Posts Tagged wearable

[Abstract] Wearable Hand Exoskeleton Systems for Virtual Reality and Rehabilitation

Abstract

The aim is to overcome the limitations of conventional systems in terms of both wearability and portability. As the hand receives diverse physical information and manipulates different type of objects, conventional systems contain many sensors and actuators, and are both large and heavy. Thus, hand exoskeleton systems exhibiting high wearability and portability while measuring finger motions and delivering forces would be highly valuable. For VR hand exoskeleton systems, a wearable hand exoskeleton system with force-controllable actuator modules was developed to ensure free finger motion and force mode control. The linkage structure ensures motion with three degrees of freedom (DOF) and provides a large fingertip workspace; the finger postures assumed when interacting with objects are appropriate. A series elastic actuator (SEA) with an actuator and an elastic element was used to fabricate compact actuator modules. Actuator friction was eliminated using a friction compensation algorithm. A proportional differential (PD) controller, optimized by a linear quadratic (LQ) method featuring a disturbance observer (DOB), was used to ensure accurate force mode control even during motion. The force control performance of the actuator module was verified in force generation experiments including stationary and arbitrary end-effector motions. The forces applied to the fingertips, which are the principal parts of the hand that interact with objects, were kinematically analyzed via both simulations and experiments. To overcome the weak point of previous system, a wearable hand exoskeleton system featuring finger motion measurement and force feedback was developed and evaluated in terms of user experience (UX). The finger structures for the thumb, index, and middle fingers, which play important roles when grasping objects, satisfy full range of motion (ROM). The system estimates all joint angles of these three digits using a dedicated algorithm; measurement accuracy was experimentally evaluated to verify system performance. The UX performance was evaluated by 15 undergraduate students who completed questionnaires assessing usability and utilitarian value following trials conducted in the laboratory. All subjects were highly satisfied with both usability and the utilitarian nature of the system, not only because control and feedback were intuitive but also because performance was accurate. For rehabilitation, a highly portable exoskeleton featuring flexion/extension finger exercises was developed. The exoskeleton features two four-bar linkages reflecting the natural metacarpophalangeal (MCP) and proximal phalangeal (PIP) joint angles. During optimization, the design parameters were adjusted to reflect normal finger trajectories, which vary by finger length and finger joint ROM. To allow for passive physical impedance, a spring was installed to generate the forces that guided the fingers. The moments transmitted to the MCP and PIP joints were estimated via finite element method (FEM) analysis and the cross-sectional areas of the links were manually designed by reference to the expected joint moments. Finger motion and force distribution experiments verified that the system guided the fingers effectively, allowed for the desired finger motions, and distributed the required moments to the joints (as revealed by FEM analysis).; This thesis reports the development of hand exoskeleton systems, for use in virtual reality (VR) environments and for hand rehabilitation

via ScholarWorks: Wearable Hand Exoskeleton Systems for Virtual Reality and Rehabilitation

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[WEB SITE] Therapeutic Shoe is Helping Stroke Patients Relearn How to Walk

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The iStride device is designed to be strapped over the shoe of the stroke patient's good leg and generates a backwards motion, exaggerating the existing step, making it harder to walk while wearing the shoe. The awkward movement strengthens the stroke-impacted leg, allowing gait to become more symmetrical once the shoe is removed. (Photo courtesy of University of South Florida)

A therapeutic shoe engineered to help improve stroke recovery is proving successful and is expected to hit the market by the end of the year, researchers from University of South Florida suggest.

Results from the recently completed clinical trials on the US patented and licensed iStride Device, formerly the Gait Enhancing Mobile Shoe (GEMS), were published recently in the Journal of NeuroEngineering and Rehabilitation.

Gait asymmetry as the result of a stroke is associated with poor balance, a major cause of degenerative issues that make individuals more susceptible to falls and injuries.

The iStride device is designed to be strapped over the shoe of the stroke patient’s good leg and generate a backwards motion, exaggerating the existing step, making it harder to walk while wearing the shoe. The awkward movement strengthens the stroke-impacted leg, allowing gait to become more symmetrical once the shoe is removed. The impaired foot wears a matching shoe that remains stationary, a media release from University of South Florida (USF Innovation) notes.

“The backward motion of the shoe is generated passively by redirecting the wearer’s downward force during stance phase. Since the motion is generated by the wearer’s force, the person is in control, which allows easier adaptation to the motion,” developer Kyle Reed, PhD, associate professor of mechanical engineering at the University of South Florida, says in the release.

