Archive for category Paretic Hand

[Abstract + References] Improving wrist imaging through a multicentre educational intervention: The challenge of orthogonal projections

In relation to wrist imaging, the accepted requirement is two orthogonal projections obtained at 90°, each with the wrist in neutral position. However, the literature and anecdotal experience suggests that this principle is not universally applied.

This multiphase study was undertaken across eight different hospitals sites. Compliance with standard UK technique was confirmed if there was a change in ulna orientation between the dorsi-palmar (DP) and lateral wrist projections. A baseline evaluation for three days was randomly identified from the preceding three months. An educational intervention was implemented using a poster to demonstrate standard positioning. To measure the impact of the intervention, further evaluation took place at two weeks (early) and three months (late).

Across the study phases, only a minority of radiographs demonstrated compliance with the standard technique, with an identical anatomical appearance of the distal ulna across the projections. Initial compliance was 16.8% (n = 40/238), and this improved to 47.8% (n = 77/161) post-intervention, but declined to 32.8% (n = 41/125) within three months. The presence of pathology appeared to influence practice, with a greater proportion of those with an abnormal radiographic examination demonstrating a change in ulna appearances in the baseline cohort (p < 0.001) and the late post-intervention group (p = 0.002) but not in the examinations performed two weeks after staff education (p = 0.239).

Assessment of image quality is critical for diagnosis and treatment monitoring. Yet poor compliance with standard anatomical principles was evident. A simple educational intervention resulted in a transient improvement in wrist positioning, but the impact was not sustained over time.

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13. Shin, S-H, Lee, Y-S, Kang, J-W, et alWhere is the ulnar styloid process? Identification of the absolute location of the ulnar styloid process based on CT and verification of neutral forearm rotation on lateral radiographs of the wrist. Clin Orthop Surg 2018; 10: 8088.
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26. Buck, FM, Nico, MAC, Gheno, R, et alMorphology of the distal radioulnar joint: cadaveric study with MRI and MR arthrography with the forearm in neutral position, pronation, and supination. Am J Roentgenol 2010; 194: W202W207.
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27. Bernstein, DT, Linnell, JD, Peterson, NJ, et alCorrelation of the lateral wrist radiograph to ulnar variance: a cadaveric study. J Hand Surg Am 2018; 43: 951.e1e9.
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35. Calabrese, I, Fuller, M, Chau, M, et alA pilot study to examine the effect of an educational poster on the knowledge and practices of lateral elbow radiograph repositioning in radiographers. J Med Imag Radiat Sci. 2020; 51: 68–74. DOI:
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via Improving wrist imaging through a multicentre educational intervention: The challenge of orthogonal projections – Beverly Snaith, Scott Raine, Lynsey Fowler, Christopher Osborne, Sophie House, Ryan Holmes, Emma Tattersall, Emma Pierce, Melanie Dobson, James W Harcus,

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[Abstract + Referrences] Developing Technique for Arm Movement Rehabilitation of Post Stroke Patient – Proceedings


There are numerous studies and efforts to improve rehabilitation programs for stroke sufferers. Mostly, the sufferers are usually suffered from temporary or permanent paralysis. This leads to rehabilitation as a recommended program to implement so that the sufferers could return to a near-to-normal and independent life. Traditionally, rehabilitation to a certain paralyzed body part, i.e. arms, uses periodic and routine therapy. It is intended to make it pliable doing joint muscle coordination movements. Therefore, this study examines and develops progressive movements to optimize the therapy result. An economical movement principle in assembling systems that is Therbligh motion is applied to the therapy of arm stroke patient movements. The principle of this movement will be compared with the traditional motion therapy used by physiotherapists. From kinematics and biomechanics analysis, it can be known which parts of the joints and muscles which play a role in the movement and how much burden occurs on the muscles or joints. The results of measurements of muscles strength with EMG to both principles of the movement of therapy for arm stroke patients, it was found that the principle of Therbligh movement produced greater muscle strength. Muscles strength is measured in position passive and active muscles.


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via Developing Technique for Arm Movement Rehabilitation of Post Stroke Patient | Proceedings of the 2020 10th International Conference on Biomedical Engineering and Technology

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[Abstract + References] An intention-based online bilateral training system for upper limb motor rehabilitation


Bilateral rehabilitation training robotic systems have potential to promote the upper limb motor recovery of post-stroke hemiparesis patients through providing the synchronization motion between the impaired limb and contralateral limb. The active rehabilitation training based on patients’ intention can also promote the recovery effect by stimulating the activity of the ipsilateral hemisphere and contralateral hemisphere. In this paper, a novel intention-based bilateral training system using biomedical signals which represents the muscle activity information and active motion intention was proposed to promote the rehabilitation training effect. The proposed system can provide the synchronization motion to the impaired limb by the exoskeleton device according to the sEMG signals from the contralateral intact limb. A BPNN model using a novel multi-features input vector was employed for establishing the relationship between the sEMG signals and the motion intention. To verify the intention prediction performance, the comparison experiments involving both the offline phase and online phase were carried out using three different kinds of feature input vectors of sEMG. Furthermore, the real-time bilateral control experiments were conducted to verify the feasibility and effectiveness of the proposed bilateral rehabilitation system, in terms of motion synchronization tracking and the real-time characteristics.

