK. Kinematic analysis of the upper extremity after stroke—how far have we reached and what have we grasped? Phys Ther Rev. 2015;20:137155. Google Scholar CrossRef
24. Alt Murphy M, Willen C, Sunnerhagen KS. Kinematic variables quantifying upper-extremity performance after stroke during reaching and drinking from a glass. Neurorehabil Neural Repair. 2011;25:7180. Google Scholar Link
25. van Dokkum L, Hauret I, Mottet D, Froger J, Metrot J, Laffont I. The contribution of kinematics in the assessment of upper limb motor recovery early after stroke. Neurorehabil Neural Repair. 2014;28:412. Google Scholar Link
26. Buma F, Kwakkel G, Ramsey N. Understanding upper limb recovery after stroke. Restor Neurol Neurosci. 2013;31:707722. Google Scholar Medline
27. Kitago T, Liang J, Huang VS, . Improvement after constraint-induced movement therapy: recovery of normal motor control or task-specific compensation? Neurorehabil Neural Repair. 2013;27:99109. Google Scholar Link
28. van Vliet PM, Sheridan MR. Coordination between reaching and grasping in patients with hemiparesis and healthy subjects. Arch Phys Med Rehabil. 2007;88:13251331. Google Scholar CrossRef, Medline
29. Aprile I, Rabuffetti M, Padua L, Di Sipio E, Simbolotti C, Ferrarin M. Kinematic analysis of the upper limb motor strategies in stroke patients as a tool towards advanced neurorehabilitation strategies: a preliminary study. BioMed Res Int. 2014;2014:636123. Google Scholar CrossRef, Medline
30. Nakamura T, Abreu BC, Patterson RM, Buford WLJr, Ottenbacher KJ. Upper-limb kinematics of the presumed-to-be-unaffected side after brain injury. Am J Occup Ther. 2008;62:4650. Google Scholar CrossRef, Medline
31. Ketcham CJ, Rodriguez TM, Zihlman KA. Targeted aiming movements are compromised in nonaffected limb of persons with stroke. Neurorehabil Neural Repair. 2007;21:388397. Google Scholar Link
32. Schaefer SY, Haaland KY, Sainburg RL. Hemispheric specialization and functional impact of ipsilesional deficits in movement coordination and accuracy. Neuropsychologia. 2009;47:29532966. Google ScholarCrossRef, Medline
33. Nowak DA, Grefkes C, Dafotakis M, Kust J, Karbe H, Fink GR. Dexterity is impaired at both hands following unilateral subcortical middle cerebral artery stroke. Eur J Neurosci. 2007;25:31733184. Google Scholar CrossRef, Medline
34. Jeannerod M, Paulignan Y, Weiss P. Grasping an object: one movement, several components. Novartis Found Symp. 1998;218:516. Google Scholar Medline
35. Wu C, Trombly CA, Lin K, Tickle-Degnen L. Effects of object affordances on reaching performance in persons with and without cerebrovascular accident. Am J Occup Ther. 1998;52:447456. Google ScholarCrossRef, Medline
36. Alt Murphy M, Persson HC, Danielsson A, Broeren J, Lundgren-Nilsson A, Sunnerhagen KS. SALGOT—Stroke Arm Longitudinal study at the University of Gothenburg, prospective cohort study protocol. BMC Neurol. 2011;11:56. Google Scholar CrossRef, Medline
37. Alt Murphy M, Sunnerhagen KS, Johnels B, Willen C. Three-dimensional kinematic motion analysis of a daily activity drinking from a glass: a pilot study. J Neuroeng Rehabil. 2006;3:18. Google ScholarCrossRef, Medline
38. Alt Murphy M, Willen C, Sunnerhagen KS. Movement kinematics during a drinking task are associated with the activity capacity level after stroke. Neurorehabil Neural Repair. 2012;26:11061115. Google Scholar Link
39. Alt Murphy M, Willen C, Sunnerhagen KS. Responsiveness of upper extremity kinematic measures and clinical improvement during the first three months after stroke. Neurorehabil Neural Repair. 2013;27:844853. Google Scholar Link
40. Patterson TS, Bishop MD, McGuirk TE, Sethi A, Richards LG. Reliability of upper extremity kinematics while performing different tasks in individuals with stroke. J Mot Behav. 2011;43:121130. Google ScholarCrossRef, Medline
