EMG map image processing for recognition of fingers movement
Članak u časopisu (Recenzirana verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Electromyography (EMG) is the conventional noninvasive method for the estimation of muscle activities. We developed a new image processing method for the recognition of individual finger movements based on EMG maps. The maps were formed from the EMG recordings via an array electrode with 24 contacts connected to a multichannel wireless miniature digital amplifier. The task was to detect and quantify the high activity regions in the EMG maps in persons with no known motor impairment. The results show the temporal and spatial patterns within the images during well-defined finger movements. The average accuracy of the automatic recognition compared with the recognition by an expert clinician in persons involved in the tests was 97.87 ± 0.92%. The application of the technique is foreseen for control for an assistive system (hand prosthesis and exoskeleton) since the interface is wearable and the processing can be implemented on a microcomputer.
Ključne reči:
array electrodes / delicate movements / EMG maps / Finger Movements Recognition / image processing / spatial and temporal modelIzvor:
Journal of Electromyography and Kinesiology, 2019, 49, 102364-Izdavač:
- Elsevier
Napomena:
- This is the peer-reviewed version of the article: Topalović, I., Graovac, S., Popović, D.B., 2019. EMG map image processing for recognition of fingers movement. Journal of Electromyography and Kinesiology 49, 102364. https://doi.org/10.1016/j.jelekin.2019.102364
DOI: 10.1016/j.jelekin.2019.102364
ISSN: 1050-6411
WoS: 000501774600004
Scopus: 2-s2.0-85073675407
URI
http://www.sciencedirect.com/science/article/pii/S1050641119302160https://dais.sanu.ac.rs/123456789/6905
Institucija/grupa
Институт техничких наука САНУ / Institute of Technical Sciences of SASATY - JOUR AU - Topalović, Ivan AU - Graovac, Stevica AU - Popović, Dejan B. PY - 2019 UR - http://www.sciencedirect.com/science/article/pii/S1050641119302160 UR - https://dais.sanu.ac.rs/123456789/6905 AB - Electromyography (EMG) is the conventional noninvasive method for the estimation of muscle activities. We developed a new image processing method for the recognition of individual finger movements based on EMG maps. The maps were formed from the EMG recordings via an array electrode with 24 contacts connected to a multichannel wireless miniature digital amplifier. The task was to detect and quantify the high activity regions in the EMG maps in persons with no known motor impairment. The results show the temporal and spatial patterns within the images during well-defined finger movements. The average accuracy of the automatic recognition compared with the recognition by an expert clinician in persons involved in the tests was 97.87 ± 0.92%. The application of the technique is foreseen for control for an assistive system (hand prosthesis and exoskeleton) since the interface is wearable and the processing can be implemented on a microcomputer. PB - Elsevier T2 - Journal of Electromyography and Kinesiology T1 - EMG map image processing for recognition of fingers movement SP - 102364 VL - 49 DO - 10.1016/j.jelekin.2019.102364 UR - https://hdl.handle.net/21.15107/rcub_dais_6905 ER -
@article{ author = "Topalović, Ivan and Graovac, Stevica and Popović, Dejan B.", year = "2019", abstract = "Electromyography (EMG) is the conventional noninvasive method for the estimation of muscle activities. We developed a new image processing method for the recognition of individual finger movements based on EMG maps. The maps were formed from the EMG recordings via an array electrode with 24 contacts connected to a multichannel wireless miniature digital amplifier. The task was to detect and quantify the high activity regions in the EMG maps in persons with no known motor impairment. The results show the temporal and spatial patterns within the images during well-defined finger movements. The average accuracy of the automatic recognition compared with the recognition by an expert clinician in persons involved in the tests was 97.87 ± 0.92%. The application of the technique is foreseen for control for an assistive system (hand prosthesis and exoskeleton) since the interface is wearable and the processing can be implemented on a microcomputer.", publisher = "Elsevier", journal = "Journal of Electromyography and Kinesiology", title = "EMG map image processing for recognition of fingers movement", pages = "102364", volume = "49", doi = "10.1016/j.jelekin.2019.102364", url = "https://hdl.handle.net/21.15107/rcub_dais_6905" }
Topalović, I., Graovac, S.,& Popović, D. B.. (2019). EMG map image processing for recognition of fingers movement. in Journal of Electromyography and Kinesiology Elsevier., 49, 102364. https://doi.org/10.1016/j.jelekin.2019.102364 https://hdl.handle.net/21.15107/rcub_dais_6905
Topalović I, Graovac S, Popović DB. EMG map image processing for recognition of fingers movement. in Journal of Electromyography and Kinesiology. 2019;49:102364. doi:10.1016/j.jelekin.2019.102364 https://hdl.handle.net/21.15107/rcub_dais_6905 .
Topalović, Ivan, Graovac, Stevica, Popović, Dejan B., "EMG map image processing for recognition of fingers movement" in Journal of Electromyography and Kinesiology, 49 (2019):102364, https://doi.org/10.1016/j.jelekin.2019.102364 ., https://hdl.handle.net/21.15107/rcub_dais_6905 .