scholarly journals Development of the Home based Virtual Rehabilitation System (HoVRS) to Remotely Deliver an Intense and Customized Upper Extremity Training

2020 ◽  
Author(s):  
Qinyin Qiu ◽  
Amanda Cronce ◽  
Jigna Patel ◽  
Gerard G Fluet ◽  
Ashley Mont ◽  
...  
Keyword(s):  
Hand Function ◽  
Chronic Stroke ◽  
Hand Rehabilitation ◽  
Kinematic Data ◽  
Virtual Rehabilitation ◽  
Home Based ◽  
Rehabilitation System ◽  
Kinematic Measures ◽  
And Training ◽  
Training Protocol

Abstract Background: After stroke, sustained hand rehabilitation training is required for continuous improvement and maintenance of distal function. Methods: In this paper, we present a system designed and implemented in our lab: the Home based Virtual Rehabilitation System (HoVRS). Fifteen subjects with chronic stroke were recruited to test the feasibility of the system as well as to refine the design and training protocol to prepare for a future efficacy study. HoVRS was placed in subjects’ homes, and subjects were asked to use the system at least 15 minutes every weekday for 3 months (12 weeks) with limited technical support and remote clinical monitoring. Results: All patients completed the study without any adverse events. Subjects on average spent 13.5 hours using the system. Clinical and kinematic data were collected pre and post study. The whole group improved on the Fugl-Meyer (FM) assessment and on six kinematic measurements. In addition, a combination of these kinematic measures was able to predict a substantial portion of subjects’ FM scores. Conclusion: The outcomes of this pilot study warrant further investigation of the system’s ability to promote recovery of hand function in subacute and chronic stroke.

scholarly journals Development of the Home based Virtual Rehabilitation System (HoVRS) to remotely deliver an intense and customized upper extremity training

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Qinyin Qiu ◽  
Amanda Cronce ◽  
Jigna Patel ◽  
Gerard G. Fluet ◽  
Ashley J. Mont ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Chronic Stroke ◽  
Hand Rehabilitation ◽  
Kinematic Data ◽  
Virtual Rehabilitation ◽  
Home Based ◽  
Rehabilitation System ◽  
Kinematic Measures ◽  
And Training ◽  
Training Protocol

Abstract Background After stroke, sustained hand rehabilitation training is required for continuous improvement and maintenance of distal function. Methods In this paper, we present a system designed and implemented in our lab: the Home based Virtual Rehabilitation System (HoVRS). Fifteen subjects with chronic stroke were recruited to test the feasibility of the system as well as to refine the design and training protocol to prepare for a future efficacy study. HoVRS was placed in subjects’ homes, and subjects were asked to use the system at least 15 min every weekday for 3 months (12 weeks) with limited technical support and remote clinical monitoring. Results All subjects completed the study without any adverse events. Subjects on average spent 13.5 h using the system. Clinical and kinematic data were collected pre and post study in the subject’s home. Subjects demonstrated a mean increase of 5.2 (SEM = 0.69) on the Upper Extremity Fugl-Meyer Assessment (UEFMA). They also demonstrated improvements in six measurements of hand kinematics. In addition, a combination of these kinematic measures was able to predict a substantial portion of the variability in the subjects’ UEFMA score. Conclusion Persons with chronic stroke were able to use the system safely and productively with minimal supervision resulting in measurable improvements in upper extremity function.

scholarly journals Development of the Home based Virtual Rehabilitation System (HoVRS) to remotely deliver an intense and customized upper extremity training

2020 ◽  
Author(s):  
Qinyin Qiu ◽  
Amanda Cronce ◽  
Jigna Patel ◽  
Gerard G Fluet ◽  
Ashley Mont ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Chronic Stroke ◽  
Hand Rehabilitation ◽  
Kinematic Data ◽  
Virtual Rehabilitation ◽  
Home Based ◽  
Rehabilitation System ◽  
Kinematic Measures ◽  
And Training ◽  
Training Protocol