“Unlike many of the existing gait rehabilitation devices, this device is passive, portable, wearable and does not require any external energy.”

The trial included six people between ages 57 and 74 who suffered a cerebral stroke at least 1 year prior to the study. They all had asymmetry large enough to impact their walking ability. Each received 12, 30-minute gait training sessions for 4 weeks. With guidance from a physical therapist, the patients’ gait symmetry and functional walking were measured using the ProtoKinetics Zeno Walkway system.

All participants improved their gait’s symmetry and speed. That includes how long it takes to stand up from a sitting position and walk, as well as how long it takes to walk to a specific location and distance traveled within 6 minutes. Four improved the percentage of time spent in a gait cycle with both feet simultaneously planted on the ground, known as double limb support.

As far as the other two that didn’t improve, one started the study with severe impairment, while the other was highly functional. It’s also important to note that three participants joined the study limited to walking in their homes. Following the trial, two of them could successfully navigate public venues, the release explains.

Reed compared his method to a previous study conducted on split-belt treadmill training (SBT), which is commonly used by physical therapists to help stroke patients improve their gait. The equipment allows the legs to move at different speeds, forcing the patient to compensate in order to remain on the treadmill. While the SBT improves certain aspects of gait, unlike the iStride, it doesn’t strengthen double limb support.

That research concluded only about 60% of patients trained on the SBT corrected their gait when walking in a normal environment. Walking is context dependent where visual cues impact how quickly one tries to move, and in what direction. The iStride allows patients to adjust accordingly. Movement on a treadmill is predictable and provides individuals a static scene.

Since patients are often disappointed in their progress after being discharged from rehabilitation, the iStride’s portability allows patients to relearn to walk in a typical setting more often and for a longer duration.

Reed is now working on a home-based clinical trial with 21 participants and expects to publish results within the next year. He recently received a Fulbright scholarship to conduct research at Hong Kong Polytechnic University. He’s working in the rehabilitation sciences and biomedical engineering departments throughout the 2019-2020 academic year, per the release.

[Source(s): University of South Florida (USF Innovation), EurekAlert]

 

via Therapeutic Shoe is Helping Stroke Patients Relearn How to Walk – Rehab Managment

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[ARTICLE] Home rehabilitation supported by a wearable soft-robotic device for improving hand function in older adults: A pilot randomized controlled trial – Full Text

Abstract

Background

New developments, based on the concept of wearable soft-robotic devices, make it possible to support impaired hand function during the performance of daily activities and intensive task-specific training. The wearable soft-robotic ironHand glove is such a system that supports grip strength during the performance of daily activities and hand training exercises at home.

Design

This pilot randomized controlled clinical study explored the effect of prolonged use of the assistive ironHand glove during daily activities at home, in comparison to its use as a trainings tool at home, on functional performance of the hand.

Methods

In total, 91 older adults with self-perceived decline of hand function participated in this study. They were randomly assigned to a 4-weeks intervention of either assistive or therapeutic ironHand use, or control group (received no additional exercise or treatment). All participants performed a maximal pinch grip test, Box and Blocks test (BBT), Jebsen-Taylor Hand Function Test (JTHFT) at baseline and after 4-weeks of intervention. Only participants of the assistive and therapeutic group completed the System Usability Scale (SUS) after the intervention period.

Results

Participants of the assistive and therapeutic group reported high scores on the SUS (mean = 73, SEM = 2). The therapeutic group showed improvements in unsupported handgrip strength (mean Δ = 3) and pinch strength (mean Δ = 0.5) after 4 weeks of ironHand use (p≤0.039). Scores on the BBT and JTHFT improved not only after 4 weeks of ironHand use (assistive and therapeutic), but also in the control group. Only handgrip strength improved more in the therapeutic group compared to the assistive and control group. No significant correlations were found between changes in performance and assistive or therapeutic ironHand use (p≥0.062).

Conclusion

This study showed that support of the wearable soft-robotic ironHand system either as assistive device or as training tool may be a promising way to counter functional hand function decline associated with ageing.

 

Introduction

Hand function predominantly determines the quality of performance in activities of daily living (ADL) and work-related functioning. Older adults with age-related loss of muscle mass (i.e. sarcopenia) [1] and/or age-related diseases (e.g. stroke, arthritis) [23] suffer from loss of hand function. As a consequence, they experience functional limitations, which affects independence in performing ADL [35].

