Optical Fiber Force Myography Sensor for Identification of Hand Postures

Author(s)

Fujiwara, Eric ; Suzuki, Carlos Kenichi

• Document type: Journal article
• Source: JOURNAL OF SENSORS; v. 2018, p. 10-pg., 2018-01-01.

Abstract

A low-cost optical fiber force myography sensor for noninvasive hand posture identification is proposed. The transducers are comprised of 10mm periodicity silica multimode fiber microbending devices mounted in PVC plates, providing 0.05 N-1 sensitivity over similar to 20N range. Next, the transducers were attached to the user forearm by means of straps in order to monitor the posterior proximal radial, the anterior medial ulnar, and the posterior distal radial muscles, and the acquired FMG optical signals were correlated to the performed gestures using a 5 hidden layers, 20-neuron artificial neural network classifier with backpropagation architecture, followed by a competitive layer. The overall results for 9 postures and 6 subjects indicated a 98.4% sensitivity and 99.7% average accuracy, being comparable to the electromyographic approaches. Moreover, in contrast to the current setups, the proposed methodology allows the identification of poses characterized by different configurations of fingers and wrist joint displacements with the utilization of only 3 transducers and a simple interrogation scheme, being suitable to further applications in human-computer interfaces. (AU)

• FAPESP's process: 14/25080-0 - Development of an optical fiber based tactile sensor system for applications in mechatronics
• Grantee: Eric Fujiwara
• Support Opportunities: Regular Research Grants