Encoding force modulation in two electrotactile feedback parameters strengthens sensory integration according to maximum likelihood estimation.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
01 08 2023
01 08 2023
Historique:
received:
06
03
2023
accepted:
14
07
2023
medline:
3
8
2023
pubmed:
2
8
2023
entrez:
1
8
2023
Statut:
epublish
Résumé
Bidirectional human-machine interfaces involve commands from the central nervous system to an external device and feedback characterizing device state. Such feedback may be elicited by electrical stimulation of somatosensory nerves, where a task-relevant variable is encoded in stimulation amplitude or frequency. Recently, concurrent modulation in amplitude and frequency (multimodal encoding) was proposed. We hypothesized that feedback with multimodal encoding may effectively be processed by the central nervous system as two independent inputs encoded in amplitude and frequency, respectively, thereby increasing state estimate quality in accordance with maximum-likelihood estimation. Using an adaptation paradigm, we tested this hypothesis during a grasp force matching task where subjects received electrotactile feedback encoding instantaneous force in amplitude, frequency, or both, in addition to their natural force feedback. The results showed that adaptations in grasp force with multimodal encoding could be accurately predicted as the integration of three independent inputs according to maximum-likelihood estimation: amplitude modulated electrotactile feedback, frequency modulated electrotactile feedback, and natural force feedback (r
Identifiants
pubmed: 37528160
doi: 10.1038/s41598-023-38753-y
pii: 10.1038/s41598-023-38753-y
pmc: PMC10393971
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
12461Informations de copyright
© 2023. The Author(s).
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