Abstract Background: After stroke, sustained hand rehabilitation training is required for continuous improvement and maintenance of distal function. Methods: In this paper, we present a system designed and implemented in our lab: the Home based Virtual Rehabilitation System (HoVRS). Fifteen subjects with chronic stroke were recruited to test the feasibility of the system as well as to refine the design and training protocol to prepare for a future efficacy study. HoVRS was placed in subjects’ homes, and subjects were asked to use the system at least 15 minutes every weekday for 3 months (12 weeks) with limited technical support and remote clinical monitoring. Results: All subjects completed the study without any adverse events. Subjects on average spent 13.5 hours using the system. Clinical and kinematic data were collected pre and post study in the subject’s home. Subjects demonstrated a mean increase of 5.2 (SEM=0.69) on the Upper Extremity Fugl-Meyer Assessment (UEFMA). They also demonstrated improvements in six measurements of hand kinematics. In addition, a combination of these kinematic measures was able to predict a substantial portion of the variability in the subjects’ UEFMA score. Conclusion: Persons with chronic stroke were able to use the system safely and productively with minimal supervision resulting in measurable improvements in upper extremity function.

scholarly journals Virtual Rehabilitation of the Paretic Hand and Arm in Persons With Stroke: Translation From Laboratory to Rehabilitation Centers and the Patient's Home

2021 ◽  
Vol 12 ◽  
Author(s):  
Gerard Fluet ◽  
Qinyin Qiu ◽  
Jigna Patel ◽  
Ashley Mont ◽  
Amanda Cronce ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Hand Function ◽  
Treatment Modalities ◽  
Virtual Rehabilitation ◽  
Rehabilitation Centers ◽  
Home Based ◽  
Definitive Solution ◽  
And Training ◽  
Upper Extremity Movement ◽  
Physiological Heterogeneity

The anatomical and physiological heterogeneity of strokes and persons with stroke, along with the complexity of normal upper extremity movement make the possibility that any single treatment approach will become the definitive solution for all persons with upper extremity hemiparesis due to stroke unlikely. This situation and the non-inferiority level outcomes identified by many studies of virtual rehabilitation are considered by some to indicate that it is time to consider other treatment modalities. Our group, among others, has endeavored to build on the initial positive outcomes in studies of virtual rehabilitation by identifying patient populations, treatment settings and training schedules that will best leverage virtual rehabilitation's strengths. We feel that data generated by our lab and others suggest that (1) persons with stroke may adapt to virtual rehabilitation of hand function differently based on their level of impairment and stage of recovery and (2) that less expensive, more accessible home based equipment seems to be an effective alternative to clinic based treatment that justifies continued optimism and study.

Abstract WP205: Home-Based Virtual Reality Therapy for Hand Recovery After Stroke

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Adam MacLellan ◽  
Catherine Legault ◽  
Alay Parikh ◽  
Leonel Lugo ◽  
Stephanie Kemp ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Upper Extremity ◽  
Large Scale ◽  
Controlled Trial ◽  
Hand Function ◽  
Chronic Stroke ◽  
Stroke Survivors ◽  
Hand Rehabilitation ◽  
Stroke Patients ◽  
Home Based

Background: Stroke is the leading cause of disability worldwide, with many stroke survivors having persistent upper limb functional impairment. Aside from therapist-directed rehabilitation, few efficacious recovery tools are available for use by stroke survivors in their own home. Game-based virtual reality systems have already shown promising results in therapist-supervised settings and may be suitable for home-based use. Objective: We aimed to assess the feasibility of unsupervised home-based use of a virtual reality device for hand rehabilitation in stroke survivors. Methodology: Twenty subacute/chronic stroke patients with upper extremity impairment were enrolled in this prospective single-arm study. Participants were instructed to use the Neofect Smart Glove 5 days per week for 8 weeks, in single sessions of 50 minutes or two 25-minute sessions daily. We measured (1) compliance to prescribed rehabilitation dose, (2) patient impression of the intervention, and (3) efficacy measures including the upper extremity Fugl-Meyer (UE-FM), the Jebsen-Taylor hand function test (JTHFT) and the Stroke Impact Scale (SIS). Results: Seven subjects (35%) met target compliance of 40 days use, and 6 subjects (30%) used the device for 20-39 days; there were no age or gender differences in use. Subjective patient experience was favorable, with ninety percent of subjects reporting satisfaction with their overall experience, and 80% reporting perceived improvement in hand function (figure 1). There was a mean improvement of 26.6±48.8 seconds in the JTHFT ( p =0.03) and 16.1±15.3 points in the domain of the SIS that assesses hand function ( p <0.01). There was a trend towards improvement in the UE-FM (2.2±5.5 points, p =0.10). Conclusions: A novel virtual reality gaming device is suitable for unsupervised use in stroke patients and may improve hand/arm function in subacute/chronic stroke patients. A large-scale randomized controlled trial is needed to confirm these results.