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[ARTICLE] The Promotoer, a brain-computer interface-assisted intervention to promote upper limb functional motor recovery after stroke: a study protocol for a randomized controlled trial to test early and long-term efficacy and to identify determinants of response – Full Text



Stroke is a leading cause of long-term disability. Cost-effective post-stroke rehabilitation programs for upper limb are critically needed. Brain-Computer Interfaces (BCIs) which enable the modulation of Electroencephalography (EEG) sensorimotor rhythms are promising tools to promote post-stroke recovery of upper limb motor function. The “Promotoer” study intends to boost the application of the EEG-based BCIs in clinical practice providing evidence for a short/long-term efficacy in enhancing post-stroke hand functional motor recovery and quantifiable indices of the participants response to a BCI-based intervention. To these aims, a longitudinal study will be performed in which subacute stroke participants will undergo a hand motor imagery (MI) training assisted by the Promotoer system, an EEG-based BCI system fully compliant with rehabilitation requirements.


This longitudinal 2-arm randomized controlled superiority trial will include 48 first ever, unilateral, subacute stroke participants, randomly assigned to 2 intervention groups: the BCI-assisted hand MI training and a hand MI training not supported by BCI. Both interventions are delivered (3 weekly session; 6 weeks) as add-on regimen to standard intensive rehabilitation. A multidimensional assessment will be performed at: randomization/pre-intervention, 48 h post-intervention, and at 1, 3 and 6 month/s after end of intervention. Primary outcome measure is the Fugl-Meyer Assessment (FMA, upper extremity) at 48 h post-intervention. Secondary outcome measures include: the upper extremity FMA at follow-up, the Modified Ashworth Scale, the Numeric Rating Scale for pain, the Action Research Arm Test, the National Institute of Health Stroke Scale, the Manual Muscle Test, all collected at the different timepoints as well as neurophysiological and neuroimaging measures.


We expect the BCI-based rewarding of hand MI practice to promote long-lasting retention of the early induced improvement in hand motor outcome and also, this clinical improvement to be sustained by a long-lasting neuroplasticity changes harnessed by the BCI-based intervention. Furthermore, the longitudinal multidimensional assessment will address the selection of those stroke participants who best benefit of a BCI-assisted therapy, consistently advancing the transfer of BCIs to a best clinical practice.

Trial registration

Name of registry: BCI-assisted MI Intervention in Subacute Stroke (Promotoer).

Trial registration number: NCT04353297; registration date on the platform: April, 15/2020.

Peer Review reports


Stroke is a major public health and social care concern worldwide [1]. The upper limb motor impairment commonly persists after stroke, and it represents the major contribution to long-term disability [2]. It has been estimated that the main clinical predictor of whether a patient would come back to work is the degree of upper extremity function [3]. Despite the intensive rehabilitation, the variability in the nature and extent of upper limb recovery remains a crucial factor affecting rehabilitation outcomes [4].

Electroencephalography (EEG)-based Brain-Computer Interface (BCI) is an emerging technology that enables a direct translation of brain activity into motor action [5]. Recently, EEG-based BCIs have been recognized as potential tools to promote functional motor recovery of upper limbs after stroke (for review see [6]). Several randomized controlled trials have shown that stroke patients can learn to modulate their EEG sensorimotor rhythms [7] to control external devices and this practice might facilitate neurological recovery both in subacute and chronic stroke phase [8,9,10].

We were previously successful in the design and validation of an EEG sensorimotor rhythms–based BCI combined with realistic visual feedback of upper limb to support hand motor imagery (MI) practice in stroke patients [1112]. Our previous pilot randomized controlled study [8] with the participation of 28 subacute stroke patients with severe motor deficit, suggested that 1 month BCI-assisted MI practice as an add-on intervention to the usual rehabilitation care was superior with respect to the add-on, 1 month MI training alone (ie., without BCI support) in improving hand functional motor outcomes (indicated by the significantly higher mean score at upper extremity Fugl-Meyer scale in the BCI with respect to control group). A greater involvement of the ipsilesional hemisphere, as reflected by a stronger motor-related EEG oscillatory activity and connectivity in response to MI of the paralyzed trained hand was also observed only in the BCI-assisted MI training condition. These promising findings corroborated the idea that a relatively low-cost technique (i.e. EEG-based BCI) can be exploited to deliver an efficacious rehabilitative intervention such as MI training and prompted us to undertake a translational effort by implementing an all-in-one BCI-supported MI training station– the Promotoer [13].

