Quantitative assessment of human-exoskeleton integration through a neurophysiological marker of embodiment

Assistive exoskeletons are increasingly used in rehabilitation settings, yet their adoption in real-world scenarios remains limited. This is partly due to the insufficient understanding of human-device interaction mechanisms. The process through which the central nervous system integrates external devices is known as "tool embodiment" and is primarily assessed through subjective questionnaires. This protocol aims to identify a quantitative marker of embodiment by leveraging the phenomenon of sensory attenuation, i.e., the modulation of sensory stimulation intensity perception as a function of action control. Twenty-one participants either self-administered electrical stimulation to the median nerve by stepping on a pedal or remained still during stimulation by the experimenter, in two conditions: with and without wearing a lower-limb exoskeleton. Somatosensory evoked potentials (SSEPs) were recorded using a 64-channel electroencephalography. Results showed reduced N60 amplitude during self-stimulation, consistent with sensory attenuation, in both conditions. However, wearing the exoskeleton led to higher N60 amplitudes, suggesting reduced motor prediction accuracy. External stimulation elicited a larger N100 component, likely reflecting increased attentional engagement. Together, N60 and N100 serve as promising neurophysiological indices of embodiment and cognitive load. These objective markers could be integrated into the design and evaluation of robotic devices, improving usability and fostering better device-user integration.

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Publication Details

Journal
Scientific Reports
Published
2025-12-24
DOI
https://doi.org/10.1038/s41598-025-33046-y
Primary Topic
Prosthetics and Rehabilitation Robotics
Type
article
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article

Quantitative assessment of human-exoskeleton integration through a neurophysiological marker of embodiment

Margherita Bertuccelli, Patrizia Bisiacchi, Alessandra Del Felice, Emanuele Menegatti et al.
Scientific Reports
Prosthetics and Rehabilitation Robotics
article

Quantitative assessment of human-exoskeleton integration through a neurophysiological marker of embodiment

Margherita Bertuccelli, Patrizia Bisiacchi, Alessandra Del Felice, Emanuele Menegatti, Stefano Tortora, Giovanni Sparacino, Alfonc Baba, Edoardo Trombin, Mariasole Pasinato, William Tasinazzo
article en

Abstract

Assistive exoskeletons are increasingly used in rehabilitation settings, yet their adoption in real-world scenarios remains limited. This is partly due to the insufficient understanding of human-device interaction mechanisms. The process through which the central nervous system integrates external devices is known as "tool embodiment" and is primarily assessed through subjective questionnaires. This protocol aims to identify a quantitative marker of embodiment by leveraging the phenomenon of sensory attenuation, i.e., the modulation of sensory stimulation intensity perception as a function of action control. Twenty-one participants either self-administered electrical stimulation to the median nerve by stepping on a pedal or remained still during stimulation by the experimenter, in two conditions: with and without wearing a lower-limb exoskeleton. Somatosensory evoked potentials (SSEPs) were recorded using a 64-channel electroencephalography. Results showed reduced N60 amplitude during self-stimulation, consistent with sensory attenuation, in both conditions. However, wearing the exoskeleton led to higher N60 amplitudes, suggesting reduced motor prediction accuracy. External stimulation elicited a larger N100 component, likely reflecting increased attentional engagement. Together, N60 and N100 serve as promising neurophysiological indices of embodiment and cognitive load. These objective markers could be integrated into the design and evaluation of robotic devices, improving usability and fostering better device-user integration.

Scientific ReportsVol. 16(1)
University of Padua (IT)
Openalex Percentile: Top 43%
Prosthetics and Rehabilitation Robotics
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