An sEMG-Controlled Forearm Bracelet for Assessing and Training Manual Dexterity in Rehabilitation: A Systematic Review
Abstract
:1. Introduction
2. Materials and Methods
2.1. Design
2.2. Search Strategy
2.3. Study Selection
2.4. Participants
2.5. Interventions
2.6. Outcome Measures
2.7. Data Extraction and Analysis
2.8. Assessment of Methodological Quality of the Studies and Risk of Bias
- (a)
- Selection bias: relates to recruiting process and participant allocation. To analyze it, randomization and allocation concealing must be considered.
- (b)
- Performance bias: refers to systematic differences between groups in the care that is provided, or in exposure to factors other than the interventions of interest. To analyze it, blinding procedures must be examined.
- (c)
- Detection bias: refers to systematic differences between groups in how outcomes are determined and may occur during intervention and follow-up. Blinding of outcome assessors must be considered when analyzing it, since it may reduce the risk.
- (d)
- Attrition bias: systematic differences between groups in withdrawals from a study. It occurs when there are withdrawals that lead to incomplete outcome data or when withdrawals in both groups differ significantly.
- (e)
- Reporting bias: refers to systematic differences between reported and unreported findings. This can occur once the study is finished and it is due to the selective report of results, reporting only statistically significant data.
- (f)
- Other biases: occur when reviewers include methodological aspects that are not assessed in the domains described before. They relate mainly to certain trial designs, such as crossover trials.
3. Results
3.1. Sample Characteristics
3.2. Intervention Characteristics
3.3. Outcome Measures
3.4. Accuracy of the System and Effects of the Interventions
3.5. Assessment of Methodological Quality of the Studies and Risk of Bias
4. Discussion
Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Study | Participants (Disease and Sample Size) | Protocol | Data Collection Process | Outcome Measures | Results |
---|---|---|---|---|---|
Melero et al. [4] | Disease: amputation n: 3 | Dance game with visual feedback using Kinect® + MYO Armband® | 10 game trials for each patient | Detection time, reaction time and operating time. O = R + D | D = 0.24 s/R = 0.92 s/O = 1.15 s MD = 2.6 s Operating time (R + MD) = 3.56 s Initial expected operating time = 6 s |
Ryser et al. [11] | Disease: stroke n: 3 | Assessing the accuracy of the MYO® to detect movement intention in order to control a dynamic hand orthosis device | Performing three gestures, each for 60 s | Classification algorithm | Accuracy for five gestures for all samples: 98%, Accuracy for three gestures related to ADL: 94.3% Accuracy in people with stroke: 78–99%. The system is suitable for stroke rehabilitation |
Lyu et al. [18] | Disease: stroke n: 6 healthy + 2 stroke | Visuomotor training task using the MYO Armband® | Accuracy: four gestures, 25 repetitions per gesture, 4 s contraction, 2 s relaxation, 30 s rest Validation: 36 blocks of exercises, four trials per block | sEMG signals captured via MYO® | Accuracy: 99.3% for wrist extension, 82% for radial deviation, 100% for flexion Accuracy in healthy subjects: 92.5% Validation: task performance improves through training Stroke patients: no event was reported regarding calibration, donning, or executing tasks with the device. Lower accuracy than healthy subjects |
Gaetani et al. [19] | Disease: transradial amputation n: 9 (8 healthy + 1 congenital amelia) | performing three different gestures with hand fingers to collect sEMG data with the MYO® and analyze accuracy and response time | 10 s of flexion, 10 s of extension, and 10 s of rest | Learning algorithm, analysis of sEMG signal | Average accuracy of gesture recognition: 90.4% Accuracy in subject with amputation: 93.3% Response time: <1 s The system works also on subjects with small not-trained muscles |
Sattar et al. [20] | Disease: transhumeral amputation n: 18 (15 healthy + 3 amputees) | Creation of BCI to control upper limb prostheses: sEMG (MYO Armband®) + fNIRS The armband acquired the sEMG signals for four-arm motions: elbow extension, elbow flexion, wrist pronation, and wrist supination | Training session: resting period of 3 min to establish a data baseline. Data acquisition: initial 5-sec rest followed by a 20-sec task period | Data processing from sEMG and fNIRS using MATLAB® | The hybrid sEMG and fNIRS system is a feasible approach to improve the CA for transhumeral amputees, improving the control performances of multifunctional upper-limb prostheses. The average accuracy of 94.6% and 74% was achieved for elbow and wrist motions by sEMG for healthy and amputated subjects, respectively Simultaneously, the fNIRS modality showed an average accuracy of 96.9% and 94.5% for hand motions of healthy and amputated subjects |