Yet, important questions remain to be addressed in order to improve the clinical viability of BCIs such as defining whether the expected early improvements in functional motor outcomes induced by the BCI-assisted MI training in subacute stroke [8] can be sustained in a long-term as it has been shown for other BCI-based approaches in chronic stroke patients [1014]. This requires advancements in the knowledge on brain functional re-organization early after stroke and on how this re-organization would correlate with the functional motor outcome (evidence-base medicine). Last but not least, the definition of the determinants of the patients response to treatment is paramount to optimize the process of personalized medicine in rehabilitation. We will address these questions by carrying out a randomized trial to eventually establish the fundamentals for a cost-effective use of EEG-based BCI technology to deliver a rehabilitative intervention such as the MI in hospitalized stroke patients.

Aim and hypotheses

The “Promotoer” study is a randomized controlled trial (RCT) designed to provide evidence for a significant early improvement of hand motor function induced by the BCI-assisted MI training operated via the Promotoer and for a persistency (up to 6 months) of such improvement. Task-specific training was reported to induce long-term improvements in arm motor function after stroke [15,16,17]. Thus, our hypothesis is that the BCI-based rewarding of hand MI tasks would promote long-lasting retention of early induced positive effect on motor performance with respect to MI tasks practiced in an open loop condition (ie, without BCI). Accordingly, the primary aim of the “Promotoer” RCT will be first to determine whether the BCI based intervention (MI-BCI) administered by means of a BCI system fully compatible with a clinical setting (the Promotoer), is superior to a non-BCI assisted MI training (MI Control) in improving hand motor function outcomes in sub-acute stroke patients admitted to the hospital for their standard rehabilitation care; secondly, we will test whether the efficacy of BCI-based intervention on hand motor function outcomes is sustained long-term after the end of intervention (6 months follow-up). A further hypothesis is that such clinical improvement would be sustained by a long-lasting neuroplasticity changes as harnessed by the BCI–based intervention. This hypothesis rises from current evidence for an early enhancement of post-stroke plastic changes enabled by BCI-based trainings [8,9,10]. To test this hypothesis, a longitudinal assessment of the brain network organization derived from advanced EEG signal processing (secondary objective) will be performed.

The heterogeneity of stroke makes prediction of treatment responders a great challenge [18]. The potential value of a combination of neurophysiological and neuroimaging biomarkers with the clinical assessment in predicting post-stroke motor recovery has been recently highlighted [19]. Our hypothesis is that the longitudinal combined functional, neurophysiological and neuroimaging assessment over 6 months from the intervention will allow for insights into biomarkers and potential predictors of patients response to the BCI-Promotoer training (secondary aim). To this purpose, well-recognized factors contributing to recovery after stroke such as the relation between clinical profile, lesion characteristics and patterns of post-stroke motor cortical re-organization (eg., ipsilesional/contralesional primary and non-primary motor areas, cortico-spinal tract integrity, severity of motor deficits at baseline; for review see [19]) will be taken into account.[…}


The Promotoer system. The Promoter is equipped with a computer, a commercial wireless EEG/EMG system (g.MOBIlab, g.tec medical engineering GmbH Austria), a screen for the therapist feedback (for the electroencephalographic – EEG activity and electromyographic- EMG activity monitoring) and screen for the ecological feedback to the participant; this ecological feedback is delivered by means of a custom software program that provides for (personalized) visual representation of the participant’s own hands. As such, this software allows the therapists to create an artificial reproduction of a given participant’s hand and forearm by adjusting a digitally created image in shape, size, skin color and orientation to match as much as possible the real hand and arm of the participant. Real-time feedback is provided by means of BCI2000 software [40]. The degree of EEG desynchronization over selected electrodes within selected frequencies (BCI control features) determines the vertical velocity of the cursor on the therapist’s screen and it operates the “virtual” hand software accordingly. The image is original as it is owned by the authors

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[Case Report] Use of a myoelectric upper limb orthosis for rehabilitation of the upper limb in traumatic brain injury – Full Text



Upper limb motor deficits following traumatic brain injury are prevalent and effective therapies are needed. The purpose of this case report was to illustrate response to a novel therapy using a myoelectric orthosis in a person with TBI.

Case description: A 42-year-old female, 29.5 years post-traumatic brain injury with diminished motor control/coordination, and learned nonuse of the right arm. She also had cognitive deficits and did not spontaneously use her right arm functionally.


Study included three phases: baseline data collection/device fabrication (five weeks); in-clinic training (2×/week for nine weeks); and home-use phase (nine weeks). The orthosis was incorporated into motor learning-based therapy.

