A neuromuscular electrical stimulation strategy based on muscle synergy for stroke rehabilitation
2015 (English)In: International IEEE/EMBS Conference on Neural Engineering, NER, IEEE Computer Society, 2015, 816-819 p.Conference paper (Refereed)
Recent experiments have suggested that the central nervous system (CNS) makes use of muscle synergies as a neural strategy to simplify the control of a variety of movements by using a single pattern of neural command signal. This nature of muscle coordination could have great significance in the treatment and rehabilitation of upper limb impairments for hemiparetic patients post stroke. The use of neuromuscular electrical stimulation (NMES) for neural prosthetics or therapeutic applications has been demonstrated as a promising clinical intervention for stroke patients to recover motor function of the upper extremity. However, the existing NMES systems do not provide control methods for the patient to achieve an individualized and functional rehabilitation training. In this research work, muscle synergies from the flexionextension elbow antagonistic muscles were studied. Using motion information and EMG signals, muscle synergies were extracted using non-negative matrix factorization (NMF) method. Reconstructed signals obtained from the muscle synergies were then applied to the virtual arm (VA) model to test a synergy based NMES strategy. Results show close resemblance to the original elbow trajectory of normal movements and thus the feasibility to control movements in stroke patients for rehabilitation.
Place, publisher, year, edition, pages
IEEE Computer Society, 2015. 816-819 p.
Engineering research, Factorization, Matrix algebra, Mergers and acquisitions, Muscle, Neuromuscular rehabilitation, Patient treatment, Central nervous systems, Clinical interventions, Neuromuscular electrical stimulation, Neuromuscular electrical stimulations (NMES), Nonnegative matrix factorization, Rehabilitation training, Stroke rehabilitation, Therapeutic Application, Patient rehabilitation
IdentifiersURN: urn:nbn:se:kth:diva-175087DOI: 10.1109/NER.2015.7146748ISI: 000377414600204ScopusID: 2-s2.0-84940377031ISBN: 9781467363891OAI: oai:DiVA.org:kth-175087DiVA: diva2:881888
7th International IEEE/EMBS Conference on Neural Engineering, NER 2015, 22 April 2015 through 24 April 2015
QC 201512112015-12-112015-10-092016-07-06Bibliographically approved