Posts Tagged neuro-rehabilitation

[BLOG POST] Technology: Filling the gaps in occupational and physical therapy

It is unsurprising that, as the population increases and ages, more therapists will be needed for rehabilitation, but the therapist numbers are not growing to match the need for therapy. The resulting deficit leaves even top rehabilitation centers at a loss; fewer therapy experts means less rehab time for patients.

The human element of therapy is undeniable—people need people in order to heal. However, time and physical effort is required to manually facilitate high-repetition therapy exercises desperately needed by patients and this limits their execution, even in world-class facilities. Therapists are the limiting factor in patient care simply because there are not enough experts and their physical resources are limited, especially in case of severely affected patients who require high physical support. This problem is only expected to worsen.

Technology, in the form of robotic rehabilitation, solves this issue elegantly by relieving therapists of the burden of attending to every repetition, allowing them to serve more patients, more efficiently, and with better outcomes.

In stroke and neuro rehabilitation, intensity is key

Many studies have shown that in various types of injuries, rehabilitation that includes hundreds to thousands of repetitions produce best clinical outcomes for upper and lower extremity movements. Task specificity and muscle reconditioning, in addition to neuroplasticity, are important factors influenced by intense, targeted, repetitive motor training.

A shocking study conducted in 2017 on spinal cord rehab patients found that:

  • As much at 40% of therapy time was dedicated to non-therapeutic actions, such as sling transfers and activity set up
  • Patients spent only 12-15 minutes in group-based rehab activity
  • Up to 2/3 of patients did not participate in group activities at all
  • The highest-repetition groups did not exceed 100 repetitions for occupational and physiotherapy combined
  • The daily repetitions were significantly lower than those require for muscle and neural improvements.1

Furthermore, the following table from a study of outpatients suffering from partial paralysis post-stroke shows less than 100 repetitions per session with the exception of walking steps.2



In animal studies, however, it was found that at least 400-600 repetitions are necessary to lead to structural neural changes for upper limb.1 There is clearly a significant disparity between the therapy needed for full recovery and the therapy available to patients. In addition, researchers surveyed 7 stroke survivors, 6 caregivers, and 20 rehab staff and found that outside of rehab:

“subsequent time was described as ‘dead and wasted.’ Main careers perceived stroke survivors felt ‘out of control … at everyone’s mercy’ and lacked knowledge of ‘what to do and why’ outside of therapy. Clinical staff perceived the stroke survivor’s ability to drive their own recovery was limited by the lack of ‘another place to go’ and the ‘passive rehab culture and environment’.”3

This passive rehab culture is a significant factor for reduced therapy outcomes. When dependent on limited rehab time for recovery, stroke patients feel unproductive and hopeless. More active therapy time can not only improve a patient’s daily function and physical health, but their mental health as well.

How Technology Can Help

It is clear that patients are not currently getting the volume and intensity of therapy required for ideal outcomes, and this not only has a physical cost, but also takes a mental toll on patients. Robot-assisted rehab can improve current therapy practices in the following ways:

  • Assisted gait training – research shows that robots can assist with “highly repetitive training of complex gait cycles, something a single therapist cannot easily do alone”4
  • Precision feedback – virtual reality and sophisticated measurements can provide precise movement feedback to leverage the recovering brain’s neuroplasticity and enhance proprioception5
  • High repetition and intensity – without constant physical assistance from a therapist, which then frees the therapist to perform other types of supporting tasks

While therapists cannot be replaced by robot-assisted rehabilitation technology, these tools can augment their practice to both reduce strain and fatigue in therapists and improve patient outcomes, sometimes making possible what was impossible previously, such as walking. Robot-assisted rehabilitation can reduce physical strain in therapists while providing for patients the high volume of repetitions needed to achieve best outcomes in therapy.