Outcomes: During in-clinic training, active range of motion, tone, muscle power, Fugl-Meyer, box and blocks test, and Chedoke assessment score improved. During the home-use phase, decrease in tone was maintained and all other outcomes declined but were still better upon study completion than baseline. The participant trained with the orthosis 70.12 h, logging over 13,000 repetitions of elbow flexion/extension and hand open/close.


Despite long-standing traumatic brain injury, meaningful improvements in motor function were observed and were likely the results of high repetition practice of functional movement delivered over a long duration. Further assessment in a larger cohort is warranted.


Traumatic brain injury (TBI) affects 1.7 million people in the general US population annually1 and is one of the most common neurologic disorders causing disability.2 Motor deficits are present in 30% of TBI survivors with arm and hand problems occurring in about 17%,3 limiting the ability to perform activities of daily living (ADL). However, there is less research on motor recovery in patients with TBI compared with other neurologic diseases involving the brain, such as stroke.2

Activity-based interventions hope to maximize rehabilitation outcomes and enhance adaptive neural plasticity;3 however, optimal doses and schedules of training have not been adequately established. Repetition is one parameter important for activity-dependent neural plasticity. Studies assessing US rehabilitation found that stroke and TBI survivors receive an average of 32–50 repetitions of upper extremity active and passive movement per therapy session, significantly less than the 400–600 repetitions achieved in animal studies.3 Although persons with TBI benefit from traditional therapy,4 it is clear that more is needed to attain full recovery, especially with severely affected individuals.

Consistent with this idea, Krebs and Volpe5 argued that the basis of all assistive and therapeutic devices should be to induce the intent to move followed by that movement actually happening, referred to as “intent-driven rehabilitation”. One way this can be accomplished is through myoelectric control wherein a weak electromyography (EMG) signal from the muscle of an impaired limb is detected, processed, and used to activate a motor within the orthosis. The motor then assists the user in producing the desired movement. The patient-directed “intentional” action of the device promotes patient engagement as the orthosis will only reward the patient with movement when they use the correct muscles to complete a task. Previous studies of myoelectric driven lab-based robotic interventions6 showed improved Fugl-Meyer motor control scores of the upper extremity7 and reduced spasticity as assessed by the modified Ashworth scale (MAS).8 While demonstrating a benefit of “intent-driven rehabilitation”, in-lab robotic intervention restricted the amount of practice because training was restricted to the short lab sessions only and no home practice was possible.6

While myolectrically-driven orthotic technology has been in development for many years,911 recent advances have made it more accessible and clinically deployable for rehabilitation. However, initial research has focused on persons with stroke1218 and not TBI. The ability of severely hemiplegic stroke survivors to activate a powered elbow orthosis using myoelectric control has been reported,13 along with increased elbow range of motion with orthosis use.18 Kim et al.15 reported that after a combined period of training and at home-use of an elbow-only myoelectric orthosis, a statistically significant three-point change in Fugl-Meyer motor control score was found in the upper extremity of nine persons post-stroke. We have recently reported a case series of chronic stroke survivors who used a myoelectric upper limb orthosis over a period of several months and achieved a 9.0 ± 4.8 point improvement in Fugl-Meyer.19 Since upper limb motor deficits in TBI are a problem that can lead to decreased independence in ADLs and given that there is a lack of effective therapies and supportive devices for upper limb impairment, the purpose of this case report was to illustrate the response to therapy combined with a myoelectric elbow–wrist–hand orthosis in a person with longstanding TBI.

Case description

The protocol described in this case report complies with standards of the Declaration of Helsinki and was approved by the Institutional Review Boards of participating institutions (IRB #16039-H29 and STU00203728) and met the Health Insurance Portability and Accountability Act (HIPAA) requirements for disclosure of protected health information. Written informed consent for participation was obtained from the patient’s legal guardian.

The participant was a 42-year-old female who sustained a TBI from being struck by a motor vehicle at age 12. At study entry, she was 29.5 years post injury, dependent on caregivers for most ADL/instrumental activities of daily living (IADLs), used a manual wheelchair for mobility, resided in a group home setting, and required assistance from caregivers to help her make decisions. She attended an adult workshop where she would perform general fitness/mobility activities along with interacting with peers socially, and had done so for several years. As a result of her injury, she had abnormal tone, weakness and dysmetria/ataxia leading to decreased motor control and coordination of the right upper limb. She has avoided using her right (dominant) arm, which has led to learned nonuse of the right arm and overuse of the left arm. Furthermore, she had cognitive, short-term memory, and perceptual deficits. Right visual processing deficits made it difficult for her to read and distinguish color. Her mini mental state exam (MMSE) score at baseline was 15 out of 30. Due to these impairments, she did not spontaneously use her right upper limb functionally. Over the years since her injury, interventions including traditional physical and occupational therapy (functional mobility training, upper limb task practice, aquatic therapy provided by licensed therapists) have been implemented with limited success to increase the use of her right upper limb.


