Independent Component Analysis of High-Density Electromyography in Muscle Force Estimation
| Autor: | Didier Staudenmann, Idsart Kingma, D.F. Stegeman, J.H. van Dieen, Andreas Daffertshofer |
|---|---|
| Přispěvatelé: | Kinesiology, Movement Behavior, Faculty of Human Movement Sciences |
| Rok vydání: | 2007 |
| Předmět: |
Adult
Multivariate statistics Speech recognition Biomedical Engineering Electromyography Sensitivity and Specificity Correlation Isometric Contraction medicine Humans Diagnosis Computer-Assisted Muscle Skeletal Muscle force Mathematics Principal Component Analysis medicine.diagnostic_test business.industry Biomechanics Reproducibility of Results Triceps brachii muscle Pattern recognition musculoskeletal system Independent component analysis Neuromuscular development and genetic disorders [UMCN 3.1] body regions Principal component analysis Stress Mechanical Artificial intelligence business Functional Neurogenomics [DCN 2] Algorithms |
| Zdroj: | Staudenmann, D, Daffertshofer, A, Kingma, I, Stegeman, D F & van Dieen, J H 2007, ' Independent component analysis of high-density electromyography in muscle force estimation ', IEEE Transactions on Biomedical Engineering, vol. 54, no. 4, pp. 751-754 . https://doi.org/10.1109/TBME.2006.889202 IEEE Transactions on Biomedical Engineering, 54, 751-4 IEEE Transactions on Biomedical Engineering, 54, 4, pp. 751-4 IEEE Transactions on Biomedical Engineering, 54(4), 751-754. IEEE Computer Society |
| ISSN: | 0018-9294 |
| DOI: | 10.1109/tbme.2006.889202 |
| Popis: | Item does not contain fulltext Accurate force prediction from surface electromyography (EMG) forms an important methodological challenge in biomechanics and kinesiology. In a previous study (Staudenmann et al., 2006), we illustrated force estimates based on analyses lent from multivariate statistics. In particular, we showed the advantages of principal component analysis (PCA) on monopolar high-density EMG (HD-EMG) over conventional electrode configurations. In the present study, we further improve force estimates by exploiting the correlation structure of the HD-EMG via independent component analysis (ICA). HD-EMG from the triceps brachii muscle and the extension force of the elbow were measured in 11 subjects. The root mean square difference (RMSD) and correlation coefficients between predicted and measured force were determined. Relative to using the monopolar EMG data, PCA yielded a 40% reduction in RMSD. ICA yielded a significant further reduction of up to 13% RMSD. Since ICA improved the PCA-based estimates, the independent structure of EMG signals appears to contain relevant additional information for the prediction of muscle force from surface HD-EMG. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|