Failure of my medical team to get my good long sleeve arm buttoned

 With zero recovery of my left hand/fingers I can't button my right arm sleeve. This then requires massive amounts of concentration when reaching for food when dining to prevent the sleeve from dragging through the food. I sometimes can button the sleeve before putting it on, but the tightness of getting my hand thru will tell me if it's possible to remove it without ripping the button off. 

My OT gave me no interventions to bring back my fingers. All I got was: 'At eight weeks, research shows little chance of getting finger mobility back if there isn't movement at eight weeks'. That is a failure mindset, it should have triggered calls to stroke leadership to get research going that delivers finger recovery!

Development of exoskeleton finger mechanisms for stroke rehabilitation

Hope they succeed since I see nothing specific out there that will recover finger function. If you have a competent? doctor s/he will know about this and bring it to your attention when research is complete. But I bet you don't have that.

 Development of exoskeleton finger mechanisms for stroke rehabilitation

Authors:     Lam, Matthew Jun Wei
Keywords:     Engineering
Medicine, Health and Life Sciences
Issue Date:     2024
Publisher:     Nanyang Technological University
Source:     Lam, M. J. W. (2024). Development of exoskeleton finger mechanisms for stroke rehabilitation. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/176402
Project:     A036

Abstract:     

 

Stroke rehabilitation presents various challenges, including limited access to specialized care, lack of intensive rehabilitation options, inconsistent therapy, and variability in therapist exercise. This literature review examines these challenges and proposes a solution aimed at improving rehabilitation outcomes for stroke survivors with curled fingers due to hand spasticity and lack of neuroplasticity. The proposed solution involves developing exoskeleton finger mechanisms specifically designed to address specific needs of individuals with curled fingers post-stroke. These mechanisms aim to provide consistent and intensive rehabilitation options customized to individual needs of stroke patients, thereby addressing identified challenges with stroke rehabilitation. By mitigating these challenges, the project seeks to improve the effectiveness and accessibility of stroke rehabilitation therapeutic services while pushing the boundaries of stroke patient’s recovery potential. The findings of this literature review underscore the importance of targeted interventions in overcoming barriers to optimal stroke recovery and enhancing the overall quality of life for stroke survivors. The overall approach to the design process, design considerations and development of finger mechanisms are covered in the report.

Glove offers 'life changing' movement to stroke patients

But can it extend the fingers clenched due to spasticity?  That's my problem.

Glove offers 'life changing' movement to stroke patients

A prototype electronic glove that enables movement in paralysed hands is potentially "life-changing", stroke patients have said.

Developed at the University of Southampton, it is intended to help people regain muscle strength and function.

Printed electrodes make contact with the skin and send electronic impulses to produce an artificial movement.

Dave Lea, the first patient to try the device, said it was "breath-taking".

The glove is intended to help people regain muscle strength and function

By stimulating the nerves and muscles, it enables stroke survivors to achieve movement in their weak side, helping them to regain muscle strength and function.

Professor Kai Yang, who developed the glove, said it could be used by patients as part of their rehabilitation at home.

He said: "This glove enables them to work on their rehab in small blocks of time when it suits them.

"With stroke rehabilitation, the more you practice movement, the more you regain muscle strength and mobility."

Dave and Susan Lea said the glove could be "life-changing"

The gloves were produced using the Winchester School of Art's industrial knitting machines, which can produce clothing that is both strong and soft enough to wear comfortably.

The electrodes are printed inside the sleeve and connected to an electronic control unit, allowing the user to vary the level of stimulation as required.

Mr Lea, from Chandler's Ford, tested the therapeutic device as part of his recuperation from a major stroke in 2015, at the age of 54, that left him largely paralysed on his right side.

The glove enables him to move his paralysed right hand.

"It's life changing - it means I can move my hand - something I've been unable to do for eight years. This is breath-taking," he said.

It is hoped that by repeated movements using the glove, he will one day no longer need it and will open and close his hand independently again.

Mr Lea's wife Sarah said it was "just amazing" seeing him test the glove for the first time.

She said: "It's giving Dave the opportunity to do that grip and release movement that he finds very difficult to do naturally.

"Things like picking up normal everyday items become a lot easier to do.

"It's incredible that it enables him to move his hand. It really could change the lives of stroke survivors."

Mr Lea's wife Sarah said it was "just amazing" seeing him test the glove

Prof Yang is now looking to refine the design of the prototype glove.

She said she intended to seek regulatory approval and then work with a manufacturer in the hope of the glove being commercially available within five years.

"We are delighted with the prototype and would like to see this become a product that's available to all stroke survivors, to help improve their recovery and their quality of life," she added.

A comprehensive scheme for the objective upper body assessments of subjects with cerebellar ataxia

 I could have done none of these tests, dead brain kinda prevents that. So what protocols are out there to recover hand/finger function due to dead brain? 

So you accurately described a problem, but provided NOTHING to solve that problem. Good to know how useless this research was.

 

finger chase test (FCT), finger tapping test (FTT), finger to nose test (FNT) and dysdiadochokinesia test (DDKT))

A comprehensive scheme for the objective upper body assessments of subjects with cerebellar ataxia

 

• Ha Tran,
• Khoa D. Nguyen,
• Pubudu N. Pathirana,
• Malcolm K. Horne,
• Laura Power &
• David J. Szmulewicz 

Journal of NeuroEngineering and Rehabilitation volume 17, Article number: 162 (2020) Cite this article

Abstract

Background

Cerebellar ataxia refers to the disturbance in movement resulting from cerebellar dysfunction. It manifests as inaccurate movements with delayed onset and overshoot, especially when movements are repetitive or rhythmic. Identification of ataxia is integral to the diagnosis and assessment of severity, and is important in monitoring progression and improvement. Ataxia is identified and assessed by clinicians observing subjects perform standardised movement tasks that emphasise ataxic movements. Our aim in this paper was to use data recorded from motion sensors worn while subjects performed these tasks, in order to make an objective assessment of ataxia that accurately modelled the clinical assessment.

Methods

Inertial measurement units and a Kinect© system were used to record motion data while control and ataxic subjects performed four instrumented version of upper extremities tests, i.e. finger chase test (FCT), finger tapping test (FTT), finger to nose test (FNT) and dysdiadochokinesia test (DDKT). Kinematic features were extracted from this data and correlated with clinical ratings of severity of ataxia using the Scale for the Assessment and Rating of Ataxia (SARA). These features were refined using Feed Backward feature Elimination (the best performing method of four). Using several different learning models, including Linear Discrimination, Quadratic Discrimination Analysis, Support Vector Machine and K-Nearest Neighbour these extracted features were used to accurately discriminate between ataxics and control subjects. Leave-One-Out cross validation estimated the generalised performance of the diagnostic model as well as the severity predicting regression model.

Results

The selected model accurately (96.4%) predicted the clinical scores for ataxia and correlated well with clinical scores of the severity of ataxia (rho=0.8, rho=0.8, p<0.001). The severity estimation was also considered in a 4-level scale to provide a rating that is familiar to the current clinically-used rating of upper limb impairments. The combination of FCT and FTT performed as well as all four test combined in predicting the presence and severity of ataxia.

Conclusion

Individual bedside tests can be emulated using features derived from sensors worn while bedside tests of cerebellar ataxia were being performed. Each test emphasises different aspects of stability, timing, accuracy and rhythmicity of movements. Using the current models it is possible to model the clinician in identifying ataxia and assessing severity but also to identify those test which provide the optimum set of data.

Trial registration Human Research and Ethics Committee, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia (HREC Reference Number: 11/994H/16).