Matrix Factorization Algorithms for the Identification of Muscle Synergies: Evaluation on Simulated and Experimental Data Sets
Northwestern University · Northwestern Medicine · +2 more institutions
Abstract
Several recent studies have used matrix factorization algorithms to assess the hypothesis that behaviors might be produced through the combination of a small number of muscle synergies. Although generally agreeing in their basic conclusions, these studies have used a range of different algorithms, making their interpretation and integration difficult. We therefore compared the performance of these different algorithms on both simulated and experimental data sets. We focused on the ability of these algorithms to identify the set of synergies underlying a data set. All data sets consisted of nonnegative values, reflecting the nonnegative data of muscle activation patterns. We found that the performance of…
Citation impact
- FWCI
- 9.50
- Percentile
- 100%
- References
- 52
Authors
3Topics & keywords
- Non-negative matrix factorization
- Independent component analysis
- Principal component analysis
- Varimax rotation
- Matrix decomposition
- Data set
- Pattern recognition (psychology)
- Algorithm