scholarly journals Development and Clinical Evaluation of a Web-Based Upper Limb Home Rehabilitation System Using a Smartwatch and Machine Learning Model for Chronic Stroke Survivors: Prospective Comparative Study (Preprint)

2019 ◽  
Author(s):  
Sang Hoon Chae ◽  
Yushin Kim ◽  
Kyoung-Soub Lee ◽  
Hyung-Soon Park
Keyword(s):  
Machine Learning ◽  
Home Care ◽  
Comparative Study ◽  
Internal Rotation ◽  
Chronic Stroke ◽  
Control Group ◽  
Stroke Survivors ◽  
Home Based ◽  
Rehabilitation System ◽  
Prospective Comparative Study

BACKGROUND Recent advancements in wearable sensor technology have shown the feasibility of remote physical therapy at home. In particular, the current COVID-19 pandemic has revealed the need and opportunity of internet-based wearable technology in future health care systems. Previous research has shown the feasibility of human activity recognition technologies for monitoring rehabilitation activities in home environments; however, few comprehensive studies ranging from development to clinical evaluation exist. OBJECTIVE This study aimed to (1) develop a home-based rehabilitation (HBR) system that can recognize and record the type and frequency of rehabilitation exercises conducted by the user using a smartwatch and smartphone app equipped with a machine learning (ML) algorithm and (2) evaluate the efficacy of the home-based rehabilitation system through a prospective comparative study with chronic stroke survivors. METHODS The HBR system involves an off-the-shelf smartwatch, a smartphone, and custom-developed apps. A convolutional neural network was used to train the ML algorithm for detecting home exercises. To determine the most accurate way for detecting the type of home exercise, we compared accuracy results with the data sets of personal or total data and accelerometer, gyroscope, or accelerometer combined with gyroscope data. From March 2018 to February 2019, we conducted a clinical study with two groups of stroke survivors. In total, 17 and 6 participants were enrolled for statistical analysis in the HBR group and control group, respectively. To measure clinical outcomes, we performed the Wolf Motor Function Test (WMFT), Fugl-Meyer Assessment of Upper Extremity, grip power test, Beck Depression Inventory, and range of motion (ROM) assessment of the shoulder joint at 0, 6, and 12 months, and at a follow-up assessment 6 weeks after retrieving the HBR system. RESULTS The ML model created with personal data involving accelerometer combined with gyroscope data (5590/5601, 99.80%) was the most accurate compared with accelerometer (5496/5601, 98.13%) or gyroscope data (5381/5601, 96.07%). In the comparative study, the drop-out rates in the control and HBR groups were 40% (4/10) and 22% (5/22) at 12 weeks and 100% (10/10) and 45% (10/22) at 18 weeks, respectively. The HBR group (n=17) showed a significant improvement in the mean WMFT score (<i>P</i>=.02) and ROM of flexion (<i>P</i>=.004) and internal rotation (<i>P</i>=.001). The control group (n=6) showed a significant change only in shoulder internal rotation (<i>P</i>=.03). CONCLUSIONS This study found that a home care system using a commercial smartwatch and ML model can facilitate participation in home training and improve the functional score of the WMFT and shoulder ROM of flexion and internal rotation in the treatment of patients with chronic stroke. This strategy can possibly be a cost-effective tool for the home care treatment of stroke survivors in the future. CLINICALTRIAL Clinical Research Information Service KCT0004818; https://tinyurl.com/y92w978t

