Motor execution detection based on autonomic nervous system responses

Marchal Crespo, Laura; Zimmermann, Raphael; Lambercy, Olivier; Edelmann, Janis; Fluet, Marie-Christine; Wolf, Martin; Gassert, Roger; Riener, Robert (2013). Motor execution detection based on autonomic nervous system responses. Physiological measurement, 34(1), pp. 35-51. Institute of Physics Publishing IOP 10.1088/0967-3334/34/1/35

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Triggered assistance has been shown to be a successful robotic strategy for provoking motor plasticity, probably because it requires neurologic patients' active participation to initiate a movement involving their impaired limb. Triggered assistance, however, requires sufficient residual motor control to activate the trigger and, thus, is not applicable to individuals with severe neurologic injuries. In these situations, brain and body–computer interfaces have emerged as promising solutions to control robotic devices. In this paper, we investigate the feasibility of a body–machine interface to detect motion execution only monitoring the autonomic nervous system (ANS) response. Four physiological signals were measured (blood pressure, breathing rate, skin conductance response and heart rate) during an isometric pinching task and used to train a classifier based on hidden Markov models. We performed an experiment with six healthy subjects to test the effectiveness of the classifier to detect rest and active pinching periods. The results showed that the movement execution can be accurately classified based only on peripheral autonomic signals, with an accuracy level of 84.5%, sensitivity of 83.8% and specificity of 85.2%. These results are encouraging to perform further research on the use of the ANS response in body–machine interfaces.

Item Type:

Journal Article (Original Article)

Division/Institute:

10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Motor Learning and Neurorehabilitation
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Gerontechnology and Rehabilitation

UniBE Contributor:

Marchal Crespo, Laura; Gassert, Roger and Riener, Robert

Subjects:

600 Technology > 610 Medicine & health
600 Technology > 620 Engineering

ISSN:

0967-3334

Publisher:

Institute of Physics Publishing IOP

Language:

English

Submitter:

Angela Amira Botros

Date Deposited:

19 Jun 2018 11:23

Last Modified:

18 Jun 2019 17:02

Publisher DOI:

10.1088/0967-3334/34/1/35

PubMed ID:

23248174

BORIS DOI:

10.7892/boris.117040

URI:

https://boris.unibe.ch/id/eprint/117040

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