Constrained ALS for Estimation of Human Upper Limb Synergies

Rabya Bahadur, Rabya Bahadur, Saeed Rehman

2023

Abstract

Human body movement is a complex task that requires the control of multiple joints via a network of muscles. The biological signals, particularly electromyography (EMG), are correlated by nature. The brain transmits these signals through the neuromuscular transmission system of the body. The combination of muscular activation for each particular movement presents a set of weights known as synergies. The traditional alternating least square (ALS) based non-negative matrix factorization (NMF) gets trapped in local minima for co-linear data. Therefore, it is not a suitable method for extracting muscle synergies. This paper advocate using l2-norm as an additional constraint for ALS-based NMF. The addition of l2-norm decorrelates the data, resulting in a better estimation of synergistic weights. For our results, we acquired EMG signals from six healthy subjects. Both plain and regularized NMF were used to extract the synergies. The synergies acquired via plain NMF have a higher cross-correlation within and indicate the triggering of the same muscles irrespective of the targeted isometric contraction. In contrast, the regularized NMF synergies targeted the correct muscular set for a particular isometric contraction. Our results show that the synergies acquired via regularized NMF are also more correlated with the physiologically inspired synergies.

Paper Citation

in Harvard Style

Bahadur R. and Rehman S. (2023). Constrained ALS for Estimation of Human Upper Limb Synergies. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 4: BIOSIGNALS; ISBN 978-989-758-631-6, SciTePress, pages 29-35. DOI: 10.5220/0011604400003414

in Bibtex Style

@conference{biosignals23,
author={Rabya Bahadur and Saeed Rehman},
title={Constrained ALS for Estimation of Human Upper Limb Synergies},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 4: BIOSIGNALS},
year={2023},
pages={29-35},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011604400003414},
isbn={978-989-758-631-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 4: BIOSIGNALS
TI - Constrained ALS for Estimation of Human Upper Limb Synergies
SN - 978-989-758-631-6
AU - Bahadur R.
AU - Rehman S.
PY - 2023
SP - 29
EP - 35
DO - 10.5220/0011604400003414
PB - SciTePress