An fmri compatible smart device for measuring palmar grasping actions in newborns
Journal article, 2020

Grasping is one of the first dominant motor behaviors that enable interaction of a newborn infant with its surroundings. Although atypical grasping patterns are considered predictive of neuromotor disorders and injuries, their clinical assessment suffers from examiner subjectivity, and the neuropathophysiology is poorly understood. Therefore, the combination of technology with functional magnetic resonance imaging (fMRI) may help to precisely map the brain activity associated with grasping and thus provide important insights into how functional outcomes can be improved following cerebral injury. This work introduces an MR-compatible device (i.e., smart graspable device (SGD)) for detecting grasping actions in newborn infants. Electromagnetic interference immunity (EMI) is achieved using a fiber Bragg grating sensor. Its biocompatibility and absence of electrical signals propagating through the fiber make the safety profile of the SGD particularly favorable for use with fragile infants. Firstly, the SGD design, fabrication, and metrological characterization are described, followed by preliminary assessments on a preterm newborn infant and an adult during an fMRI experiment. The results demonstrate that the combination of the SGD and fMRI can safely and precisely identify the brain activity associated with grasping behavior, which may enable early diagnosis of motor impairment and help guide tailored rehabilitation programs.

Grasping actions detection

Fiber Bragg grating sensors (FBGs)

Functional magnetic resonance imaging (fMRI)

MR-compatible measuring systems

Motor assessment

Author

Daniela Lo Presti

Università Campus Bio-Medico di Roma

Sofia Dall'orso

King's College London

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Biomedical Signals and Systems

Silvia Muceli

King's College London

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Biomedical Signals and Systems

Tomoki Arichi

Evelina London Children's Healthcare

King's College London

Sara Neumane

King's College London

University Paris-Saclay

Neurodevelopmental and Neurovascular Disorders

Anna Lukens

Evelina London Children's Healthcare

Riccardo Sabbadini

Università Campus Bio-Medico di Roma

Carlo Massaroni

Università Campus Bio-Medico di Roma

Michele Arturo Caponero

ENEA Centro Ricerche Frascati

Domenico Formica

Università Campus Bio-Medico di Roma

E. Burdet

Imperial College London

Emiliano Schena

Università Campus Bio-Medico di Roma

Sensors

1424-8220 (ISSN) 1424-3210 (eISSN)

Vol. 20 21 1-16 6040

Subject Categories

Pediatrics

Other Medical Engineering

Neurosciences

DOI

10.3390/s20216040

PubMed

33114180

More information

Latest update

11/11/2020