Pneumatic Hand Rehabilitation Device

2011 ◽  
Author(s):  
Robert P. Gagliard ◽  
Robert Fregeolle ◽  
Khalid M. Sharaf ◽  
Mansour Zenouzi ◽  
Douglas E. Dow
Keyword(s):  
Physical Therapy ◽  
Hand Function ◽  
Insurance Coverage ◽  
Air Pressure ◽  
Hand Rehabilitation ◽  
Hand Therapy ◽  
Widespread Application ◽  
Home Based ◽  
Home Based Therapy ◽  
Alternative Designs

A prototype of a pneumatic device for rehabilitation of the hand was designed, built and tested. Progressive impairment of hand function may result from a prolonged condition of hemiparesis, such as resulting from stroke. Reduced daily use of the affected limb, spasticity and contracture contribute to progressive impairment. Physical therapy attenuates the impairment in many patients, but regular sessions of physical therapy are difficult to maintain due to the associated costs, limited insurance coverage, and necessity of being at the clinic for each session. Systems or devices suitable for home-based therapy sessions would widen the accessibility of physical therapy to more patients. However, reported therapeutic systems appear to be expensive, heavy and complicated, thus limiting their suitability for widespread application in home settings. Recent reports of pneumatic based hand therapy systems suggest a platform for hand rehabilitation that would be simpler, lighter, less expensive, and have a lower risk of safety concerns. The design utilized in this project has the affected hand encased in a glove apparatus that has an embedded air bladder positioned ventral to each of the five digits on the palmer side of the hand, such that the bladder acts to assist extension of each finger and thumb as internal air pressure increases. Several alternative designs of glove-bladder combinations were designed, fabricated and tested. An electro-pneumatic regulator (SMC Corp. of America, Noblesville, IN) controlled the pressure of air to the bladders from an air compressor. The pneumatic regulator was controlled by a custom designed and assembled microcontroller (Arduino, open source) based control system. The microcontroller controlled solenoids that functioned as valves for the passage of air to the bladders from the pneumatic regulator, one solenoid for each of the 5 bladders in a glove. Tests were done to compare alternative glove-bladder designs. For a bladder corresponding to one digit, the relations between air pressure and the resulting torque were explored using a system of weights. Moreover, for constant pressure levels, the relations between angle of a digit and torque were explored. The pneumatic hand rehabilitation system developed in this project shows promise toward development of pneumatic hand therapy systems that would be suitable for home-based therapy.

scholarly journals An Instrumented Glove-Controlled Portable Hand-Exoskeleton for Bilateral Hand Rehabilitation

Biosensors ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 495
Author(s):  
Shih-Hung Yang ◽  
Chia-Lin Koh ◽  
Chun-Hang Hsu ◽  
Po-Chuan Chen ◽  
Jia-Wei Chen ◽  
...  
Keyword(s):  
Daily Living ◽  
Hand Function ◽  
Hand Movement ◽  
Clinical Settings ◽  
Hand Rehabilitation ◽  
Rehabilitation Programs ◽  
Home Based ◽  
Instrumented Glove ◽  
Flexible Mechanism ◽  
Hand Exoskeleton

Effective bilateral hand training is desired in rehabilitation programs to restore hand function for people with unilateral hemiplegia, so that they can perform daily activities independently. However, owing to limited human resources, the hand function training available in current clinical settings is significantly less than the adequate amount needed to drive optimal neural reorganization. In this study, we designed a lightweight and portable hand exoskeleton with a hand-sensing glove for bilateral hand training and home-based rehabilitation. The hand-sensing glove measures the hand movement of the less-affected hand using a flex sensor. Thereafter, the affected hand is driven by the hand exoskeleton using the measured hand movements. Compared with the existing hand exoskeletons, our hand exoskeleton improves the flexible mechanism for the back of the hand for better wearing experience and the thumb mechanism to make the pinch gesture possible. We designed a virtual reality game to increase the willingness of repeated movement practice for rehabilitation. Our system not only facilitates bilateral hand training but also assists in activities of daily living. This system could be beneficial for patients with hemiplegia for starting correct and sufficient hand function training in the early stages to optimize their recovery.

