TY - GEN
T1 - Quantitative Characterization of Haptic Sensory Adaptation Evoked Through Transcutaneous Nerve Stimulation
AU - Prabhu, Nita
AU - Vargas, Luis
AU - Hu, Xiaogang
N1 - Funding Information:
This study was supported by the Abrams Scholarship Program through the Joint Department of Biomedical Engineering at UNC-CH and NCSU.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Objective: Haptic perception is an important component of bidirectional human-machine interactions that allow users to better interact with their environment. Artificial haptic sensation along an individual's hand can be evoked via noninvasive electrical nerve stimulation; however, continuous stimulation can result in adaptation of sensory perception over time. In this study, we sought to quantify the adaptation profile via the change in perceived sensation intensity over time. Approach: Noninvasive stimulation of the peripheral nerve bundles evoked haptic perception using a 2x5 electrode grid placed along the medial side of the upper arm near the median and ulnar nerves. An electrode pair that evoked haptic sensation along the forearm and hand was selected. During a trial of 110-s of continuous stimulation, a constant stimulus amplitude just below the motor threshold was delivered. Each subject was instructed to press on a force transducer producing a force amplitude matched with the perceived intensity of haptic sensation. Main Findings: A force decay (i.e., intensity of sensation) was observed in all 7 subjects. Variations in the rate of decay and the start of decay across subjects were also observed. Significance: The preliminary findings established the sensory adaptation profile of peripheral nerve stimulation. Accounting for these subject-specific profiles of adaptation can allow for more stable communication between a robotic device and a user. Additionally, sensory adaptation characterization can promote the development of new stimulation strategies that can mitigate these observed adaptations, allowing for a better and more stable human-machine interaction experience.
AB - Objective: Haptic perception is an important component of bidirectional human-machine interactions that allow users to better interact with their environment. Artificial haptic sensation along an individual's hand can be evoked via noninvasive electrical nerve stimulation; however, continuous stimulation can result in adaptation of sensory perception over time. In this study, we sought to quantify the adaptation profile via the change in perceived sensation intensity over time. Approach: Noninvasive stimulation of the peripheral nerve bundles evoked haptic perception using a 2x5 electrode grid placed along the medial side of the upper arm near the median and ulnar nerves. An electrode pair that evoked haptic sensation along the forearm and hand was selected. During a trial of 110-s of continuous stimulation, a constant stimulus amplitude just below the motor threshold was delivered. Each subject was instructed to press on a force transducer producing a force amplitude matched with the perceived intensity of haptic sensation. Main Findings: A force decay (i.e., intensity of sensation) was observed in all 7 subjects. Variations in the rate of decay and the start of decay across subjects were also observed. Significance: The preliminary findings established the sensory adaptation profile of peripheral nerve stimulation. Accounting for these subject-specific profiles of adaptation can allow for more stable communication between a robotic device and a user. Additionally, sensory adaptation characterization can promote the development of new stimulation strategies that can mitigate these observed adaptations, allowing for a better and more stable human-machine interaction experience.
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U2 - 10.1109/ICHMS56717.2022.9980598
DO - 10.1109/ICHMS56717.2022.9980598
M3 - Conference contribution
AN - SCOPUS:85146268998
T3 - Proceedings of the 2022 IEEE International Conference on Human-Machine Systems, ICHMS 2022
BT - Proceedings of the 2022 IEEE International Conference on Human-Machine Systems, ICHMS 2022
A2 - Kaber, David
A2 - Guerrieri, Antonio
A2 - Fortino, Giancarlo
A2 - Nurnberger, Andreas
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE International Conference on Human-Machine Systems, ICHMS 2022
Y2 - 17 November 2022 through 19 November 2022
ER -