The participant underwent casting and a myoelectric elbow–wrist–hand orthosis (MyoPro Motion-G, Myomo Inc., Cambridge, MA) was custom fabricated by a certified and licensed orthotist. The orthosis is intended to help individuals with a weakened or paralyzed arm to complete patient-initiated movements and enhance function (Figure 1).

Figure 1. Functional task practice example. (a) Myoelectric elbow–wrist–hand orthosis custom fabricated to fit the participant using MyoPro Motion G components (Myomo Inc.). When the user tries to move the elbow or grasp objects, sensors in the orthosis detect the myoelectric signal generated by the user’s volitional effort, to activate the motor and move the elbow/hand in the desired direction, assisting the user to complete the desired movement. (b) Functional task practice without the orthosis donned to reinforce training. (c) Demonstration of return of functional use showing the participant spontaneously using her impaired limb to feed her pet treats.


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[Abstract] Assistive and Rehabilitation Robotics for Upper Limb Impairments in Post-Stroke Patients: Evaluation Criteria for the Design and Functionality


Rehabilitation and assistive robotics are beneficial for chronic and subacute stroke patients with upper limb impairments. Rehabilitation robotics is the use of robotic machinery and devices during therapy sessions to motivate and optimize the patient’s upper limb motor functions. While assistive robotics is the use of portable robotic devices, which can assist the post stroke user with their upper limb movements along their daily tasks. Assistive robotic devices may also allow patients to “in-directly” improve their motor functions through encouraging them to utilize their affected limb on daily basis. Thus, an assistive device is seen to be essential complementary to a rehabilitation device. Before marketing these two types of devices, they should undergo evaluation studies and clinical trials. This process will not only ensure patient’s safety and optimal outcomes, but also help to overcome challenges in promoting the final product. The aim of this short article is to provide a brief review of current rehabilitation and assistive robotics, highlighting how they are complementary to each other, and how they can be evaluated and improved.


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[Abstract] Methodology for the Design of Rehabilitation Robots: Application in an Exoskeleton for Upper Limb Rehabilitation – Full Text PDF


This article presents a methodology for the design of rehabilitation devices that considers factors involved in a clinical environment. This methodology integrates different disciplines that work together. The methodology is composed by 3 phases and 13 stages with specific tasks, the first phase includes the clinical context considering the requirements of the patient and therapist during the rehabilitation, the second phase is focused in engineering based on the philosophy of digital twin, and in the third phase is evaluated the device. This article explains the characteristics of the methodology and how it was applied in the design of an exoskeleton for passive rehabilitation of the upper limb.

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In a program we developed called “Let’s keep wiping to draw pictures!”, projected graphic images change according to rehabilitation movements for upper limbs, and the levels of exercise amount and quality of movement achieved by patients are reflected in the outcome of the artwork as feedback. At a rehabilitation hospital, inpatients who used the program to perform rehabilitation exercises showed higher levels of satisfaction and expectation in the exercises, and performed simple and repetitive movements more willingly. The program can expect to maintain motivation towards rehabilitation.

Keywords: healthcare design, interaction design, design practice, rehabilitation

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[BLOG POST] Hand Rehab after Stroke: The Top 5 Evidenced-Based Methods

You’ve probably heard a lot of recommendations on how to recover hand function after stroke. We sifted through the research for you to explain the top 5 medically proven methods for hand rehabilitation, why they work, and who they work for.


Hand Rehab after Stroke: The Top 5 Evidenced-Based Methods

After a stroke, it’s challenging enough to navigate the medical system to find what services you need, let alone the right treatment approach for you.

You’ve probably heard a lot of recommendations on how to recover hand function after stroke, and everyone seems to give different advice. That’s why we sifted through the research for you. We’ll explain the top 5 evidence-based methods for hand rehabilitation, why they work, and who they work for.

The top 5 evidence-based treatments for improving hand function after stroke:

  1. Constraint‐induced movement therapy (CIMT)
  2. Mental practice
  3. Mirror therapy
  4. Virtual reality
  5. High dose repetitive task practice

Constraint-Induced Movement Therapy

Unaffected arm wearing oven mitt for at-home constraint therapy.
You can restrict your unaffected side at home by wearing an oven mitt or placing it inside your pants or sweatshirt pocket. This will help remind you to rely on your affected side when completing therapy tasks.

What it is:

Constraint-Induced Movement Therapy (CIMT) is a neuro-rehabilitation method where the non-affected hand is constrained or restricted in order to force the brain to use the affected hand, thereby increasing neuroplasticity.

There are two key components: constraint and shaping.

Constraint refers to the way in which the hand is restricted. Therapists have used casts, splints, and mitts to restrict the use of the non-affected hand. None of them have been shown to be more effective than the other.

