Two-stage classification of electromyogram signals from hand grasps in the transverse plane

Nantarika Thiamchoo and Pornchai Phukpattaranont

Computer Methods in Biomechanics and Biomedical Engineering, 2023, vol. 26, issue 2, 222-234

Abstract: This paper presents a two-stage classification to resolve the effect of arm position changes on electromyogram (EMG) classification for hand grasps in the transverse plane. The proposed method combines the EMG signals with the signals from an inertial measurement unit in both the position and motion classification stages. To improve accuracy, we incorporate EMG data from the upper arm and shoulder with the forearm EMG signals. When evaluated on the five alternative object grasps placed on the nine positions, the proposed technique yields an average total classification error of 0.9%, which is a substantial improvement over the single-stage classification (4.3%).

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2022.2054271 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:26:y:2023:i:2:p:222-234

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20

DOI: 10.1080/10255842.2022.2054271

Access Statistics for this article

Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton

More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().