1 Zbogar D, Eng JJ, Miller WC, Krassioukov AV, Verrier MC. Movement repetitions in physical and occupational therapy during spinal cord injury rehabilitation. Spinal Cord. 2017;55(2):172–179. doi:10.1038/sc.2016.129
2 Lang CE, MacDonald JR, Gnip C. Counting repetitions: an observational study of outpatient therapy for people with hemiparesis post-stroke. J Neurol Phys Ther. 2007 Mar;31(1):3-10. PubMed PMID: 17419883.
3 Eng XW, Brauer SG, Kuys SS, Lord M, Hayward KS. Factors Affecting the Ability of the Stroke Survivor to Drive Their Own Recovery outside of Therapy during Inpatient Stroke Rehabilitation. Stroke Res Treat. 2014;2014:626538. doi:10.1155/2014/626538
4 Morone G, Paolucci S, Cherubini A, et al. Robot-assisted gait training for stroke patients: current state of the art and perspectives of robotics. Neuropsychiatr Dis Treat. 2017;13:1303–1311. Published 2017 May 15. doi:10.2147/NDT.S114102
5 Turner DL, Ramos-Murguialday A, Birbaumer N, Hoffmann U, Luft A. Neurophysiology of robot-mediated training and therapy: a perspective for future use in clinical populations. Front Neurol. 2013;4:184. Published 2013 Nov 13. doi:10.3389/fneur.2013.00184

Originally published on 25.2.2020

via Technology: Filling the gaps in occupational and physical therapy – Hocoma

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[Abstract] Robotic Exoskeleton for Wrist and Fingers Joint in Post-Stroke Neuro-Rehabilitation for Low-Resource Settings


Robots have the potential to help provide exercise therapy in a repeatable and reproducible manner for stroke survivors. To facilitate rehabilitation of the wrist and fingers joint, an electromechanical exoskeleton was developed that simultaneously moves the wrist and metacarpophalangeal joints.
The device was designed for the ease of manufacturing and maintenance, with specific considerations for countries with limited resources. Active participation of the user is ensured by the implementation of electromyographic control and visual feedback of performance. Muscle activity requirements, movement parameters, range of motion, and speed of the device can all be customized to meet the needs of the user.
Twelve stroke survivors, ranging from the subacute to chronic phases of recovery (mean 10.6 months post-stroke) participated in a pilot study with the device. Participants completed 20 sessions, each lasting 45 minutes. Overall, subjects exhibited statistically significant changes (p < 0.05) in clinical outcome measures following the treatment, with the Fugl-Meyer Stroke Assessment score for the upper extremity increasing from 36 to 50 and the Barthel Index increasing from 74 to 89. Active range of wrist motion increased by 190 while spasticity decreased from 1.75 to 1.29 on the Modified Ashworth Scale.
Thus, this device shows promise for improving rehabilitation outcomes, especially for patients in countries with limited resources.

via Robotic Exoskeleton for Wrist and Fingers Joint in Post-Stroke Neuro-Rehabilitation for Low-Resource Settings – IEEE Journals & Magazine

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[NEWS] Thunderbirds fund cutting-edge rehab enhancements for Barrow

Above: The Thunderbirds Charities gift to Barrow Neurological Foundation is being used to acquire four new devices, similar to this robotic hand. These instruments enable therapists at the Barrow Neuro-Robotics Rehabilitation Center to personalize therapy based on a patient’s abilities.

Patients recovering from stroke, traumatic brain and spine injuries will now have a leg up in their recovery journeys, thanks to a $350,000 grant from Thunderbirds Charities to Barrow Neurological Foundation.
An estimated 13.8 million Americans live with a disability caused by a brain or spinal cord injury, and each year, Barrow records more than 30,000 outpatient visits in the Neuro-Rehabilitation Center.

With this gift from Thunderbirds Charities, Barrow will acquire four cutting-edge devices for its Neuro-Robotics Rehabilitation Center, which provides personalized therapy to deliver better outcomes in less time. These robotics include:

• A body weight-supported treadmill that uses augmented and virtual reality to simulate challenges in everyday life, such as walking a golf course.

• A robot-assisted shoulder and arm rehabilitation device with intelligent gravity compensation and virtual reality to work on skills needed for daily function.

