On the Potential of EEG Biomarkers to Inform Robot-Assisted Rehabilitation in Stroke Patients

E. Pirondini; C. Pierella; N. Kinany; M. Coscia; J. Miehlbradt; C. Magnin; P. Nicolo; A. Guggisberg; S. Micera; L. Deouell; D. Van De Ville

doi:10.1007/978-3-030-01845-0_192

On the Potential of EEG Biomarkers to Inform Robot-Assisted Rehabilitation in Stroke Patients

E. Pirondini, C. Pierella, N. Kinany, M. Coscia, J. Miehlbradt, C. Magnin, P. Nicolo, A. Guggisberg, S. Micera, L. Deouell, D. Van De Ville

Department of Psychology

The Hebrew University of Jerusalem

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Stroke is a devastating neurological condition, often causing severe functional and cognitive deficits, sharply diminishing the patient’s quality of life. Among others, robot-assisted rehabilitation has been widely proposed to enhance the rehabilitation outcome. However, clinical scores and robotic parameters often used to inform rehabilitative-decision process are unfit to fully describe the neural reorganization that occur after a brain insult. The lack of reliable, simple, and sensitive neural biomarkers has potentially limited the clinical translation of these advanced rehabilitative technologies. Here, we show that EEG-topographic measures can be extracted as robust and sensitive biomarkers of stroke recovery to inform robotic therapies.

Original language	English
Title of host publication	Biosystems and Biorobotics
Pages	956-960
Number of pages	5
DOIs	https://doi.org/10.1007/978-3-030-01845-0_192
State	Published - 2019

Publication series

Name	Biosystems and Biorobotics
Volume	21

All Science Journal Classification (ASJC) codes

Mechanical Engineering
Artificial Intelligence
Biomedical Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-01845-0_192

Cite this

Pirondini, E., Pierella, C., Kinany, N., Coscia, M., Miehlbradt, J., Magnin, C., Nicolo, P., Guggisberg, A., Micera, S., Deouell, L., & Van De Ville, D. (2019). On the Potential of EEG Biomarkers to Inform Robot-Assisted Rehabilitation in Stroke Patients. In Biosystems and Biorobotics (pp. 956-960). (Biosystems and Biorobotics; Vol. 21). https://doi.org/10.1007/978-3-030-01845-0_192

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AU - Pirondini, E.

AU - Pierella, C.

AU - Kinany, N.

AU - Coscia, M.

AU - Miehlbradt, J.

AU - Magnin, C.

AU - Nicolo, P.

AU - Guggisberg, A.

AU - Micera, S.

AU - Deouell, L.

AU - Van De Ville, D.

PY - 2019

Y1 - 2019

N2 - Stroke is a devastating neurological condition, often causing severe functional and cognitive deficits, sharply diminishing the patient’s quality of life. Among others, robot-assisted rehabilitation has been widely proposed to enhance the rehabilitation outcome. However, clinical scores and robotic parameters often used to inform rehabilitative-decision process are unfit to fully describe the neural reorganization that occur after a brain insult. The lack of reliable, simple, and sensitive neural biomarkers has potentially limited the clinical translation of these advanced rehabilitative technologies. Here, we show that EEG-topographic measures can be extracted as robust and sensitive biomarkers of stroke recovery to inform robotic therapies.

AB - Stroke is a devastating neurological condition, often causing severe functional and cognitive deficits, sharply diminishing the patient’s quality of life. Among others, robot-assisted rehabilitation has been widely proposed to enhance the rehabilitation outcome. However, clinical scores and robotic parameters often used to inform rehabilitative-decision process are unfit to fully describe the neural reorganization that occur after a brain insult. The lack of reliable, simple, and sensitive neural biomarkers has potentially limited the clinical translation of these advanced rehabilitative technologies. Here, we show that EEG-topographic measures can be extracted as robust and sensitive biomarkers of stroke recovery to inform robotic therapies.

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BT - Biosystems and Biorobotics

ER -

On the Potential of EEG Biomarkers to Inform Robot-Assisted Rehabilitation in Stroke Patients

Abstract

Publication series

All Science Journal Classification (ASJC) codes

UN SDGs

Access to Document

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