Published in

Nature Research, Scientific Reports, 1(12), 2022

DOI: 10.1038/s41598-022-14458-6

Links

Tools

Export citation

Search in Google Scholar

Smartphone-based photogrammetry provides improved localization and registration of scalp-mounted neuroimaging sensors

Journal article published in 2022 by Ilaria Mazzonetto, Marco Castellaro ORCID, Robert J. Cooper, Sabrina Brigadoi
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Red circle
Postprint: archiving forbidden
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

AbstractFunctional near infrared spectroscopy and electroencephalography are non-invasive techniques that rely on sensors placed over the scalp. The spatial localization of the measured brain activity requires the precise individuation of sensor positions and, when individual anatomical information is not available, the accurate registration of these sensor positions to a head atlas. Both these issues could be successfully addressed using a photogrammetry-based method. In this study we demonstrate that sensor positions can be accurately detected from a video recorded with a smartphone, with a median localization error of 0.7 mm, comparable if not lower, to that of conventional approaches. Furthermore, we demonstrate that the additional information of the shape of the participant’s head can be further exploited to improve the registration of the sensor’s positions to a head atlas, reducing the median sensor localization error of 31% compared to the standard registration approach.