Automated Forearm Prosthesis Controlling Using Fiber Bragg Grating Sensor

被引：0

作者：

Rialto P.V., Júnior ^{[1
]}

Dureck E.H. ^{[2
]}

Kalinowski A. ^{[2
]}

Zamarreño C.R. ^{[3
]}

Socorro-Leranoz A.B. ^{[3
]}

Da Silva J.C.C. ^{[2
]}

Lazzaretti A.E. ^{[2
]}

Dreyer U.J. ^{[1
]}

机构：

[1] Graduate Program on Energy Systems, Universidade Tecnológica Federal Do Paraná, Curitiba

[2] Graduate Program in Electrical and Computer Engineering, Universidade Tecnológica Federal Do Paraná, Curitiba

[3] Universidad Publica de Navarra, Campus Arrosadia, Pamplona

来源：

Journal of Microwaves, Optoelectronics and Electromagnetic Applications | 2023年 / 22卷 / 01期

关键词：

Automated Prosthesis; Fiber Bragg Grating (FBG); Forearm sensing; Two finger control;

D O I：

10.1590/2179-10742023v22i1271724

中图分类号：

学科分类号：

摘要：

This paper describes the automation of a forearm prosthesis using the signal collected by a Fiber Bragg Grating (FBG) sensor. The FBG sensor is applied to one subject's forearm to measure the deformation as a result of the index and middle fingers when moved individually. It is possible to control a one joint model prosthesis allied to a compliant hand mechanism through signal analyses. Each finger movement has its features, such as its amplitude, which opens the possibility of using those to control different parts of the prosthesis, joint rotation by the middle finger, and compliant hand movement by the index finger. This paper presents results regarding prosthesis assembling, Hypertext Transfer Protocol (HTTP) communication latency between prosthesis and computer and tests with pre-acquired and processed FBG signal data. The prosthesis wrist rotation movement is related to the middle finger signal, and its compliant mechanism actuation is due to index finger signal. The communication between prosthesis and the computer had a mean latency of 140 ms and a standard deviation of 18 ms. The results demonstrate the potential for using the sensor system and automated prosthesis in other applications involving real-time forearm sensing, multi-finger signal analysis, and prosthetic movement. © 2023 SBMO/SBMag.

引用

页码：208 / 218

页数：10

共 32 条

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