Castiblanco et al. [21] | Disease: stroke n: 10 (6 healthy + 4 stroke) | Healthy: collection of six sEMG signals (four from right arm and two from left). One trial. Stroke: 12 sEMG signals (eight from impaired side, two from non-impaired). Three trials. All with visual feedback | Maintaining each movement 3–5 s (open-close the hand, flexion-extension of the wrist, spread the fingers, and pinch-grip each finger) | Classification algorithms | Exercises with best performance: opening-closing hand Exercises with worst performance: pinch-grip finger it was possible to identify the hand movements from sEMG signals for subjects who had a motor disability due to stroke with a correct classification rate of 85% |
Study | Participants (Disease and Sample Size) | Intervention or Protocol | Dosage | Outcome Measures | Results |
---|---|---|---|---|---|
Esfahlani et al. [7] | Disease: stroke n: 20 | 3D games controlled with Kinect® and MYO® | 8 weeks 1 h/day, (days per week not specified) | EQ (Rasch Analysis), MAS, angular velocity, acceleration, ROM | Flow, presence, and absorption EQ: participants enjoyed the sessions the activities covered a good ROM for the upper body Suggest audio feedback |
Esfahlani et al. [9] | Disease: stroke, MA and TBI n: 23 (10 healthy CG; 2 stroke, 2 TBI and 9 MA IG) | Serious game controlled by Kinect® + MYO® + pedal | 45-minute sessions, no further information | ROM response time, electromyographic data, velocity, orientation, and inertial information | Improvement in performance reflected in response time and ROM High interest and engagement The combination of MYO® and Kinect® increase the accuracy to detect gestures |
Esfahlani et al. [10] | Disease: MS n: 52 (40 MS IG; 12 healthy CG) | IG: video games using Kinect + MYO + Pedal GC: not specified | 10 weeks 5 days/week 1 h/day | MAS, ROM | Statistically significant differences in performance and ROM. High interest and engagement |
MacIntosh et al. [22] | Disease: CP n: 19 | Video game controlled by completing therapeutic gestures detected via electromyography and inertial sensors on the forearm via the MYO® and custom software | 4 weeks 17 min/day | AHA, BBT, wrist extension, grip strength, COPM, SEAS | Moderate improvements in active writs extension, grip strength, COPM and BBT, small improvement in AHA Positive results in SEAS No adverse effects |
Tool item | Melero et al. [4] | Esfahlani et al. [7] | Esfahlani et al. [9] | Esfahlani et al. [10] | Ryser et al. [11] | Lyu et al. [18] | Gaetani et al. [19] | Sattar et al. [20] | Castiblanco et al. [21] | MacIntosh et al. [22] | |
---|---|---|---|---|---|---|---|---|---|---|---|
Methodological analysis | 1 | VG | F | F | F | F | VG | F | VG | VG | VG |
2 | NS | B | B | NS | B | NS | B | F | B | G | |
3 | NS | B | B | F | B | NS | B | F | F | G | |
4 | NS | B | B | G | B | B | B | B | B | F | |
5 | NS | NS | B | NS | B | NS | B | B | B | G | |
6 | B | NS | NS | NS | B | G | F | NS | F | VG | |
7 | NA | NA | B | G | NA | F | NA | B | F | G | |
8 | NA | NA | F | B | NA | B | NA | G | F | G | |
9 | NA | NA | G | G | NA | B | NA | G | B | G | |
10 | NA | NA | NS | NS | NA | F | NA | NS | NS | G | |
11 | G | G | F | G | F | F | F | F | F | VG | |
12 | F | G | B | F | F | F | NS | F | F | VG | |
13 | NS | G | B | F | B | NS | G | F | NS | VG | |
14 | B | F | F | F | F | F | B | F | F | G | |
15 | F | B | VG | F | NS | F | B | B | G | F | |
16 | F | F | G | G | NS | G | NS | B | G | F | |
17 | G | NS | NS | NS | NS | NS | NS | B | NS | NS | |
18 | F | NS | NS | NS | NS | F | G | B | NS | NS | |
19 | VG | B | F | F | F | F | F | G | G | G | |
20 | F | F | G | G | G | G | F | G | G | VG | |
21 | F | B | F | G | F | F | B | G | G | VG | |
22 | NA | B | VG | G | B | F | G | NS | F | G | |
23 | G | F | G | G | VG | G | G | F | NS | G | |
24 | G | F | G | VG | VG | G | B | F | NS | G | |
25 | B | B | B | B | B | B | B | B | B | F | |
26 | NS | B | F | B | F | F | B | B | NS | B | |
27 | VG | VG | VG | NS | B | NS | F | NS | F | F | |
28 | NS | G | NS | G | NS | NS | NS | NS | NS | VG | |
29 | NS | NS | NS | NS | NS | NS | NS | NS | NS | VG | |
30 | NS | NS | NS | NS | NS | NS | NS | NS | NS | VG | |
31 | NS | NS | NS | NS | NS | NS | NS | NS | NS | NS | |
Internal validity | LOW | LOW | LOW | MEDIUM | LOW | MEDIUM | LOW | LOW | MEDIUM | HIGH | |
External validity | LOW | LOW | LOW | LOW | LOW | LOW | LOW | LOW | LOW | LOW | |
Overall quality | LOW | LOW | LOW | MEDIUM | LOW | MEDIUM | LOW | LOW | MEDIUM | HIGH |
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Share and Cite
Marcos-Antón, S.; Gor-García-Fogeda, M.D.; Cano-de-la-Cuerda, R. An sEMG-Controlled Forearm Bracelet for Assessing and Training Manual Dexterity in Rehabilitation: A Systematic Review. J. Clin. Med. 2022, 11, 3119. https://doi.org/10.3390/jcm11113119
Marcos-Antón S, Gor-García-Fogeda MD, Cano-de-la-Cuerda R. An sEMG-Controlled Forearm Bracelet for Assessing and Training Manual Dexterity in Rehabilitation: A Systematic Review. Journal of Clinical Medicine. 2022; 11(11):3119. https://doi.org/10.3390/jcm11113119
Chicago/Turabian StyleMarcos-Antón, Selena, María Dolores Gor-García-Fogeda, and Roberto Cano-de-la-Cuerda. 2022. "An sEMG-Controlled Forearm Bracelet for Assessing and Training Manual Dexterity in Rehabilitation: A Systematic Review" Journal of Clinical Medicine 11, no. 11: 3119. https://doi.org/10.3390/jcm11113119