| Full text | |
| Author(s): |
Fujiwara, Eric
;
Wu, Yu Tzu
;
Suzuki, Carlos Kenichi
;
de Andrade, Dandara Thamilys Guedes
;
Ribas Neto, Antonio
;
Rohmer, Eric
;
IEEE
Total Authors: 7
|
| Document type: | Journal article |
| Source: | 2018 IEEE 15TH INTERNATIONAL WORKSHOP ON ADVANCED MOTION CONTROL (AMC); v. N/A, p. 6-pg., 2018-01-01. |
| Abstract | |
The application of an optical fiber sensor on the identification of hand postures by force myography technique is reported. The transducers are comprised of fiber microbending elements attached to the user forearm, allowing the assessment of muscular activities related to the hand movements. Next, the output light intensities are detected, and then correlated to the performed postures by means of artificial neural networks. The methodology was applied on the identification of 5 postures, yielding a 96.7% accuracy considering the average of 4 subjects. Finally, the sensor was utilized for controlling a virtual prosthetic hand implemented on V-REP environment, based on the event driven finite-state approach, providing the real-time execution of predefined grasp patterns. (AU) | |
| FAPESP's process: | 13/07559-3 - BRAINN - The Brazilian Institute of Neuroscience and Neurotechnology |
| Grantee: | Fernando Cendes |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| 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 |