41. Platz T, Prass K, Denzler P, Bock S, Mauritz KH. Testing a motor performance series and a kinematic motion analysis as measures of performance in high-functioning stroke patients: reliability, validity, and responsiveness to therapeutic intervention. Arch Phys Med Rehabil. 1999;80:270277. Google Scholar CrossRef, Medline
42. Subramanian SK, Yamanaka J, Chilingaryan G, Levin MF. Validity of movement pattern kinematics as measures of arm motor impairment poststroke. Stroke. 2010;41:23032308. Google Scholar CrossRef, Medline
43. Nijenhuis SM, Prange GB, Stienen AHA, Buurke JH, Rietman JS. Direct effect of a dynamic wrist and hand orthosis on reach and grasp kinematics in chronic stroke. Paper presented at: IEEE International Conference on Rehabilitation Robotics; Singapore; August 11-14, 2015: 404409.
44. Kamper DG, McKenna-Cole AN, Kahn LE, Reinkensmeyer DJ. Alterations in reaching after stroke and their relation to movement direction and impairment severity. Arch Phys Med Rehabil. 2002;83:702707. Google Scholar CrossRef, Medline
45. Fugl-Meyer AR, Jaasko L, Leyman I, Olsson S, Steglind S. The post-stroke hemiplegic patient. 1. A method for evaluation of physical performance. Scand J Rehabil Med. 1975;7:1331. Google Scholar Medline
46. Fugl-Meyer AR. Post-stroke hemiplegia assessment of physical properties. Scand J Rehabil Med. 1980;2(7):8593. Google Scholar
47. Duncan PW, Propst M, Nelson SG. Reliability of the Fugl-Meyer assessment of sensorimotor recovery following cerebrovascular accident. Phys Ther. 1983;63:16061610. Google Scholar CrossRef, Medline
48. Persson HC, Alt Murphy M, Danielsson A, Lundgren-Nilsson A, Sunnerhagen KS. A cohort study investigating a simple, early assessment to predict upper extremity function after stroke—a part of the SALGOT study. BMC Neurol. 2015;15:92. Google Scholar CrossRef, Medline
49. Bohannon RW, Smith MB. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther. 1987;67:206207. Google Scholar CrossRef, Medline
50. Adams HPJr, Bendixen BH, Kappelle LJ, . Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke. 1993;24:3541. Google Scholar CrossRef, Medline
51. Bamford J, Sandercock P, Dennis M, Burn J, Warlow C. Classification and natural history of clinically identifiable subtypes of cerebral infarction. Lancet. 1991;337:15211526. Google Scholar CrossRef, Medline
52. Pallant J. SPSS Survival Manual: A Step by Step Guide to Data Analysis Using SPSS for Windows (Version 15). Buckingham, England: Open University Press; 2007. Google Scholar
53. Kwakkel G, Kollen B, Lindeman E. Understanding the pattern of functional recovery after stroke: facts and theories. Restor Neurol Neurosci. 2004;22:281299. Google Scholar Medline
54. Buma FE, van Kordelaar J, Raemaekers M, van Wegen EE, Ramsey NF, Kwakkel G. Brain activation is related to smoothness of upper limb movements after stroke. Exp Brain Res. 2016;234:20772089. Google Scholar CrossRef, Medline
55. Sainburg RL, Duff SV. Does motor lateralization have implications for stroke rehabilitation? J Rehabil Res Dev. 2006;43:311322. Google Scholar CrossRef, Medline
56. Pohl PS, Luchies CW, Stoker-Yates J, Duncan PW. Upper extremity control in adults post stroke with mild residual impairment. Neurorehabil Neural Repair. 2000;14:3341. Google Scholar Link
57. Schaefer SY, Haaland KY, Sainburg RL. Ipsilesional motor deficits following stroke reflect hemispheric specializations for movement control. Brain. 2007;130(pt 8):21462158. Google Scholar CrossRef, Medline
58. Mani S, Mutha PK, Przybyla A, Haaland KY, Good DC, Sainburg RL. Contralesional motor deficits after unilateral stroke reflect hemisphere-specific control mechanisms. Brain. 2013;136(pt 4):12881303. Google Scholar CrossRef, Medline
59. McCrea PH, Eng JJ, Hodgson AJ. Biomechanics of reaching: clinical implications for individuals with acquired brain injury. Disabil Rehabil. 2002;24:534541. Google Scholar CrossRef, Medline