scholarly journals Development and Clinical Evaluation of a Web-Based Upper Limb Home Rehabilitation System Using a Smartwatch and Machine Learning Model for Chronic Stroke Survivors: Prospective Comparative Study

10.2196/17216 ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. e17216
Author(s):  
Sang Hoon Chae ◽  
Yushin Kim ◽  
Kyoung-Soub Lee ◽  
Hyung-Soon Park
Keyword(s):  
Machine Learning ◽  
Home Care ◽  
Comparative Study ◽  
Internal Rotation ◽  
Chronic Stroke ◽  
Control Group ◽  
Stroke Survivors ◽  
Home Based ◽  
Rehabilitation System ◽  
Prospective Comparative Study

Background Recent advancements in wearable sensor technology have shown the feasibility of remote physical therapy at home. In particular, the current COVID-19 pandemic has revealed the need and opportunity of internet-based wearable technology in future health care systems. Previous research has shown the feasibility of human activity recognition technologies for monitoring rehabilitation activities in home environments; however, few comprehensive studies ranging from development to clinical evaluation exist. Objective This study aimed to (1) develop a home-based rehabilitation (HBR) system that can recognize and record the type and frequency of rehabilitation exercises conducted by the user using a smartwatch and smartphone app equipped with a machine learning (ML) algorithm and (2) evaluate the efficacy of the home-based rehabilitation system through a prospective comparative study with chronic stroke survivors. Methods The HBR system involves an off-the-shelf smartwatch, a smartphone, and custom-developed apps. A convolutional neural network was used to train the ML algorithm for detecting home exercises. To determine the most accurate way for detecting the type of home exercise, we compared accuracy results with the data sets of personal or total data and accelerometer, gyroscope, or accelerometer combined with gyroscope data. From March 2018 to February 2019, we conducted a clinical study with two groups of stroke survivors. In total, 17 and 6 participants were enrolled for statistical analysis in the HBR group and control group, respectively. To measure clinical outcomes, we performed the Wolf Motor Function Test (WMFT), Fugl-Meyer Assessment of Upper Extremity, grip power test, Beck Depression Inventory, and range of motion (ROM) assessment of the shoulder joint at 0, 6, and 12 months, and at a follow-up assessment 6 weeks after retrieving the HBR system. Results The ML model created with personal data involving accelerometer combined with gyroscope data (5590/5601, 99.80%) was the most accurate compared with accelerometer (5496/5601, 98.13%) or gyroscope data (5381/5601, 96.07%). In the comparative study, the drop-out rates in the control and HBR groups were 40% (4/10) and 22% (5/22) at 12 weeks and 100% (10/10) and 45% (10/22) at 18 weeks, respectively. The HBR group (n=17) showed a significant improvement in the mean WMFT score (P=.02) and ROM of flexion (P=.004) and internal rotation (P=.001). The control group (n=6) showed a significant change only in shoulder internal rotation (P=.03). Conclusions This study found that a home care system using a commercial smartwatch and ML model can facilitate participation in home training and improve the functional score of the WMFT and shoulder ROM of flexion and internal rotation in the treatment of patients with chronic stroke. This strategy can possibly be a cost-effective tool for the home care treatment of stroke survivors in the future. Trial Registration Clinical Research Information Service KCT0004818; https://tinyurl.com/y92w978t

Effects of training with a passive hand orthosis and games at home in chronic stroke: a pilot randomised controlled trial

