Literature DB >> 10672794

Dimensional change in muscle as a control signal for powered upper limb prostheses: a pilot study.

L P Kenney1, I Lisitsa, P Bowker, G H Heath, D Howard.   

Abstract

The vast majority of externally powered prostheses are controlled from the myoelectric signal, measured at the skin surface using socket-located electrodes. This signal has been well researched and sophisticated signal processing methods developed. Nevertheless, the inherent properties of the signal, such as its broad bandwidth and low voltage amplitude, make its use less than straightforward in the control of low frequency activity such as powered prosthetic hand movement. This paper reports on a pilot study of an alternative, a signal derived from dimensional change in muscle. A new socket-located sensor was designed to measure dimensional change in muscle, the linearised output of which is termed the myokinemetric (MK) signal. This was used in a series of tasks aimed at investigating the potential for its use in upper-limb prosthesis control. Six amputee subjects were tested, of whom one was a regular user of the myoelectric hand, one had some experience, and four had little or no previous experience of controlling devices using their residual limb. Data is presented on the problems of shift in signal range with time and socket donning and doffing and on the ability of subjects to control the amplitude of the signal. The results show that subjects were able to control the magnitude of the MK signal to a significant degree, with typical errors averaging 0.1-0.3 mm, around 10% of the signal range. The principal problem encountered was the shift in signal with time and socket donning and doffing.

Mesh:

Year:  1999        PMID: 10672794     DOI: 10.1016/s1350-4533(99)00089-2

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  5 in total

1.  Estimation of elbow flexion force during isometric muscle contraction from mechanomyography and electromyography.

Authors:  Wonkeun Youn; Jung Kim
Journal:  Med Biol Eng Comput       Date:  2010-06-04       Impact factor: 2.602

Review 2.  Non-invasive control interfaces for intention detection in active movement-assistive devices.

Authors:  Joan Lobo-Prat; Peter N Kooren; Arno H A Stienen; Just L Herder; Bart F J M Koopman; Peter H Veltink
Journal:  J Neuroeng Rehabil       Date:  2014-12-17       Impact factor: 4.262

3.  The Piezo-resistive MC Sensor is a Fast and Accurate Sensor for the Measurement of Mechanical Muscle Activity.

Authors:  Andrej Meglič; Mojca Uršič; Aleš Škorjanc; Srđan Đorđević; Gregor Belušič
Journal:  Sensors (Basel)       Date:  2019-05-07       Impact factor: 3.576

4.  A Piezoresistive Sensor to Measure Muscle Contraction and Mechanomyography.

Authors:  Daniele Esposito; Emilio Andreozzi; Antonio Fratini; Gaetano D Gargiulo; Sergio Savino; Vincenzo Niola; Paolo Bifulco
Journal:  Sensors (Basel)       Date:  2018-08-04       Impact factor: 3.576

Review 5.  Control Methods for Transradial Prostheses Based on Remnant Muscle Activity and Its Relationship with Proprioceptive Feedback.

Authors:  Stefan Grushko; Tomáš Spurný; Martin Černý
Journal:  Sensors (Basel)       Date:  2020-08-28       Impact factor: 3.576

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.