Towards Robot-Assisted Post-Stroke Hand Rehabilitation: Fugl-Meyer Gesture Recognition Using sEMG

Background: Overground Robot-Assisted Gait Training (o-RAGT) appears to be a promising stroke rehabilitation in terms of clinical outcomes. The literature on surface ElectroMyoGraphy (sEMG) assessment in o-RAGT is limited. This paper aimed to assess muscle activation patterns with sEMG in subjects subacute post stroke after training with o-RAGT and conventional therapy. Methods: An observational preliminary study was carried out with subjects subacute post stroke who received 15 sessions of o-RAGT (5 sessions/week; 60 min) in combination with conventional therapy. The subjects were assessed with both clinical and instrumental evaluations. Gait kinematics and sEMG data were acquired before (T1) and after (T2) the period of treatment (during ecological gait), and during the first session of o-RAGT (o-RAGT1). An eight-channel wireless sEMG device acquired in sEMG signals. Significant differences in sEMG outcomes were found in the BS of TA between T1 and T2. There were no other significant correlations between the sEMG outcomes and the clinical results between T1 and T2. Conclusions: There were significant functional gains in gait after complex intensive clinical rehabilitation with o-RAGT and conventional therapy. In addition, there was a significant increase in bilateral symmetry of the Tibialis Anterior muscles. At this stage of the signals from the tibialis anterior (TA), gastrocnemius medialis (GM), rectus femoris (RF), and biceps femoris caput longus (BF) muscles of each lower extremity. sEMG data processing extracted the Bilateral Symmetry (BS), the Co-Contraction (CC), and the Root Mean Square (RMS) coefficients. Results: Eight of 22 subjects in the subacute stage post stroke agreed to participate in this sEMG study. This subsample demonstrated a significant improvement in the motricity index of the affected lower limb and functional ambulation. The heterogeneity of the subjects’ characteristics and the small number of subjects was associated with high variability research, functional gait recovery was associated with minimal change in muscle activation patterns.

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Design and development of a skinny bidirectional soft glove for post-stroke hand rehabilitation

2017 Intelligent Systems Conference (IntelliSys) ◽

10.1109/intellisys.2017.8324248 ◽

2017 ◽

Author(s):

Boran Wang ◽

Andrew McDaid ◽

Kean C. Aw ◽

Morteza Biglari-Abhari

Keyword(s):

Hand Rehabilitation ◽

Design And Development ◽

Post Stroke

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Direct Drive Hand Exoskeleton for Robot-assisted Post Stroke Rehabilitation

Acta Polytechnica Hungarica ◽

10.12700/aph.18.5.2021.5.4 ◽

2021 ◽

Vol 18 (5) ◽

pp. 37-54

Author(s):

Márk Ottó Bauer ◽

Máté Benjámin Vizi ◽

Péter Galambos ◽

Tibor Szalay

Keyword(s):

Stroke Rehabilitation ◽

Direct Drive ◽

Robot Assisted ◽

Post Stroke ◽

Hand Exoskeleton

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Design and Manufacture of Data Gloves for Rehabilitation Training and Gesture Recognition Based on Flexible Sensors

Journal of Healthcare Engineering ◽

10.1155/2021/6359403 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Kai Guo ◽

Senhao Zhang ◽

Shasha Zhao ◽

Hongbo Yang

Keyword(s):

Experimental Data ◽

Gesture Recognition ◽

The Self ◽

Hand Rehabilitation ◽

Data Glove ◽

Flexible Sensors ◽

Rehabilitation Training ◽

Flexible Sensor ◽

The Core ◽

Design And Manufacture

This work takes the production and usage scenarios of the data glove as the research object and studies the method of applying the flexible sensor to the data glove. Many studies are also devoted to exploring the transplantation of flexible sensors to data gloves. However, this type of research still lacks the display of specific application scenarios such as gesture recognition or hand rehabilitation training. A small amount of experimental data and theoretical analysis are difficult to promote the development of flexible sensors and flexible data gloves design schemes. Therefore, this study uses the self-made flexible sensor of the research group as the core sensing unit to produce a flexible data glove to monitor the bending changes of the knuckles and then use it for simple gesture recognition and rehabilitation training.

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Exoskeleton for Post-Stroke Hand Rehabilitation

10.14733/cadconfp.2021.251-255 ◽

2021 ◽

Author(s):

Aron Grandi ◽

Arun Karthikeyan ◽

Elimar Junior ◽

Mario Rodriguez

Keyword(s):

Hand Rehabilitation ◽

Post Stroke

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The Design of a Low-Cost Therapy Robot for Hand Rehabilitation of a Post-Stroke Patient

2018 International Conference on Computer Engineering, Network and Intelligent Multimedia (CENIM) ◽

10.1109/cenim.2018.8710833 ◽

2018 ◽

Cited By ~ 3

Author(s):

Khairul Anam ◽

Ahmad Adib Rosyadi ◽

Bambang Sujanarko

Keyword(s):

Stroke Patient ◽

Low Cost ◽

Hand Rehabilitation ◽

Post Stroke

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Applications of Smart Textiles in Post-Stroke Rehabilitation

Sensors ◽

10.3390/s20082370 ◽

2020 ◽

Vol 20 (8) ◽

pp. 2370 ◽

Cited By ~ 1

Author(s):

Ewa Korzeniewska ◽

Andrzej Krawczyk ◽

Józef Mróz ◽

Elżbieta Wyszyńska ◽

Rafał Zawiślak

Keyword(s):

Vapor Deposition ◽

Stroke Rehabilitation ◽

Physical Vapor Deposition ◽

Surface Resistance ◽

Hand Rehabilitation ◽

Post Stroke ◽

Rehabilitation Robots ◽

Hand Muscle ◽

High Flexibility ◽

Resistance Value

Stroke is a disease affecting a large part of our society. According to WHO data, it is the second world’s biggest killer, accounting for near six million deaths in 2016 and it is about 30% of the total number of strokes per year. Other patients affected by such a disease should be rehabilitated as soon as possible. As a result of this phenomenon, paresis may occur. Among the devices available on the market there are many rehabilitation robots, but the method of electrostimulation can be used. The authors focused their attention on electrostimulation and commercially available therapies. Using this method, application to people with large hand muscle contracture is difficult. The authors of the work present a solution dedicated to exactly such people. A solution of textronic sensors manufactured on a textile substrate using the technology of physical vapor deposition is presented in the article. As a result of the conducted research, an electroconductive structure was obtained with a low surface resistance value of 1 Ω/□ and high flexibility. It can alternatively be used in hand rehabilitation for electrostimulation of fingertips. The solution is dedicated to people with high hands spasticity for whom it is impossible to put on a rehabilitation glove.

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