Source: Movement Kinematics of the Ipsilesional Upper Extremity in Persons With Moderate or Mild Stroke – Jan 20, 2017

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[WEB SITE] Paralyzed Man Regains Hand Movement, Thanks to First-Ever Nerve-Transfer Surgery


Beginning with a twitch in his fingers about six months ago, a Canadian man has successfully re-animated his paralyzed hand after undergoing a nerve transfer surgery.


Tim Raglin regularly dove, headfirst, into the water at his family’s lake house. The 45-year old Canadian man had done so thousands of times without incident. In 2007, though Raglin hit his head on a rock in the shallow water, shattering a vertebra in his cervical spine.

His family pulled him to safety, saving him from drowning. However, for nine years, both his hands and feet were left paralyzed.

Now though, there’s hope for Raglin and others like him.

Raglin is the first Canadian to ever undergo a nerve transfer surgery. Dr. Kirsty Boyd from the Ottawa Hospital essentially rewired Raglin’s body– rerouting some of his fully-functional elbow nerves to his hand. Although Raglin had to wait several months for the nerves to regrow, this procedure allowed him to regain some control over his right hand.

Raglin can now unfold his fingers from the palm of his right hand and grip onto items such as a fork, a shaver and a toothbrush.
Ottawa Citizen


After persevering for 18 months, Raglin was finally able to open his fingers during an occupational therapy session at The Ottawa Hospital Rehabilitation Centre.

“It was kind of a shock,” he said in an interview. “And it’s really moving now: There’s a lot of nerves touching muscles that are getting stronger…Every iteration, it just gets more and more exciting.”

It’s still a slow uphill battle for Raglin. The muscles in his hand have deteriorated from lack of use, so they tire easily. In addition, because Raglin is using a different nerve pathway to activate the muscles in his hand, it will take some time for his brain to adjust to the new system.

Despite these challenges, he has learned to close his fingers on something by flexing his bicep. In time, however, it’s expected his brain will figure out how to separate the triggers for his hand and his bicep.

“I’m not quite at the point where I can get a cup off the table, but I can envision myself doing that. I know I will be able to do that eventually—so it’s exciting to see that.”

Source: Paralyzed Man Regains Hand Movement, Thanks to First-Ever Nerve-Transfer Surgery

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[Abstract] TMS measures of motor cortex function after stroke: A meta-analysis


    The neurophysiological effects of stroke are localised to the affected motor cortex.There is no clear evidence of imbalanced interhemispheric inhibition after stroke.Facilitating the affected motor cortex may be most beneficial in selected patients.



Transcranial magnetic stimulation (TMS) is commonly used to measure the effects of stroke on corticomotor excitability, intracortical function, and interhemispheric interactions. The interhemispheric inhibition model posits that recovery of motor function after stroke is linked to rebalancing of asymmetric interhemispheric inhibition and corticomotor excitability. This model forms the rationale for using neuromodulation techniques to suppress unaffected motor cortex excitability, and facilitate affected motor cortex excitability. However, the evidence base for using neuromodulation techniques to promote post-stroke motor recovery is inconclusive.


The aim of this meta-analysis was to compare measures of corticomotor excitability, intracortical function, and interhemispheric inhibition, between the affected and unaffected hemispheres of people with stroke, and measures made in healthy adults.


A literature search was conducted to identify studies that made TMS measures of the motor cortex in adult stroke patients. Two authors independently extracted data, and the quality of included studies was assessed. TMS measures were compared between the affected and unaffected hemispheres of stroke patients, between the affected hemisphere and healthy controls, and between the unaffected hemisphere and healthy controls. Analyses were carried out with data grouped according to the muscle from which responses were recorded, and separately according to time post-stroke (<3 months, and ≥6 months). Meta-analyses were carried out using a random effects model.


There were 844 studies identified, and 112 studies included in the meta-analysis. Results were very similar across muscle groups. Affected hemisphere M1 excitability is lower than unaffected and healthy control M1 excitability after stroke. Affected hemisphere short interval intracortical inhibition (SICI) is lower than unaffected and healthy control SICI early after stroke, and not different in the chronic phase. There were no differences detected between the unaffected hemisphere and healthy controls. There were only seven studies of interhemispheric inhibition that could be included, with no clear effects of hemisphere or time post-stroke.


The neurophysiological effects of stroke are primarily localised to the affected hemisphere, and there is no clear evidence for hyper-excitability of the unaffected hemisphere or imbalanced interhemispheric inhibition. This indicates that facilitating affected M1 excitability directly may be more beneficial than suppressing unaffected M1 excitability for promoting post-stroke recovery.

Source: TMS measures of motor cortex function after stroke: A meta-analysis

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