An effective intervention for improving hand function of (stroke) patients should consist of several key aspects of motor learning, such as high-intensity and task-specificity in repetitive and functional exercises that are actively initiated by the patient him/herself [67]. In a traditional rehabilitation setting, those kinds of interventions are performed with one-on-one attention from the healthcare professional for each patient. This might become problematic in the near future when the population of older adults with age-related diseases (e.g. stroke, rheumatoid arthritis) with hand function decline will rise, resulting in an increased need for healthcare professionals and a rise of healthcare costs [8]. Therefore, new alternatives to provide intensive therapy for all patients are needed in the future.

New technological developments, such as robot-assisted hand training, have the potential to provide such intensive, repetitive and task-specific therapy. Several reviews [911] already showed positive results on motor function after robot-assisted training of the upper extremity. However, limiting factors of robot-assisted therapy are the need for supervision of a healthcare professional, the high costs of the devices and the limited availability of wearable devices for training at home [12]. Furthermore, it is often not efficient in transferring the trained movements into daily situations [6]. Therefore, the next generation robotic training approaches should pay substantial attention towards home-based rehabilitation and the functional nature of the exercise involved.

A new way of providing functional, intensive and task-specific hand training would involve using new technological innovations that enable support of the affected hand directly during the performance of ADL, based on the concept of a wearable robotic glove [1318]. In this way, the affected hand can be used repeatedly and for prolonged periods of time during functional daily activities. These robotic gloves can use different human-robot interfaces to provide assistance for the affected hand, such as an EMG-controlled glove, a tendon driven glove, a glove controlled by force sensors etc. [1314161819]. All these robotic gloves use soft and flexible materials to make such devices more lightweight and easy to use, accommodating wearable applications. This concept of a wearable soft-robotic glove allows persons with reduced hand function to use their hand(s) during a large variety of functional activities and may even turn performing daily activities into extensive training, independent from the availability of healthcare professionals. This is thought to improve hand function and patient’s independence in performing ADL.

Therefore, an easy to use and wearable soft-robotic glove (ironHand system), supporting grip strength and hand training exercises at home, was developed within the ironHand project [20]. Previous studies have examined feasibility [20] and the orthotic effect of the ironHand system [21]. In a first randomized controlled clinical study, the effect of prolonged use of such an assisting glove during ADL at home on functional performance of the hand was explored, in comparison to its use as a training tool at home.[…]

 

Continue —> Home rehabilitation supported by a wearable soft-robotic device for improving hand function in older adults: A pilot randomized controlled trial

Fig 2.
Overview of the ironHand system with assistive functionality (left panel) and therapeutic functionality (right panel). * Reprinted from Bioservo Technologies under a CC BY license, with permission from Bioservo Technologies, original copyright 2017.
https://doi.org/10.1371/journal.pone.0220544.g002

 

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[ARTICLE] A Wearable Rehabilitation System to Assist Partially Hand Paralyzed Patients in Repetitive Exercises – Full Text PDF

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Abstract

The main purpose of the paper is development, implementation, and testing of a low cost portable system to assist partially paralyzed patients in their hand rehabilitation after strokes or some injures. Rehabilitation includes time consuming and repetitive exercises which are costly and demotivating as well as the requirements of clinic attending and direct supervision of physiotherapist. In this work, the system consists of a graphical user interface (GUI) on a smartphone screen to instruct and motivate the patients to do their exercises by themselves. Through the GUI, the patients are instructed to do a sequence of exercises step by step, and the system measures the electrical activities (electromyographic signals EMG) of the user’s forearm muscles by Myo armband. Depending on database, the system can tell whether the patients have done correct movements or not. If a correct movement is detected, the system will inform the user through the GUI and move to the next exercise. For preliminary results, the system was extensively tested on a healthy person.