• A sensor-based device used to work on balance and posture training.

• An interactive surface for upper extremity, cognitive and sensory retraining to allow patients to practice motor skills.

Barrow has been at the forefront in the use of robotics, which mimic normal human movements and can be programmed to support or challenge a patient’s abilities. Many of these devices incorporate an interactive component, creating a game-like experience for the patient to conquer.

“These new robotics will help Barrow patients relearn how to stand, walk and perform skills that many take for granted, while also providing our therapists with more advanced tools to monitor progress,” said Katie Cobb, president of Barrow Neurological Foundation. “We want to thank Thunderbirds Charities for providing these life-changing tools for our patients’ continued recovery.”

“Barrow’s Neuro-Robotics Rehabilitation Center is making a positive, profound impact on the health of patients recovering from severe and debilitating injuries, and we are honored to be able to support such a great mission,” said Carlos Sugich, President of Thunderbirds Charities.

via Thunderbirds fund cutting-edge rehab enhancements for Barrow | AZ Big Media

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[VIDEO] Relearning and Retraining in Brain Injury Rehabilitation Does VR help? – YouTube

Δημοσιεύτηκε στις 20 Ιουν 2018

Dr. Sharan Srinivasan | Stereotactic and Functional Neurosurgeon, CMD-NewRo- the neuro rehab experts presents on “Relearning and Retraining in Brain Injury Rehabilitation Does VR help?” at the vamrr Summit on Virtual Reality in Health | 21 March | Bengaluru


via Relearning and Retraining in Brain Injury Rehabilitation Does VR help? – YouTube

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[Abstract + References] Classifying Imaginary Hand Movement through Electroencephalograph Signal for Neuro-rehabilitation


Brain-Computer-Interface (BCI) has been widely used in the field of neuro-rehabilitation such as automatic controls based on brain commands to upper and lower extremity prosthesis devices in patients with paralysis. In a post-stroke period, approximately 50% of stroke sufferers have unilateral motor deficits leading to a chronic decline in chronic upper extremity function. Stroke affects patients in their productive and elderly age which is potentially creating new problems in national health development. BCI can be used to aid post-stroke patient recovery, thus motion detection and classification is essential for optimizing BCI device control. Therefore, this study aims to distinguish several hand functions such as grasping, pinching, and hand lifting from releasing movement in accordance with the usual movements performed during post-stroke rehabilitation based on brain signals obtained from electroencephalogram (EEG). In this study, the information that obtained from the processing of EEG signals were be used as inputs for artificial neural networks then classified to distinguish two types of imaginary hand movements (grasping v. releasing, pinching v. releasing, hand lifting v. releasing). The results of these classifications using Extreme Learning Machine (ELM) based on spectral analysis and CSP (Common Spatial Pattern) calculation show that ELM and CSP was a good feature in distinguishing two types of motion with software/system accuracy average above 95%. This could be useful for optimizing BCI devices in neuro-rehabilitation, such as combining with Functional Electrical Stimulator (FES) device as a self-therapy for post-stroke patient.


Badan Penelitian dan Pengembangan Kesehatan. Riset Kesehatan Dasar 2013, Available at :, accesed February 2017.

J. A. Franck. Concise Arm and Hand Rehabilitation Approach in Stroke. vol. 3. no. 4. 2015.

N. Birbaumer. A. R. Murguialday. and L. Cohen. Brain-computer interface in paralysis. Curr. Opin. Neurol. vol. 21. no. 6. pp. 634–8. 2008.

J. J. Daly. R. Cheng. J. Rogers. K. Litinas. K. Hrovat. and M. Dohring. Feasibility of a New Application of Noninvasive Brain Computer Interface (BCI): A Case Study of Training for Recovery of Volitional Motor Control After Stroke. J. Neurol. Phys. Ther. vol. 33. no. 4. pp. 203–211. 2009.

K. K. Ang. C. Guan. K. S. Phua. C. Wang. L. Zhou. K. Y. Tang. G. J. Ephraim Joseph. C. W. K. Kuah. and K. S. G. Chua. Brain-computer interface-based robotic end effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke.. Front. Neuroeng. vol. 7. no. July. p. 30. 2014.

