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  4. Computer vision-based algorithm to sUppoRt coRrect electrode placemeNT (CURRENT) for home-based electric non-invasive brain stimulation
 
research article

Computer vision-based algorithm to sUppoRt coRrect electrode placemeNT (CURRENT) for home-based electric non-invasive brain stimulation

Windel, Fabienne  
•
Gardier, Remy Marc M.  
•
Fourchard, Gaspard
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July 14, 2023
Clinical Neurophysiology

Objective: Home-based non-invasive brain stimulation (NIBS) has been suggested as an adjunct treatment strategy for neuro-psychiatric disorders. There are currently no available solutions to direct and monitor correct placement of the stimulation electrodes. To address this issue, we propose an easy-touse digital tool to support patients for self-application. Methods: We recruited 36 healthy participants and compared their cap placement performance with the one of a NIBS-expert investigator. We tested participants' placement accuracy with instructions before (Pre) and after the investigator's placement (Post), as well as participants using the support tool (CURRENT). User experience (UX) and confidence were further evaluated. Results: Permutation tests demonstrated a smaller deviation within the CURRENT compared with Pre cap placement (p = 0.02). Subjective evaluation of ease of use and usefulness of the tool were vastly positive (8.04 out of 10). CURRENT decreased the variability of performance, ensured placement within the suggested maximum of deviation (10 mm) and supported confidence of correct placement. Conclusions: This study supports the usability of this novel technology for correct electrode placement during self-application in home-based settings. Significance: CURRENT provides an exciting opportunity to promote home-based, self-applied NIBS as a safe, high-frequency treatment strategy that can be well integrated in patients' daily lives. & COPY; 2023 Published by Elsevier B.V. on behalf of International Federation of Clinical Neurophysiology.

  • Details
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Type
research article
DOI
10.1016/j.clinph.2023.06.009
Web of Science ID

WOS:001043377300001

Author(s)
Windel, Fabienne  
Gardier, Remy Marc M.  
Fourchard, Gaspard
Vinals, Roser  
Bavelier, Daphne
Padberg, Frank Johannes
Rancans, Elmars
Bonne, Omer
Nahum, Mor
Thiran, Jean-Philippe  
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Date Issued

2023-07-14

Published in
Clinical Neurophysiology
Volume

153

Start page

57

End page

67

Subjects

Clinical Neurology

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Neurosciences

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Neurosciences & Neurology

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home -based non-invasive brain stimulation

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tes

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electrode localization algorithm

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real-time feedback

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monitoring

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computer vision

•

state

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
UPHUMMEL  
Available on Infoscience
August 28, 2023
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/200294
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