References

  • [1]
    Jarrass´e N., Proietti T., Crocher V., Robertson J., Sahbani A., Morel G. and Roby-Brami A. 2014 Robotic exoskeletons: a perspective for the rehabilitation of arm coordination in stroke patients Frontiers in human neuroscience 8

    Google Scholar

  • [2]
    Mulas M., Folgheraiter M. and Gini G. 2005 An emg-controlled exoskeleton for hand rehabilitation Rehabilitation Robotics, 2005. ICORR 2005. 9th International Conference on. IEEE 371-374

    CrossrefGoogle Scholar

  • [3]
    Ho N., Tong K., Hu X., Fung K., Wei X., Rong W. and Susanto E. 2011 An emg-driven exoskeleton hand robotic training device on chronic stroke subjects: task training system for stroke rehabilitation Rehabilitation Robotics (ICORR), 2011 IEEE International Conference on. IEEE 1-5

    Google Scholar

  • [4]
    Stein J., Narendran K., McBean J., Krebs K. and Hughes R. 2007 Electromyography-controlled exoskeletal upper-limb–powered orthosis for exercise training after stroke American journal of physical medicine & rehabilitation 86 255-261

    CrossrefGoogle Scholar

  • [5]
    Bae J.-H., Kim Y.-M. and Moon I. 2012 Wearable hand rehabilitation robot capable of hand function assistance in stroke survivors Biomedical Robotics and Biomechatronics (BioRob), 2012 4th IEEE RAS & EMBS International Conference on. IEEE 1482-1487

    CrossrefGoogle Scholar

  • [6]
    Hasegawa Y., Mikami Y., Watanabe K., Firouzimehr Z. and Sankai Y. 2008 Wearable handling support system for paralyzed patient 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems 741-746 Sept

    CrossrefGoogle Scholar

  • [7]
    Sugar T. G., He J., Koeneman E. J., Koeneman J. B., Herman R., Huang H., Schultz R. S., Herring D. E., Wanberg J., Balasubramanian S., Swenson P. and Ward J. A. 2007 Design and control of rupert: A device for robotic upper extremity repetitive therapy IEEE Transactions on Neural Systems and Rehabilitation Engineering 15 336-346 Sept

    CrossrefGoogle Scholar

  • [8]
    Alamri A., Cha J. and El Saddik A. 2010 Ar-rehab: An augmented reality framework for poststroke-patient rehabilitation IEEE Transactions on Instrumentation and Measurement 59 2554-2563

    CrossrefGoogle Scholar

  • [9]
    Holden M. K. 2005 Virtual environments for motor rehabilitation Cyberpsychology & behavior 8 187-211

    CrossrefGoogle Scholar

  • [10]
    Shusong X. and Xia Z. 2010 Emg-driven computer game for post-stroke rehabilitation 2010 IEEE Conference on Robotics, Automation and Mechatronics 32-36 June

    CrossrefGoogle Scholar

  • [11]
    ThalmicLabs. (2017-08-10) Getting started. [Online]. Available: https://developer.thalmic.com/docs/apireference/platform/gettingstarted.html

    Google Scholar

  • [12]
    Abaid N., Kopman V. and Porfiri M. 2013 An attraction toward engineering careers: The story of a brooklyn outreach program for k-12 students IEEE, Robotics Automation Magazine 20 31-39 June

    CrossrefGoogle Scholar

  • [13]
    Sathiyanarayanan M. and Mulling T. 2015 Map navigation using hand gesture recognition: A case study using myo connector on apple maps Procedia Computer Science 58 50-57 second International Symposium on Computer Vision and the Internet (VisionNet15). [Online]. Available:http://www.sciencedirect.com/science/article/pii/S1877050915021195

    CrossrefGoogle Scholar

  • [14]
    ThalmicLabs. (2017-08-29) Website. [Online]. Available: https://www.myo.com/

    Google Scholar

  • [15]

Fig.1. shows a Myo gestures control armband and a smartphone.

Fig. 3. The main parts of the Myo armband, adapted from [14].

via A Wearable Rehabilitation System to Assist Partially Hand Paralyzed Patients in Repetitive Exercises* – IOPscience

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[WEB PAGE] Wearable robots usher in next generation of mobility therapies – CORDIS

Wearable robots that can anticipate and react to users’ movement in real time could dramatically improve mobility assistance and rehabilitation tools.

© Shutterstock

Wearable robots are programmable body-worn devices, or exoskeletons, that are designed to mechanically interact with the user. Their purpose is to assist or even substitute human motor function for people who have severe difficulty moving or walking.

The BIOMOT project, completed in September 2016, has helped to advance this emerging field by demonstrating that personalised computational models of the human body can effectively be used to control wearable exoskeletons. The project has identified ways of achieving improved flexibility and autonomous performance, which could assist in the use of wearable robots as mobility assistance and rehabilitation tools.

‘An increasing number of researchers in the field of neurorehabilitation are interested in the potential of these robotic technologies for clinical rehabilitation following neurological diseases,’ explains BIOMOT project coordinator Dr. Juan Moreno from the Spanish Council for Scientific Research (CSIC). ‘One reason is that these systems can be optimised to deliver diverse therapeutic interventions at specific points of recuperation or care.’

