Performance of Combined Surface and Intramuscular EMG for Classification of Hand Movements

The surface EMG (sEMG) has been used as control source for upper limb prosthetics since decades. Previous studies suggested that intramuscular EMG showed promising results for upper limb prosthetics. This study investigates the strength of combined surface and intramuscular EMG (cEMG) for improved m...

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Vydané v:Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Ročník 2018; s. 5220 - 5223
Hlavní autori: Rehman, Muhammad Zia Ur, Gillani, Syed Omer, Waris, Asim, Jochumsen, Mads, Niazi, Imran Khan, Kamavuako, Ernest Nlandu
Médium: Konferenčný príspevok.. Journal Article
Jazyk:English
Vydavateľské údaje: United States IEEE 01.07.2018
Predmet:
Band-pass filters
Electrodes
Electromyography
Feature extraction
Muscles
ISSN:1557-170X, 2694-0604, 1558-4615, 2694-0604
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Shrnutí:The surface EMG (sEMG) has been used as control source for upper limb prosthetics since decades. Previous studies suggested that intramuscular EMG showed promising results for upper limb prosthetics. This study investigates the strength of combined surface and intramuscular EMG (cEMG) for improved myoelectric control. Five able-bodied subjects and three transradial amputees were evaluated using offline classification error as performance metric. Six surface and intramuscular channels were recorded concurrently from each subject for seven consecutive days and Stacked sparse autoencoders (SSAE) and LDA classifiers were used for classification. As a control source, either sEMG channels were used or combined channels were used with reduced features using PCA. In the within session analysis, cEMG (2.21 ± 1.19%) outperformed the sEMG (4.63 ± 2.07%) for both able-bodied and amputee subjects using SSAE. For between session analysis, cEMG outperformed the sEMG for both able-bodied and amputee subjects with percentage points difference of 7.93. These results imply cEMG can significantly improve the performance of pattern recognition based myoelectric control scheme for amputee subjects too and further improvement can be made by utilizing SSAE which show improved performance as compared to LDA.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 23
ISSN:1557-170X
2694-0604
1558-4615
2694-0604
DOI:10.1109/EMBC.2018.8513480