File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Detection of Human Action Intention by Electromyography (EMG)

TitleDetection of Human Action Intention by Electromyography (EMG)
Authors
Issue Date27-Jul-2022
Abstract
Due to the growing proportion of elderly people in modern society, there is significant need for an increased understanding of the mechanisms of skeletal muscle structures and functions. This will allow robots to be developed to provide support for the elderly. Wearable robots have been developed for applications related to assistance and rehabilitation. The control strategy of a wearable robot is a subtle balance between the generation of muscle force from a human and the generation of force from a robot assistant. The intention of standing should be detected instantaneously, as the time window for the effect of assistance is much shorter. According to the literature, electronic signals generated from muscles are present before the force itself. Therefore, surface electromyography (sEMG) is a suitable approach for detecting the action of human movement. An approach for detecting human action intention based on sEMG is presented in this paper. By using the Kalman Filter, the response time can be shrunk within 20ms, which will provide an instant signal to the robot control system and improve the robot assistant's performance.

Persistent Identifierhttp://hdl.handle.net/10722/333884

 

DC FieldValueLanguage
dc.contributor.authorYuan, Wenbo-
dc.contributor.authorZou, Kehan-
dc.contributor.authorZhao, Yafei-
dc.contributor.authorXi, Ning-
dc.date.accessioned2023-10-06T08:39:53Z-
dc.date.available2023-10-06T08:39:53Z-
dc.date.issued2022-07-27-
dc.identifier.urihttp://hdl.handle.net/10722/333884-
dc.description.abstract<div>Due to the growing proportion of elderly people in modern society, there is significant need for an increased understanding of the mechanisms of skeletal muscle structures and functions. This will allow robots to be developed to provide support for the elderly. Wearable robots have been developed for applications related to assistance and rehabilitation. The control strategy of a wearable robot is a subtle balance between the generation of muscle force from a human and the generation of force from a robot assistant. The intention of standing should be detected instantaneously, as the time window for the effect of assistance is much shorter. According to the literature, electronic signals generated from muscles are present before the force itself. Therefore, surface electromyography (sEMG) is a suitable approach for detecting the action of human movement. An approach for detecting human action intention based on sEMG is presented in this paper. By using the Kalman Filter, the response time can be shrunk within 20ms, which will provide an instant signal to the robot control system and improve the robot assistant's performance.</div>-
dc.languageeng-
dc.relation.ispartof2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER) (27/07/2022-31/07/2022, Baishan)-
dc.titleDetection of Human Action Intention by Electromyography (EMG)-
dc.typeConference_Paper-
dc.identifier.doi10.1109/CYBER55403.2022.9907225-
dc.identifier.scopuseid_2-s2.0-85141173344-
dc.identifier.spage750-
dc.identifier.epage754-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats