Clinical Features to Predict the Use of a sEMG Wearable Device (REMO®) for Hand Motor Training of Stroke Patients: A Cross-Sectional Cohort Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants
2.2. The Device
2.3. Test Methods
2.4. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
TBR | Technology-Based Rehabilitation |
sEMG | Surface Electromyography |
CT | Computed Tomography |
MRI | Magnetic Resonance Imaging |
IMU | Inertial Measurement Unit |
CR | Contraction Ratio |
MVC | Maximum Voluntary Contraction |
FMA | Fugl-Meyer Assessment scale |
FMA-UE | Fugl-Meyer Assessment Upper Extremity |
FMA-hand | Fugl-Meyer Assessment Upper Extremity, wrist and hand sub-items |
FMA sensation | Fugl-Meyer Assessment, sensation section |
FMA pain/ROM | Fugl-Meyer Assessment, range of motion and pain section |
RPS | Reaching Performance Scale |
BBT | Box and Blocks Test |
NHPT | Nine Hole Pegboard Test |
MAS | Modified Ashworth Scale |
PecMaj | Pectoralis Major |
BicBra | Biceps Brachii |
FlexCarp | Flexor Carpi muscles |
FlexDigProf | Flexor Digitorum Profundus |
FlexDigSup | Flexor Digitorum Superficialis |
FIM | Functional Independence Measure |
AUC | Area Under the Curve |
RoC | Receiver Operating Characteristic |
CI | confidence interval |
GLM | logistic multivariable regression model |
GLM0 | logistic multivariable regression model, 0 movement |
GLM5 | logistic multivariable regression model, 5 movements |
GLM10 | logistic multivariable regression model, 10 movements |
GLMk | logistic multivariable regression model, k-means output number |
DoF | Degree of Freedom |
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Age | |
Mean Years (SD) | 65.09 (12.14) |
Sex | |
Female/Male, n (%) | 44/73 (38/62%) |
Aphasia | |
Yes/No, n (%) | 37/80 (32/68%) |
Apraxia | |
Yes/No, n (%) | 7/110 (6/94%) |
Lesion Type | |
Ischemic Stroke, n (%) | 77 (66%) |
Hemorrhagic Stroke, n (%) | 40 (34%) |
Affected arm | |
Right/Left, n (%) | 56/61 (48/52%) |
Time from stroke | |
Mean months (SD) | 15.98 (35) |
FMA, Mean (SD) | |
FMA-UE | 30.04 (22.66) |
FMA-hand | 9.94 (9.33) |
FMA sensation | 16.44 (7.99) |
FMA Pain/ROM | 42.40 (5.28) |
RPS | |
Mean (SD) | 16.62 (14.91) |
NHPT | |
Mean (SD) | 0.13 (0.20) |
BBT | |
Mean (SD) | 14.82 (18.97) |
FIM | |
Mean (SD) | 85.95 (24.37) |
MAS, Mean (SD) | |
Total score | 1.92 (2.83) |
PecMaj | 0.29 (0.68) |
BicBra | 0.49 (0.75) |
FlexCarp | 0.56 (0.93) |
FlexDigProf | 0.24 (0.65) |
FlexDigSup | 0.35 (0.69) |
Model | N Movements | Variables | Odds Ratio (CI 95%) | K Value/Total | Se/Sp |
---|---|---|---|---|---|
GLM0 | N > 0 | FMA-UE | 1.53 (1.18–1.98) | ≥10/66 | 0.95/0.82 |
FMA-UE pain/ROM | 1.22 (1.04–1.43) | ≥43/48 | 0.79/0.65 | ||
GLM5 | N ≥ 5 | FMA-UE | 1.65 (1.22–2.22) | ≥18/66 | 1/0.76 |
FlexCarp | 0.45 (0.26–0.92) | <0/4 | 1/0 | ||
GLMk | N ≥ 6 | FMA-UE | 1.52 (1.18–1.97) | ≥18/66 | 1/0.76 |
FlexCarp | 0.51 (0.26–0.98) | <0/4 | 1/0 | ||
GLM10 | N = 10 | FMA-UE | 1.11 (1.07–1.15) | ≥18/66 | 0.90/0.86 |
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Pregnolato, G.; Rimini, D.; Baldan, F.; Maistrello, L.; Salvalaggio, S.; Celadon, N.; Ariano, P.; Pirri, C.F.; Turolla, A. Clinical Features to Predict the Use of a sEMG Wearable Device (REMO®) for Hand Motor Training of Stroke Patients: A Cross-Sectional Cohort Study. Int. J. Environ. Res. Public Health 2023, 20, 5082. https://doi.org/10.3390/ijerph20065082
Pregnolato G, Rimini D, Baldan F, Maistrello L, Salvalaggio S, Celadon N, Ariano P, Pirri CF, Turolla A. Clinical Features to Predict the Use of a sEMG Wearable Device (REMO®) for Hand Motor Training of Stroke Patients: A Cross-Sectional Cohort Study. International Journal of Environmental Research and Public Health. 2023; 20(6):5082. https://doi.org/10.3390/ijerph20065082
Chicago/Turabian StylePregnolato, Giorgia, Daniele Rimini, Francesca Baldan, Lorenza Maistrello, Silvia Salvalaggio, Nicolò Celadon, Paolo Ariano, Candido Fabrizio Pirri, and Andrea Turolla. 2023. "Clinical Features to Predict the Use of a sEMG Wearable Device (REMO®) for Hand Motor Training of Stroke Patients: A Cross-Sectional Cohort Study" International Journal of Environmental Research and Public Health 20, no. 6: 5082. https://doi.org/10.3390/ijerph20065082