The mental workload has been playing more and more important role in air transportation industry. And the level of mental workload has apparent link to the human operational performance. To explore the human operational performance, relationship between the states of muscles of the forearm and Surface Electromyography (sEMG) signals induced by specific motion modes should be studied first. In this paper, the flexor carpi ulnaris, flexor carpi radialis, brachioradialis, palmaris longus and biceps brachii of the right forearm are selected as the source of the sEMG signals according to the anatomy. The sEMG signals of these muscles were obtained in a specific and real experimental environment. A method of binary coding was applied to deal with the sEMG. The result of experiment shows that sEMG signals have strong ability of recognizing different hand movements. But only using the parameter of time domain can we hardly distinguish hang gestures.
CITATION STYLE
Hou, T., Qian, C., Lu, Y., & Fu, S. (2018). The mapping between hand motion states induced by arm operation and surface electromyography. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10906 LNAI, pp. 317–329). Springer Verlag. https://doi.org/10.1007/978-3-319-91122-9_27
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