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2022 | OriginalPaper | Buchkapitel

NNMF Analysis to Individual Identification of Fingers Movements Using Force Feedback and HD-EMG

verfasst von : V. C. Ecard, L. L. Menegaldo, L. F. Oliveira

Erschienen in: XXVII Brazilian Congress on Biomedical Engineering

Verlag: Springer International Publishing

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Abstract

High-density electromyography (HD-EMG) signals have been widely used today due to their ability to extract spatial information from muscle activity. Several studies pursuit a pattern of activation of the fingers with the muscle activation center using several types of different protocols. This work aims to develop a feedback protocol for finger recognition using HD-EMG. The tools for the analysis were the activation centroids of each finger in addition to the use of the non-negative matrix factorization (NNMF) algorithm to extract the associated synergies of each finger and dissociate them. The protocol elected in this research proved to be effective in the selection of index and minimum fingers. In addition, an ANOVA statistical test application on synergies showed great utility in dissociating fingers.

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Vorheriges Kapitel Comparison of Kinematic Data Obtained by Inertial Sensors and Video Analysis

Nächstes Kapitel Nonlinear Closed-Loop Control of an OpenSim Wrist Model: Tuning Using Genetic Algorithm

Martinez MR, Mañanas M, Alonso JF (2012) High-density surface EMG maps from upper-arm and forearm muscles. Neuroeng Rehab 9:1–17. https://doi.org/10.1186/1743-0003-9-85CrossRef

Merletti R, Holobar A, Farina D (2008) Analysis of motor units with high-density surface electromyography. J Electromyogr Kinesiol 18:879–890. https://doi.org/10.1016/j.jelekin.2008.09.002CrossRef

Gazzoni M, Celadon N, Mastrapasqua D et al (2014) Quantifying forearm muscle activity during wrist and finger movements by means of multi-channel electromyography. PLoS ONE 9:1–11. https://doi.org/10.1371/journal.pone.0109943CrossRef

Muccli S, Farina D (2012) Simultaneous and proportional estimation of hand kinematics from EMG during mirrored movements at multiple degrees-of-freedon. IEEE Trans Neural Syst Rehab 20:371–378. https://doi.org/10.1109/TNSRE.2011.2178039CrossRef

Martinez MR, Mañanas M, Alonso JF, Merletti R (2012) Identification of isometric contractions based on high density EMG maps. J Electromyogr Kinesiol 23:33–42. https://doi.org/10.1016/j.jelekin.2012.06.009CrossRef

Gallina A, Botter A (2013) Spatial localization of electromyographic amplitude distributions associated to the activation of dorsal forearm muscles. Front Physiol 4:367–372. https://doi.org/10.3389/fphys.2013.00367CrossRef

Celadon N, Dosen S, Binder I et al (2016) Proportional estimation of finger movements from high-density surface electromyography. Neuroengineering Rehab 13:17–36. https://doi.org/10.1186/s12984-016-0172-3CrossRef

Dai C, Hu X (2018) Extracting and classifying spatial muscle activation patterns in forearm flexor muscles using high-density electromyogram recordings. Int J Neural Syst 29:1–15. https://doi.org/10.1142/S0129065718500259CrossRef

Lee D, Seung H (1999) Learning the parts of objects by non-negative matrix factorization. Nature 401:788–791. https://doi.org/10.1038/44565CrossRefMATH

10.

Wang B, Plumbley M (2005) Musical audio stream separation by non-negative matrix factorization. In: Conference: proceedings of the DMRN summer conference, Glasgow, Scotland, pp 23–24

11.

Cichocki A, Zdunek R, Amari S (2006) New algorithms for non-negative matrix factorization in applications to blind source separation. In: 2006 IEEE international conference on acoustics speech and signal processing proceedings, Toulouse, France, 2006. pp V–V

12.

Tsuge S, Shishibori M, Kuroiwa S et al.(2001) Dimensionality reduction using non-negative matrix factorization for information retrieval. In: 2001 IEEE international conference on systems, man and cybernetics, Tucson, USA, pp 960–965

13.

Wilson K, Raj B, Paris S (2017) Regularized non-negative matrix factorization with temporal dependencies for speech denoising. INTERSPEECH, Brisbane, Australia 2017:411–414

14.

Steele K, Rozumalski A, Schwartz M (2015) Muscle synergies and complexity of neuromuscular control during gait in cerebral palsy. Dev Med Child Neurol 57:1176–1182. https://doi.org/10.1111/dmcn.12826CrossRef

15.

Kin Y, Bulea T, Damiano D (2016) Novel methods to enhance precision and reliability in muscle synergy identification during walking. Front Human Neuroscience 10:455. https://doi.org/10.3389/fnhum.2016.00455CrossRef

16.

Banks CL, Pai MM, Mcguirk TE et al (2017) Methodological choices in muscle synergy analysis impact differentiation of physiological characteristics following stroke. Front Comput Neurosci 11:78. https://doi.org/10.3389/fncom.2017.00078CrossRef

17.

Barroso F, Torricelli D, Molina-Rueda F et al (2017) Combining muscle synergies and biomechanical analysis to assess gait in stroke patients. J Biomech 63:98–103. https://doi.org/10.1016/j.jbiomech.2017.08.006CrossRef

18.

Phukpattaranont P, Thongpanja S, Anam K et al (2018) Evaluation of feature extraction techniques and classifiers for finger movement recognition using surface electromyography signal. Med Biol Eng Comput 56:1–13. https://doi.org/10.1007/s11517-018-1857-5CrossRef

19.

Naik G, Nguyen H (2015) Nonnegative matrix factorization for the identification of EMG finger movements: evaluation using matrix analysis. IEEE J Biomed Health Informatics 19(2):478–485. https://doi.org/10.1109/JBHI.2014.2326660CrossRef

20.

Topalovic I, Graovac S, Popovic D (2019) EMG map image processing for recognition of fingers movement. J Electromyogr Kinesiol 49:102364. https://doi.org/10.1016/j.jelekin.2019.102364CrossRef

21.

Hu X, Suresh N L, Xue C et al. Extracting extensor digitorum communis activation patterns using high-density surface electromyography. Front Physiol 6:279. https://doi.org/10.3389/fphys.2015.00279

Titel: NNMF Analysis to Individual Identification of Fingers Movements Using Force Feedback and HD-EMG
verfasst von: V. C. Ecard
L. L. Menegaldo
L. F. Oliveira
Verlag: Springer International Publishing
Buch: XXVII Brazilian Congress on Biomedical Engineering
Print ISBN: 978-3-030-70600-5

Electronic ISBN: 978-3-030-70601-2

Copyright-Jahr: 2022
DOI: https://doi.org/10.1007/978-3-030-70601-2_74

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