However, a number of factors have limited the widespread market adoption of wearable robots. Moreno and his team identified a need for wearable equipment to be more compact and lightweight, and better able anticipate and detect the intended movements of the wearer. In addition, robots needed to become more versatile and adaptable in order to aid people in a variety of different situations; walking on uneven ground, for example, or approaching an obstacle.

In order to address these challenges, the project developed robots with real-time adaptability and flexibility by increasing the symbiosis between the robot and the user through dynamic sensorimotor interactions. A hierarchical approach to these interactions was taken, allowing the project team to apply different layers for different purposes. This means in effect that an exoskeleton can be personalised to an individual user.

‘Thanks to this framework, the BIOMOT exoskeleton can rely on mechanical and bioelectric measurements to adapt to a changing user or task condition,’ says Moreno. ‘This leads to improved robotic interventions.’

Following theoretical and practical work, the project team then tested these prototype exoskeletons with volunteers. A key technical challenge was how to combine a robust and open architecture with a novel wearable robotic system that can gather signals from human activity. ‘Nonetheless, we succeeded in investigating for the first time the potential of automatically controlling human-robot interactions in order to enhance user compliance to a motor task,’ says Moreno. ‘Our research with healthy humans showed such positive and promising results that we are keen to continue validation with both stroke and spinal cord injury patients.’

Indeed, Moreno is confident that the success of the project will open up potential new research avenues. For example, the results will help scientists to develop computational models for rehabilitation therapies, and better understand human movement in more detail.

‘In the project we also defined novel techniques to evaluate and benchmark performances of wearable exoskeletons,’ says Moreno. ‘Further innovation projects are planned by consortium members to follow up on this research, and to exploit developments in the field of human motion capture, human-machine interaction and adaptive control.’

For further information, please see:
project website

via Wearable robots usher in next generation of mobility therapies | News | CORDIS | European Commission

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[WEB SITE] Flint Rehab Introduces MiGo Wearable for Stroke Recovery

MiGo

Flint Rehab announces the launch of MiGo, a wearable activity tracker specifically designed for stroke survivors. The device makes its official debut at the 2019 Consumer Electronics Show in Las Vegas.

MiGo is designed to track upper extremity activity — in addition to walking — and is optimized for the movement patterns performed by individuals with stroke. The device is accompanied by a smartphone app that provides motivational support through digital coaching, progressive goal setting, and social networking with other stroke survivors, according to the company in a media release.

“Most wearable fitness trackers are designed to help people get into shape. MiGo is a new type of wearable that helps people regain their independence after a stroke,” says Dr Nizan Friedman, co-founder and CEO of Irvine, Calif-based Flint Rehab, in the release.

“Traditionally, innovation in medical technology has been limited by what insurance companies are willing to cover. As a consumer-level digital health technology, MiGo avoids these constraints, empowering stroke survivors to take their recovery into their own hands.”

A common outcome of stroke is hemiparesis, or impaired movement on one side of the body. One of the leading causes of this lifelong disability is a phenomenon called “learned non-use,” where stroke survivors neglect to use their impaired arm or leg, causing their brain to lose the ability to control those limbs altogether.

MiGo directly addresses the problem of learned non-use by motivating stroke survivors to use their impaired side as much as possible. Using deep-learning algorithms, MiGo accurately tracks how much the wearer is using their impaired side, providing them with an easy-to-understand rep count throughout the day.

MiGo also provides an intelligent activity goal that updates every day based on the wearer’s actual movement ability, ensuring every user stays continuously challenged at the level appropriate for them. Then, the device acts as the wearer’s personal cheerleader, giving them rewards and positive feedback right on their wrist as they work to hit their daily goal, the release explains.

“Suffering a stroke is a traumatic, life-changing event. Many survivors do not have the proper support network to deal with the event, and they may find it difficult to relate with friends and family who don’t understand what they are going through,” states Dan Zondervan, co-founder and vice president of Flint Rehab.

“Using the MiGo app, users can join groups to share their activity data and collaborate with other stroke survivors to achieve group goals. Group members can also share their experiences and offer encouraging support to each other — right in the app,” he adds.

For more information, visit Flint Rehab.

