This study proposes a novel approach for telepal- pation of digital twins of biological tissue phantoms within a Virtual Reality environment, integrating neuromorphic vibrotactile feedback. When exploring the virtual sample, which presents varied material properties, a vibrotactile actuator placed on the user's fingertip delivers naturalistic stiffness feedback in real-time. The information is processed through a neuromorphic approach, which implements the spiking behavior of the mechanoreceptors of the human skin, to trigger vibrations of the haptic interface. A psychophysical experiment confirmed that the proposed strategy and system enable the identification of different stiffness levels with an overall accuracy of 94% and a threshold of stiffness difference of 0.13 N/mm. These results provide preliminary evidence for the possibility to detect tumor inclusions in biological tissue through digital twins. This pioneering approach paves the way for advanced telemedicine applications thereby fostering advancements in remote palpation of biological tissues for medical training and both remote and enhanced diagnosis.

Telepalpation System for Stiffness Recognition of Tissue Digital Twins through Neuromorphic Vibrotactile Feedback in Virtual Reality

Profili, Alessandro;Piretta, Flaminia;Mezei, Marton Csaba;Auletta, Fabrizia;Filosa, Mariangela;Oddo, Calogero Maria
2025-01-01

Abstract

This study proposes a novel approach for telepal- pation of digital twins of biological tissue phantoms within a Virtual Reality environment, integrating neuromorphic vibrotactile feedback. When exploring the virtual sample, which presents varied material properties, a vibrotactile actuator placed on the user's fingertip delivers naturalistic stiffness feedback in real-time. The information is processed through a neuromorphic approach, which implements the spiking behavior of the mechanoreceptors of the human skin, to trigger vibrations of the haptic interface. A psychophysical experiment confirmed that the proposed strategy and system enable the identification of different stiffness levels with an overall accuracy of 94% and a threshold of stiffness difference of 0.13 N/mm. These results provide preliminary evidence for the possibility to detect tumor inclusions in biological tissue through digital twins. This pioneering approach paves the way for advanced telemedicine applications thereby fostering advancements in remote palpation of biological tissues for medical training and both remote and enhanced diagnosis.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/588000
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