E. Buch. C. Weber. L. G. Cohen. C. Braun. M. A. Dimyan. T. Ard. J. Mellinger. A. Caria. S. Soekadar. A. Fourkas. and N. Birbaumer. Think to move: A neuromagnetic brain-computer interface (BCI) system for chronic stroke. Stroke. vol. 39. no. 3. pp. 910–917. 2008.

G.-B. Huang. Q. Zhu. C. Siew. G. H. Ã. Q. Zhu. C. Siew. G.-B. Huang. Q. Zhu. and C. Siew. Extreme learning machine: Theory and applications. Neurocomputing. vol. 70. no. 1–3. pp. 489–501. 2006.

Emotiv Insight User Manual. 2015, Availabe at :, accessed June 2017

P. Szachewicz. Classification of Motor Imagery for Brain-Computer Interfaces. p. 50. 2013.

B. Shoelson. edfRead, Available at : 31900-edfread, accesed February 2017.

J. Ethridge and W. Weaver. Common Spatial Patterns Alogarithm. MatlabCentral. 2009. .

Q. Yuan. W. Zhou. S. Li. and D. Cai. Epileptic EEG classification based on extreme learning machine and nonlinear features. Epilepsy Res. vol. 96. no. 1–2. pp. 29–38. 2011.

G. Huang. Introduction to Extreme Learning Machines. Hands-on Work. Mach. Learn. Biomed. Informatics 2006. 2006.

M. H.. A. Samaha. and K. AlKamha. Automated Classification of L/R Hand Movement EEG Signals using Advanced Feature Extraction and Machine Learning. Int. J. Adv. Comput. Sci. Appl. vol. 4. no. 6. p. 6. 2013.

G. Lange. C. Y. Low. K. Johar. F. A. Hanapiah. and F. Kamaruzaman. Classification of Electroencephalogram Data from Hand Grasp and Release Movements for BCI Controlled Prosthesis. Procedia Technol. vol. 26. pp. 374–381. 2016.

X. Yong and C. Menon. EEG classification of different imaginary movements within the same limb. PLoS One. vol. 10. no. 4. pp. 1–24. 2015.

via Classifying Imaginary Hand Movement through Electroencephalograph Signal for Neuro-rehabilitation | Rahma | Walailak Journal of Science and Technology (WJST)

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[ARTICLE] Development of a robotic device for post-stroke home tele-rehabilitation – Full Text

This work deals with the complex mechanical design task of converting a large pneumatic rehabilitation robot into an electric and compact system for in-home post-stroke therapies without losing performance. It presents the new HomeRehab robot that supports rehabilitation therapies in three dimensions with an adaptive controller that optimizes patient recovery. A preliminary usability test is also conducted to show that its performance resembles that found in RoboTherapist 2D commercial system designed for hospitals. The mechanical design of a novel and smart two-dimensional force sensor at the end-effector is also described.

According to the World Health Organization, by 2050, the number of persons over 65 years old will increase by 73% in the industrialized countries and by 207% worldwide.1 This segment of population is particularly prone to suffer a cerebrovascular accident or stroke, since the relative incidence of stroke doubles every decade after age 55. Stroke survivors immediately experience hemiparesis, resulting in impairment of extremities associated with diminished health-related quality of life.2 Rehabilitation can help hemiparetic patients to learn new ways of using and moving their weak arms and legs. It is also possible with immediate therapy that people who suffer from hemiparesis may eventually regain movement. However, reductions in healthcare reimbursement place constant demands on rehabilitation specialists to reduce the cost of care and improve productivity.3 Service providers have responded by shortening the length of patient hospitalization.4,5 Additionally, early home supported discharge of subacute stroke patients has been proved to have a significant impact on motor recovery after stroke although it requires some level of innovation of methods and tools for service delivery to really become a sustainable solution for the healthcare system.6,7 All these reasons support the necessity of in-home rehabilitation systems as the one proposed in this work.