[Source(s0): Flint Rehab, Business Wire]

 

via Flint Rehab Introduces MiGo Wearable for Stroke Recovery – Rehab Managment

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[Abstract + References] eConHand: A Wearable Brain-Computer Interface System for Stroke Rehabilitation

Abstract

Brain-Computer Interface (BCI) combined with assistive robots has been developed as a promising method for stroke rehabilitation. However, most of the current studies are based on complex system setup, expensive and bulky devices. In this work, we designed a wearable Electroencephalography(EEG)-based BCI system for hand function rehabilitation of the stroke. The system consists of a customized EEG cap, a small-sized commercial amplifer and a lightweight hand exoskeleton. In addition, visualized interface was designed for easy use. Six healthy subjects and two stroke patients were recruited to validate the safety and effectiveness of our proposed system. Up to 79.38% averaged online BCI classification accuracy was achieved. This study is a proof of concept, suggesting potential clinical applications in outpatient environments.

2. E. Donchin , K. Spencer and R. Wijesinghe , “The mental prosthesis: assessing the speed of a P300-based brain-computer interface”, IEEE Transactions on Rehabilitation Engineering, vol. 8, no. 2, pp. 174-179, 2000.

3. D. McFarland and J. Wolpaw , “Brain-Computer Interface Operation of Robotic and Prosthetic Devices”, Computer, vol. 41, no. 10, pp. 52-56, 2008.

4. Xiaorong Gao , Dingfeng Xu , Ming Cheng and Shangkai Gao , “A bci-based environmental controller for the motion-disabled”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 11, no. 2, pp. 137-140, 2003.

5. A. Ramos-Murguialday , D. Broetz , M. Rea et al “Brain-machine interface in chronic stroke rehabilitation: A controlled study”, Annals of Neurology, vol. 74, no. 1, pp. 100-108, 2013.

6. F. Pichiorri , G. Morone , M. Petti et al “Brain-computer interface boosts motor imagery practice during stroke recovery”, Annals of Neurology, vol. 77, no. 5, pp. 851-865, 2015.

7. M. A. Cervera , S. R. Soekadar , J. Ushiba et al “Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis”, Annals of Clinical and Translational Neurology, vol. 5, no. 5, pp. 651-663, 2018.

8. K. Ang , K. Chua , K. Phua et al “A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke”, Clinical EEG and Neuroscience, vol. 46, no. 4, pp. 310-320, 2014.

9. N. Bhagat , A. Venkatakrishnan , B. Abibullaev et al “Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors”, Frontiers in Neuroscience, vol. 10, pp. 122, 2016.

10. J. Webb , Z. G. Xiao , K. P. Aschenbrenner , G. Herrnstadt , and C. Menon , “Towards a portable assistive arm exoskeleton for stroke patient rehabilitation controlled through a brain computer interface”, in Biomedical Robotics and Biomechatronics (BioRob), 2012 4th IEEE RAS & EMBS International Conference, pp. 1299-1304, 2012.

11. A. L. Coffey , D. J. Leamy , and T. E. Ward , “A novel BCI-controlled pneumatic glove system for home-based neurorehabilitation”, in Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, pp. 3622-3625, 2014.

12. D. Bundy , L. Souders , K. Baranyai et al “Contralesional Brain-Computer Interface Control of a Powered Exoskeleton for Motor Recovery in Chronic Stroke Survivors”, Stroke, vol. 48, no. 7, pp. 1908-1915, 2017.

13. X. Shu , S. Chen , L. Yao et al “Fast Recognition of BCI-Inefficient Users Using Physiological Features from EEG Signals: A Screening Study of Stroke Patients”, Frontiers in Neuroscience, vol. 12, pp. 93, 2018.

14. A. Delorme , T. Mullen , C. Kothe et al “EEGLAB, SIFT, NFT, BCILAB, and ERICA: New Tools for Advanced EEG Processing”, Computational Intelligence and Neuroscience, vol. 2011, pp. 1-12, 2011.

15. G. Schalk , D. McFarland , T. Hinterberger , N. Birbaumer and J. Wolpaw , “BCI2000: A General-Purpose Brain-Computer Interface (BCI) System”, IEEE Transactions on Biomedical Engineering, vol. 51, no. 6, pp. 1034-1043, 2004.

16. M. H. B. Azhar , A. Casey , and M. Sakel , “A cost-effective BCI assisted technology framework for neurorehabilitation”, The Seventh International Conference on Global Health Challenges, 18th-22nd November, 2018. (In Press)

17. C. M. McCrimmon , M. Wang , L. S. Lopes et al “A small, portable, battery-powered brain-computer interface system for motor rehabilitation”, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2776-2779, 2016.

