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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Evaluation of Optical Myography Sensor as Predictor of Hand Postures

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Author(s):
Wu, Yu Tzu [1] ; Fujiwara, Eric [1] ; Suzuki, Carlos K. [1]
Total Authors: 3
Affiliation:
[1] Univ Estadual Campinas, Sch Mech Engn, Lab Photon Mat & Devices, BR-13083860 Campinas, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: IEEE SENSORS JOURNAL; v. 19, n. 13, p. 5299-5306, JUL 1 2019.
Web of Science Citations: 1
Abstract

Optical myography stands as one of many techniques to assess hand postures. As a combination of computer vision and muscular activity analysis, it differs from conventional gesture recognition techniques, such as instrumented gloves or optical tracking, by not relying on the existence of a healthy hand, so it is able to detect the hand motion as well as the motion intent. In this aspect, optical myography is like well-established myographic approaches, such as surface electromyography or force myography, but it is simpler, more comfortable, and inexpensive. This recent technology is hereby evaluated upon the construction of a feasible and low-cost sensor that monitors both the front and the back of the forearm. The results are organized into two sections: the first validates the sensor and the second evaluates its performance as a predictor of eight static postures, including the thumb and the fingers motion. In the end, the sensor proved to be comparable to more mature techniques with an F-score of similar to 92.2% and similar to 71.5% for front- and back-side analysis, respectively. (AU)

FAPESP's process: 17/25666-2 - Development of an optical fiber force myography sensor for applications in human-robot interfaces
Grantee:Eric Fujiwara
Support type: Regular Research Grants