2016 ◽  
Vol 31 (2) ◽  
pp. 207-216 ◽  
Author(s):  
Sharon M Nijenhuis ◽  
Gerdienke B Prange-Lasonder ◽  
Arno HA Stienen ◽  
Johan S Rietman ◽  
Jaap H Buurke
Keyword(s):  
Randomised Controlled Trial ◽  
Controlled Trial ◽  
Hand Function ◽  
User Acceptance ◽  
Chronic Stroke ◽  
Control Group ◽  
Home Based ◽  
Randomised Controlled ◽  
Clinical Changes ◽  
At Home

Objectives: To compare user acceptance and arm and hand function changes after technology-supported training at home with conventional exercises in chronic stroke. Secondly, to investigate the relation between training duration and clinical changes. Design: A randomised controlled trial. Setting: Training at home, evaluation at research institute. Subjects: Twenty chronic stroke patients with severely to mildly impaired arm and hand function. Interventions: Participants were randomly assigned to six weeks (30 minutes per day, six days a week) of self-administered home-based arm and hand training using either a passive dynamic wrist and hand orthosis combined with computerised gaming exercises (experimental group) or prescribed conventional exercises from an exercise book (control group). Main measures: Main outcome measures are the training duration for user acceptance and the Action Research Arm Test for arm and hand function. Secondary outcomes are the Intrinsic Motivation Inventory, Fugl-Meyer assessment, Motor Activity Log, Stroke Impact Scale and grip strength. Results: The control group reported a higher training duration (189 versus 118 minutes per week, P = 0.025). Perceived motivation was positive and equal between groups ( P = 0.935). No differences in clinical outcomes over training between groups were found (P ⩾ 0.165). Changes in Box and Block Test correlated positively with training duration ( P = 0.001). Conclusions: Both interventions were accepted. An additional benefit of technology-supported arm and hand training over conventional arm and hand exercises at home was not demonstrated. Training duration in itself is a major contributor to arm and hand function improvements.

Individual finger synchronized robot-assisted hand rehabilitation in subacute to chronic stroke: a prospective randomized clinical trial of efficacy

2012 ◽  
Vol 26 (8) ◽  
pp. 696-704 ◽  
Author(s):  
Chang Ho Hwang ◽  
Jin Wan Seong ◽  
Dae-Sik Son
Keyword(s):  
Clinical Trial ◽  
Hand Function ◽  
Intervention Group ◽  
Chronic Stroke ◽  
Sensory Loss ◽  
Hand Rehabilitation ◽  
Stroke Patients ◽  
Robot Assisted ◽  
Individual Finger ◽  
Taylor Test

Objective: To evaluate individual finger synchronized robot-assisted hand rehabilitation in stroke patients. Design: Prospective parallel group randomized controlled clinical trial. Subjects: The study recruited patients who were ≥18 years old, more than three months post stroke, showed limited index finger movement and had weakened and impaired hand function. Patients with severe sensory loss, spasticity, apraxia, aphasia, disabling hand disease, impaired consciousness or depression were excluded. Interventions: Patients received either four weeks (20 sessions) of active robot-assisted intervention (the FTI (full-term intervention) group, 9 patients) or two weeks (10 sessions) of early passive therapy followed by two weeks (10 sessions) of active robot-assisted intervention (the HTI (half-term intervention) group, 8 patients). Patients underwent arm function assessments prior to therapy (baseline), and at 2, 4 and 8 weeks after starting therapy. Results: Compared to baseline, both the FTI and HTI groups showed improved results for the Jebsen Taylor test, the wrist and hand subportion of the Fugl-Meyer arm motor scale, active movement of the 2nd metacarpophalangeal joint, grasping, and pinching power ( P < 0.05 for all) at each time point (2, 4 and 8 weeks), with a greater degree of improvement for the FTI compared to the HTI group ( P < 0.05); for example, in Jebsen Taylor test (65.9 ± 36.5 vs. 46.4 ± 37.4) and wrist and hand subportion of the Fugl-Meyer arm motor scale (4.3 ± 1.9 vs. 3.4 ± 2.5) after eight weeks. Conclusions: A four-week rehabilitation using a novel robot that provides individual finger synchronization resulted in a dose-dependent improvement in hand function in subacute to chronic stroke patients.

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