Shaping involves repetitive movements or activities at the patient’s ability level which become progressively harder. Therapists use shaping techniques to avoid overwhelming the motor system.

Why it works:

Our brain automatically completes a task in the easiest way possible. Our brain is more interested in completing a task than in how it is accomplished.

After a stroke, it’s easier for our brain to do tasks one-handed. This leads to “learned non-use”.

When we constrain our non-affected hand, suddenly our stronger hand becomes the weaker, less functional hand and we’re forced to use our affected hand. Our affected hand might not have much movement, but to our brain any movement is better than no movement, and the brain is highly motivated to figure out how to accomplish a task.

This is where the “shaping” piece is so important. If you are presented with rehab tasks that overwhelm the motor system or are higher level than your affected hand can functionally do, you’ll be more likely to knock the table over than to participate in picking up pennies from the table.

If you knock the table over with your affected hand, your occupational therapist might actually be excited about it; but in practical life finding that balance of not being too easy and not being so hard that you give up is an important lesson for every human being, not just those after stroke.

Who it’s for:

This approach is used for people who have at least 10 degrees of active wrist and finger extension, as well as 10 degrees of thumb abduction (the ability of the thumb to move out of the palm).

It’s been shown to be effective even years after stroke. Lower intensity CIMT is better than higher intensity in the very early stages after stroke.

Mental Practice

Man in headphones listening to mental practice recordings.
You might listen to an audio recording describing the sequence of throwing a ball, imagining yourself doing it. After listening, actually practice throwing the ball the way you envisioned!

What it is:

Mental practice, sometimes called motor imagery or mental imagery, is a training method for improving your hand and arm function without moving a muscle!

Mental practice is typically done by listening to pre-recorded audio that describes in detail the motor movement of a specific task. The listener imagines their hand and arm moving in a “typical” way, and the instructor provides cues to extend their arm or open their fingers, as well as the entire sensory experience of the task.

While it’s true that you can do mental practice on its own, it’s best combined with physical practice immediately following.

Why it works:

Brain scans show that similar parts of the brain are activated whether movement is actual, observed or imagined.

It’s a separate area of the brain that’s responsible for actually triggering the muscle movement, but it goes to show that there’s a lot more required of the brain to complete a task than just sending a signal to the muscle.

Who it’s for:

Mental practice has been shown to improve arm movement and functional use in patients after stroke of all levels of abilities and as a treatment approach for people months or years after stroke!

Mirror Therapy

Unaffected hand and its mirror image reflected in mirror box.
It is critical to stay focused on the reflected image of your hand during mirror therapy, imagining that it is your affected side performing the target movements.

What it is:

Mirror therapy is another voodoo-seeming approach that has a lot of scientific evidence to back it up. It essentially tricks your brain into thinking your affected hand is moving.

You position a mirror to reflect your non-affected hand, while hiding your affected hand. Any movement of your non-affected hand will be reflected in the mirror and make it seem as though you are actually moving your affected hand.

Why it works:

The approach is centered around mirror neurons, which fire in your brain when you see your arm move. Typically, we think about motor neurons being sent from the brain to the muscle, but we don’t realize that mirror neurons are connected to the motor neurons.

After a stroke you lose the ability to access your motor neurons, but not your mirror neurons. By accessing your mirror neurons through seeing your movement (even if the movement is fake), you are tapping into the network between the neurons.

It’s like trying to reconnect with an old friend on Facebook by finding the friends they’re connected with. It might not be the most direct approach in a real life situation, but in stroke rehab that friend of a friend might be your strongest connection.

Who it’s for:

Mirror therapy can be used for people with no movement of the hand or smaller movements of the hand and shoulder, but not functional movement of the hand.

If you have functional movement of your hand, meaning individual finger movement and wrist movement, you have surpassed the benefit that mirror therapy can provide.

It can be used early after stroke, as well as in the chronic stages of stroke.

Virtual Reality

Neofect Smart Board virtual reality arm exercise system.
The Neofect Smart Board is a non-immersive virtual reality rehabilitation system.

What it is:

Virtual reality uses a computer interface to simulate a real life objects and events. It’s become an increasingly more prevalent rehabilitation technique to provide motivation and engagement in therapy.

There are two types:  

  1. Immersive: goggles are placed over the eyes and the patient is visually in a different environment than their actual physical one
  2. Non-immersive: sensors are placed on the body and track the movement of the body and the movements are shown on a screen

Why it works:

Virtual reality works best when paired with traditional therapy. It’s theorized to provide more motivation and engagement for the intensity of therapeutic exercise needed for neuroplasticity. It’s been shown to beneficial in high doses, meaning more than 20 hours.

Another possible factor of why virtual reality works are the same mechanisms that make mirror therapy effective (tapping into the mirror neurons) could be similar.