18. J. Meng , B. Edelman , J. Olsoe et al “A Study of the Effects of Electrode Number and Decoding Algorithm on Online EEG-Based BCI Behavioral Performance”, Frontiers in Neuroscience, vol. 12, pp. 227, 2018.

19. T. Mullen , C. Kothe , Y. Chi et al “Real-time neuroimaging and cognitive monitoring using wearable dry EEG”, IEEE Transactions on Biomedical Engineering, vol. 62, no. 11, pp. 2553-2567, 2015.

 

via eConHand: A Wearable Brain-Computer Interface System for Stroke Rehabilitation – IEEE Conference Publication

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[NEWS] Vibrating Glove Could Help Stroke Patients Improve Hand Function

Many were shocked when “Games of Thrones” actress Emily Clarke recently disclosed in The New Yorker that she suffered from two brain aneurysms in 2011 and 2013, respectively. Owing to her bravery and resilient spirit, her recovery was quick enough to resume normal work life within weeks of the operation.

Clarke, however, belongs to the exclusive 10 percent of survivors who recover completely after experiencing a stroke. On the other hand, 40 percent of stroke patients usually have moderate to severe impairments according to statistics published by Healthline.

Strokes are common in the U.S. as 1 in 19 deaths are caused by this.  American Stroke Association’s datarevealed 795,000 Americans suffer from strokes every year. Of which, 185,000 experience recurrent attacks as reintegrating into society with motor skills intact poses a serious challenge.

Strokes are a leading cause of disability in the U.S. One of the main disabilities stroke survivors deal with is known as apraxia, which is a neurological disorder that prevents swift body movements. Other disabilities include the one-sided paralysis of the body known as hemiplegia and dysphagia, which refers to damage to part of the brain controlling swallowing.

Generally, rehabilitation and therapy help, but the field requires more research and innovation. There are a few scientists trying to come up with more novel methods of therapy using the power of technology. For instance, U.S. Food and Drug Administration (FDA) approved the H200 Wireless Hand Rehabilitation System, which is available to purchase in commercial markets.

It is a wireless device stimulating muscles in the forearm and hand. As of now, this is the only commercially available product for the hand muscles according to this research paper reviewing devices for stroke rehabiliation for the lower limbs. On the contrary, Biomove 3000, Hand Mentor PRO,  mPower 1000 and NeuroMove are other devices developed in the past that are still available to purchase.

There is more hope and promise for survivors losing feeling in their arms as extensive research is in progress. Another new device meant to be worn like a glove was developed as a prototype by researchers in Stanford University and Georgia Tech.

What is the latest prototype?

The innovation was the brainchild of a graduate student from Georgia Tech, Caitlyn Seim. She invented the glove to gently stimulate nerves for several hours a day to improve sensation in the arms and hands. The vibrating glove can be worn during normal day-to-day activities like shopping or listening to music.

Once the prototype was made, Seim showed it to her Stanford University professors to get help with further research and to eventually push the device to clinical testing. Maarten Lansberg, an associate professor of neurology, and Allison Okamura, a professor mechanical engineering at Stanford University, are on board with the project. After the glove showed positive results in pilot studies, the trio received a grant from the prestigious Wu Tsai Neurosciences Institute to expand their research.

Currently, the researchers are in the process of improving the device for more comfort and accessibility before starting clinical tests again.The long-term vision is to build a device capable of helping stroke survivors restore lost function in their arms and hands.

The trio are united by a strong curiosity and passion to help stroke survivors. Lansberg had been treating stroke patients as a medical doctor, and Okamura has done research on touch-based devices with the intention to help such patients.

Seim’s interest stems from building wearable computing devices like virtual goggles and smartwatches, but she now intends to use her expertise to benefit health care and accessibility. She will be joining Stanford as a postdoctoral fellow in the fall, and she’ll continue working on the glove.

 

via Vibrating Glove Could Help Stroke Patients Improve Hand Function

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[WEB SITE] A glove to treat symptoms of stroke

A glove to treat symptoms of stroke

Enter a captionA new glove being developed by Georgia Tech and Stanford researchers aims to treat symptoms of stroke through vibration. Credit: Courtesy Caitlyn Seim

The most obvious sign someone has survived a stroke is usually some trouble speaking or walking. But another challenge may have an even greater impact on someone’s daily life: Often, stroke survivors lose sensation and muscle control in one arm and hand, making it difficult to dress and feed themselves or handle everyday objects such as a toothbrush or door handle.