Socially, chronic stroke patients can highly benefit from innovative approaches based on home rehabilitation therapy.8 Technological and scientifically, only a few commercial systems are currently available for in-home use (e.g. HandMentor™,9 ReJoyce,10 and ArmeoBoom from Hocoma), and their performances are not comparable to in-person therapies.11 Key challenges not addressed properly for home systems include features such as affordability, autonomy, and high performance. Only if all requirements are satisfied, it will be possible to encourage national health systems, insurance companies, and patients to apply such platforms.

This work is part of an ongoing project called HomeRehab that will develop a new tele-rehabilitation robotic system for delivering therapy to stroke patients at home. Instead, Technologies has a robotic system called RoboTherapist 2D (Figure 1) developed to provide rehabilitation to patients who suffer from stroke and/or other neurological disorders.12 Currently, the system, as the majority of commercial devices, is only designed to be used in hospitals and medical centers in collaboration with nurses and medical staff.13


Figure 1. RoboTherapist 2D system from Instead Technologies.

HomeRehab aims to modify and adapt the system so it can be used at home by patients easily and supporting the premise of tele-rehabilitation.14 This article describes in detail the mechanical design of the new HomeRehab system that adapts the RoboTherapist 2D for in-home use by making it smaller, lighter, and cheaper, but maintaining its high performance. Additionally, the system includes a third degree-of-freedom (DOF) plus a novel low-cost force sensor that were not considered for the original platform, but they are very interesting features for a complete in-home solution. Another key feature of the whole system is that it integrates patient monitoring techniques using wearable devices to monitor the physiological state of the patient and modify exercises based on that information.

The following section briefly summarizes the main requirements considered to develop a successful device, and afterward in section “Mechanical design,” the mechanical design of the new system is described in detail. Section “Robot controller” presents the controller of the robot as well as the adaptive controller implemented for the rehabilitation therapies. Section “Usability pilot study” carries out a validation phase by conducting several tests and surveys to compare the usability of RoboTherapist 2D with HomeRehab, and last section gathers main conclusions. […]


Continue —>   Development of a robotic device for post-stroke home tele-rehabilitationAdvances in Mechanical Engineering – Iñaki Díaz, José María Catalan, Francisco Javier Badesa, Xabier Justo, Luis Daniel Lledo, Axier Ugartemendia, Jorge Juan Gil, Jorge Díez, Nicolás García-Aracil, 2018

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[Abstract] A novel approach to integrate VR exer-games for stroke rehabilitation: Evaluating the implementation of a ‘games room’


This study evaluates the integration of virtual reality (VR) exer-games for people post-stroke through the implementation of a “exer-games room” in an inpatient rehabilitation hospital. Qualitative data (interviews with patients and clinicians) and quantitative data (from the first year of operation of the games room) are synthesized and reviewed to provide an overall interpretative evaluation. The Consolidated Framework for Implementation Research (CFIR) is used to analyze the successful and less successful factors involved in the implementation.

Source: A novel approach to integrate VR exer-games for stroke rehabilitation: Evaluating the implementation of a ‘games room’ – IEEE Xplore Document

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[WEB SITE] Press Release: New Move to Use Robots for Stroke Rehabilitation –

Due to the high costs of clinical neuro-rehabilitation, post stroke treatments are limited in all countries to only a few weeks to months after the stroke event. Any system aimed at pro-longing neuro-rehabilitation out of the clinics, for example at patients’ homes; that can use low cost treatments, addresses a major issue in our current health care management systems.

How SCRIPT will contribute:

The SCRIPT project will produce two prototype robotic devices, a passive‐actuated device and one actuated actively, both of which can be used in the stroke patient’s home. Provision of motivating and challenging therapeutic activities using a robotic hand and wrist rehabilitation device at home, will provide a chance for more frequent therapies and interactions. It is thought that such frequent interaction will further influence recovery at chronic phases of stroke rehabilitation.