Virtual reality also creates a biofeedback loop: your brain sends a signal to the muscle, the brain receives a signal back in the form of visual or auditory input. Basically, you get rewarded for your effort.

Who it’s for:

Virtual reality can be used with people who have mild to severe impairments, and from early after stroke to years out.

When deciding what’s right for you, it’s important to look at the adjustability of the device to meet you where you’re at and also to increase in difficulty as you improve.

If you have minimal movements, you’ll want a virtual reality tool specifically for stroke rehabilitation. If you have more movement, it’s possible to use gaming systems not specifically designed for rehab, but make sure you have the support to optimize it for rehab.

High Dose Repetitive Task Practice

Putting coins in a piggy bank during repetitive task practice.
There are many ways to do task-specific training at home. Placing coins into a piggy bank is just one of them!

What it is:

Repetitive Task Practice is when you practice a task or a part of a task over and over. Task-specific training is a type of repetitive task practice, and refers to the task we complete that is relevant to our daily life.

“Reach to grasp, transport and release” is a type of task-specific training because it is one of the common motor requirements for many functional daily tasks.

The keys for repetitive task practice:

  • Task must be meaningful
  • Participant must be an active problem-solver
  • Real life objects are used
  • Difficulty level is not too high and not too low
  • Repetition is key

Why it works:

Repetitive Task Practice is based on motor learning theory. Our brains are driven by function. We’re able to achieve neuroplasticity with development of skills, as our brain processes the demands of the task, which have motor and cognitive components.

It’s often used with other treatments, such as virtual reality, to increase the 15 hour dosage that has been shown to be beneficial.

Who it’s for:

Task-specific practice is generally used and is studied in people who have some functional ability of their hand. It’s been shown to be beneficial throughout the rehabilitation process.

Even though the research has been focused on “functional ability” of the hand by practicing reach, grasp, transport, release; there’s potential for recovery by using the same principles of task-specific practice: real life objects, functional tasks, and problem-solving even without the ability to grasp.

Functionally, we can use our affected upper extremity as a stabilizer, an assist, or for manipulation. There are lots of ways to get that side involved to prevent “learned non-use” and to improve your problem-solving skills.

Now What?

There are two key factors to any hand recovery method: support and meaning.

Neofect aims to support and inspire you to live your best life with virtual reality tools that can be used as part of a constraint-induced movement therapy program or with repetitive task practice.

Our comprehensive recovery and wellness app: Neofect Connect and our YouTube Channel: Find What Works are based on the principles of repetitive task practice and aim to give you the tools to live your best life.

Now the only question is, what are you waiting for?

Pollock  A, Farmer  SE, Brady  MC, Langhorne  P, Mead  GE, Mehrholz  J, van Wijck  F. Interventions for improving upper limb function after stroke. Cochrane Database of Systematic Reviews 2014, Issue 11. Art. No.: CD010820. DOI: 10.1002/14651858.CD010820.pub2.


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[ARTICLE] Key components of mechanical work predict outcomes in robotic stroke therapy – Full Text



Clinical practice typically emphasizes active involvement during therapy. However, traditional approaches can offer only general guidance on the form of involvement that would be most helpful to recovery. Beyond assisting movement, robots allow comprehensive methods for measuring practice behaviors, including the energetic input of the learner. Using data from our previous study of robot-assisted therapy, we examined how separate components of mechanical work contribute to predicting training outcomes.


Stroke survivors (n = 11) completed six sessions in two-weeks of upper extremity motor exploration (self-directed movement practice) training with customized forces, while a control group (n = 11) trained without assistance. We employed multiple regression analysis to predict patient outcomes with computed mechanical work as independent variables, including separate features for elbow versus shoulder joints, positive (concentric) and negative (eccentric), flexion and extension.


Our analysis showed that increases in total mechanical work during therapy were positively correlated with our final outcome metric, velocity range. Further analysis revealed that greater amounts of negative work at the shoulder and positive work at the elbow as the most important predictors of recovery (using cross-validated regression, R2 = 52%). However, the work features were likely mutually correlated, suggesting a prediction model that first removed shared variance (using PCA, R2 = 65–85%).


These results support robotic training for stroke survivors that increases energetic activity in eccentric shoulder and concentric elbow actions.


Assistance is often provided to aid limb movement during the rehabilitation process of stroke survivors. Many clinical researchers agree that active participation enhances recovery, and the goal of therapy should be to maximize “involvement” [12]. Too much assistance can actually discourage patient effort [3]. However, measurement of the degree to which patients are actually active is often difficult. Advances in rehabilitation devices allow for the measurement of forces and motion to better monitor patient activity. Here we investigate how upper limb mechanics during training relate to recovery.