Now, doctors and engineers at Stanford and Georgia Tech are working on a novel therapy that could help more  survivors regain the ability to control their arms and hands – a vibrating glove that gently stimulates the wearer’s hand for several hours a day.

Caitlyn Seim, a  at Georgia Tech, started the project in the hope that the glove’s stimulation could have some of the same impact as more traditional exercise programs. After developing a prototype, she approached Stanford colleagues Maarten Lansberg, an associate professor of neurology, and Allison Okamura, a professor of mechanical engineering, in order to expand her efforts. With help from a Wu Tsai Neurosciences Institute Neuroscience seed grant, the trio are working to improve on their prototype glove and bring the device closer to clinical testing.

“The concept behind it is that users wear the glove for a few hours each day during normal  – going to the supermarket or reading a book at home,” said Seim. “We are hoping that we can discover something that really helps stroke survivors.”

Reaching for new stroke treatments

Seim, Lansberg and Okamura’s goal is a tall order. Despite some individual success stories, the reality is that most stroke struggle to regain the ability to speak, move around and take good care of themselves.

“Stroke can affect patients in many ways, including causing problems with , gait, vision, speech and cognition,” Lansberg said, yet despite decades of research, “there are essentially no treatments that have been proven to help stroke patients recover these functions.”

It was in that context that all three researchers independently started thinking about what they could do to improve the lives of people who’ve survived strokes. As the  in the bunch, Lansberg had already been treating stroke patients for years and has helped lead the Stanford Stroke Collaborative Action Network, or SCAN, another project of the Wu Tsai Neurosciences Institute. Okamura, meanwhile, has focused much of her research on haptic or touch-based devices, and in the last few years her lab has spent more and more time thinking about how to use those devices to help stroke survivors.

“Rehabilitation engineering provides a unique opportunity for me to work directly with the patients who are affected by our research,” Okamura said. “The potential to translate the kind of technology relatively quickly to a commercial product that can reach a large number of  in need of therapy is also very exciting.”

For her part, Seim’s interest in stroke stems from an interest in wearable computing devices – but rather than build more virtual reality goggles and smartwatches, Seim said she wants to apply wearable computing to the areas of health and accessibility, “areas which have some of the most compelling problems to me,” she said.

Growing a new idea

With that ambition in mind, Seim built a prototype vibrating glove that she hoped would stimulate nerves and improve both sensation and function in stroke survivors’ hands and arms. After collecting some promising initial data, Seim reached out to the Stanford team.

“Stanford has SCAN and StrokeNet, along with a community of interdisciplinary engineering and computing research, so I reached out to Maarten, and he was very supportive,” Seim said.

Now, Seim, Lansberg and Okamura are revising the glove’s design to improve its function and to add elements for comfort and accessibility. Then, they’ll begin a new round of clinical tests at Stanford.

Long term, the hope is to build something that helps  recover some of the functions they have lost in their hands and arms. And if initial tests work out, Lansberg said, it’s possible the same basic idea could be applied to treat other complications associated with stroke.

“The glove is an innovative idea that has shown some promise in pilot studies,” Lansberg said. “If proven beneficial for patients with impaired arm function, it is conceivable that variations of this type of therapy could be developed to treat, for example, patients with impaired gait.”


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[ARTICLE] Fabric Soft Poly-Limbs for Physical Assistance of Daily Living Tasks – Full Text

Abstract

This paper presents the design and development of a highly articulated, continuum, wearable, fabric-based Soft Poly-Limb (fSPL). This fabric soft arm acts as an additional limb that provides the wearer with mobile manipulation assistance through the use of soft actuators made with high-strength inflatable fabrics. In this work, a set of systematic design rules is presented for the creation of highly compliant soft robotic limbs through an understanding of the fabric based components behavior as a function of input pressure. These design rules are generated by investigating a range of parameters through computational finite-element method (FEM) models focusing on the fSPL’s articulation capabilities and payload capacity in 3D space. The theoretical motion and payload outputs of the fSPL and its components are experimentally validated as well as additional evaluations verify its capability to safely carry loads 10.1x its body weight, by wrapping around the object. Finally, we demonstrate how the fully collapsible fSPL can comfortably be stored in a soft-waist belt and interact with the wearer through spatial mobility and preliminary pick-and-place control experiments.

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