The principal aims of SCRIPT are to:

• use such rehabilitative technologies at patient’s home to enable better management of chronic stroke patients
• focus on hand and wrist exercise; as this presents the least researched area with the most functional relevance and potential for contribution to personal independence.
• look at differences between passive and active actuated devices.
• provide an educational, motivational and engaging interaction, therefore making a therapy session more enjoyable for patients.
• focus on remote management and support of the patient.
• deduce from summative evaluation in this project, the impact on health and recovery and its potential cost implications.

The SCRIPT multidisciplinary team has existing expertise in all aspects of robot‐mediated therapy, clinical evaluation and interface design and usability. After their discharge from the hospital a patient can begin using the SCRIPT developed robotic tools at home. SCRIPT systems will be adaptive to the user requirements and provide immediate feedback to a patient on their performance. The feedback will also be provided to an “off-site” health care professional with in‐depth considerations for security and confidentiality, who can remotely monitor progress, making adjustments to the support that the device provides.

We believe that the SCRIPT systems will be beneficial to patient recovery and can assist with improving their quality of life. SCRIPT will reduce hospital and home visits for patients & carers, and therefore have a large impact on reducing hospital costs; improving the quality and standard of care.

The SCRIPT project is partially funded by the European Commission under the 7th Framework Programme. The project activities will last for 36 months.

The Project partners are:


R.U.ROBOTS LIMITED (RUR), United Kingdom
MOOG BV (MOOG), Netherlands

For any further information about project development and implementation, please contact:

Dr.Farshid Amirabdollahian
School of Computer Science
University of Hertfordshire
College Lane
Hatfield Herts AL10 9AB
United Kingdom
Ph: +44-1707286125

Further information can be found at:

See our links section for other media coverage from the press release

Source: Press Release: New Move to Use Robots for Stroke Rehabilitation |

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[Abstract] Ethical Considerations in Providing an Upper Limb Exoskeleton Device for Stroke Patients


The health care system needs to face new and advanced medical technologies that can improve the patients’ quality of life by replacing lost or decreased functions. In stroke patients, the disabilities that follow cerebral lesions may impair the mandatory daily activities of an independent life. These activities are dependent mostly on the patient’s upper limb function so that they can carry out most of the common activities associated with a normal life. Therefore, an upper limb exoskeleton device for stroke patients can contribute a real improvement of quality of their life. The ethical problems that need to be considered are linked to the correct adjustment of the upper limb skills in order to satisfy the patient’s expectations, but within physiological limits. The debate regarding the medical devices dedicated to neurorehabilitation is focused on their ability to be beneficial to the patient’s life, keeping away damages, injustice, and risks.

Source: Ethical Considerations in Providing an Upper Limb Exoskeleton Device for Stroke Patients – Medical Hypotheses

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[Review] iPad Use in Stroke Neuro-Rehabilitation – Full Text PDF


Neuro-rehabilitation services are essential in reducing post-stroke impairments, enhancing independence, and improving recovery in hospital and post-discharge. However these services are therapist-dependent and resource intensive. Patients’ disengagement and boredom in stroke units are common which adversely affect functional and psychological outcomes. Novel techniques such as use of iPads™ are increasingly researched to overcome such challenges.

The aim of this review is to determine the feasibility, effectiveness, acceptability, and barriers to the use of iPads™ in stroke neuro-rehabilitation. Four databases and manual literature search were used to identify published studies using the terms “iPad”, “Stroke”, and “neuro-rehabilitation”. Studies were included in accordance with the review selection criteria. A total of 16 articles were included in the review. The majority of the studies focused on iPads use in speech and language therapy. Although of small scale, the studies highlighted that iPads are feasible, have the potential to improve rehabilitation outcomes, and can improve patient’s social isolation. Patients’ stroke severity and financial limitations are some of the barriers highlighted in this review. This review presents preliminary data supportive for the use of iPad technology in stroke neuro-rehabilitation. However, further research is needed to determine impact on rehabilitation goals acquisition, clinical efficacy, and cost-efficiency.

Download Full Text PDF

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