Current tools for measuring physical activity during therapy offer limited information for describing interaction with the external environment or agent. While studies have shown that the intensity of therapy influences patient improvement, researchers have relied on simple metrics related to experimental conditions (e.g. movement repetitions, time-on-task, and therapy dosage) [45]. More sophisticated tools have been used to directly measure energetic contributions during therapy, such as oxygen consumption devices to measure metabolic cost [6] or electromyography to measure muscle activity [78]. However, such measures do not account for the time-varying force-motion relationships that occur during assisted movement. Robots easily measure both kinematic and kinetic variables facilitating the computation of energetic contributions in terms of mechanical power and work.

While energetic descriptions of movement have been widely studied, it has mainly focused on cyclic [9] or sustained movements, such as walking. Researchers have computed work and power to characterize normal and abnormal gait patterns [1011], to evaluate robot-assisted locomotion [12], and to reduce energetic costs when using exoskeletons [13]. Recently our work has focused on robotic augmentation of upper limb dynamics to facilitate vigorous movement during practice [1415]. We showed that stroke survivors increase total work output during force training [16]. Our intervention was fundamentally different than many previous strategies in that patients trained over a broader range of movements. In contrast to reaching studies [1718], such self-directed exploration allows for the examination of how energetics might depend on different force and motion states.

To better evaluate the variation in patient energetics, we believe more comprehensive measures are required beyond total expenditure of power or work. Researchers have also examined compartmentalized work and power measures in normal limb behaviors, for example, associating magnitudes of mechanical energy (e.g. positive/concentric and negative/eccentric work) with movement actions (e.g. flexion and extension) at individual joints [19]. Motor impairments due to stroke are also typically described in the context of motor actions of the limb. For example, stroke survivors exhibit abnormal flexion and extension synergies [20] and alterations in concentric and eccentric muscle contractions [2122]. As such, impairments can be associated with subcomponents of work and power. As patients interact differently in response to forces, subcomponents of work and power could reveal individual differences in involvement.

An emerging trend in rehabilitation is to identify certain factors that predict individual improvement in response to therapy. Researchers have identified patient biomarkers (impairment level, neurophysiological) correlated to patient outcomes providing better recommendations for therapy [23,24,25]. Similarly, our goal is to determine if particular types of work are more important to patient recovery. Such evaluation could inform decisions on design strategies and optimize assistance to each individual. In contrast to previous studies which have relied on independent analyses of many individual predictors, our analysis goal necessitates more rigorous statistical methods to deal with potentially related work features. One possible solution is to employ multiple regression analysis which can identify features most important for prediction.

In this paper, we investigate how the energetic contributions of stroke survivors during robot-assisted training relate to upper limb recovery. We employ well-established methods of inverse dynamics to estimate the torques generated by each patient during self-directed motor exploration training with customized forces. These methods conveniently allow us to quantify the energetic involvement of each individual joint in terms of mechanical work. We then use multiple regression analysis to identify which components of work are most important for predicting recovery. We hypothesize that positive work (concentric) in elbow extension is the best predictor of outcome. This study provides a key preliminary step towards evaluating energetic descriptions of patient involvement which can inform methods for upper limb robotic therapy practice.


Study participants

This investigation considered data collected from a previous study that featured 22 stroke survivors [15]. The main inclusion criteria included: 1) chronic stroke (8+ months post-stroke) 2) hemiparesis with moderate to severe arm impairment measured by the upper extremity portion of the Fugl-Meyer Assessment (UEFM score of 15–50) 3) primary cortex involvement. Each individual gave informed consent in accordance with the Northwestern University Institutional Review Board (IRB).


Experiment participants were asked to operate a two-degree of freedom robotic device with the affected arm (Fig. 1a). A custom video display system (not shown) provided visual feedback of the location of the wrist as the arm moved in the horizontal plane. During movement, the weight of the arm was supported. Movement data was collected at 200 Hz and filtered using a 5th order Butterworth low pass filter with a 12 Hz cutoff. Using anthropometric measurements recorded from each participant, we computed inverse kinematic relationships to obtain elbow and shoulder joint angles corresponding to endpoint position data. The robot control and instrumentation were mediated by a Simulink-based XPC Target computer, with a basic rate of 1 kHz. The robot controller compensated for the dynamics of the robot arm. A force sensor attached to the end-effector measured the human-robot interaction forces.

Experimental design. a Stroke survivors performed self-directed motor exploration by moving the robot handle in the horizontal plane. Measurements of their limb motion and the interaction forces were used to estimate the positive (concentric) and negative (eccentric) mechanical work exerted in different directions of shoulder and elbow joint motion. b The probability distribution of each individual’s movement velocities during unassisted motor exploration (top; blue indicates lower probability, red indicates higher probability, black contour line represents the 90th percentile velocity coverage) formed the basis for the design of customized training forces (bottom; red arrows indicate the direction and relative magnitude of forces applied, colored contour lines represents Gaussian model fit to velocity data)



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