Optimization framework for the model-based estimation of in vivo α-motoneuron properties in the intact human

R. Ornelas Kobayashi, A. Gogeascoechea, J. Buitenweg, U. Yavuz, M. Sartori

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

The in vivo estimation of α-motoneuron (MN) properties in humans is crucial to characterize the effect that neurorehabilitation technologies may elicit over the composite neuro-musculoskeletal system. Here, we combine biophysical neuronal modelling, high-density electromyography and convolutive blind-source separation along with numerical optimization to estimate geometrical and electrophysiological properties of in vivo decoded human MNs. The proposed methodology implements multi-objective optimization to automatically tune ionic channels conductance and soma size of MN models for minimizing the error between several features of simulated and in vivo decoded MN spike trains. This approach will open new avenues for the closed-loop control of motor restorative technologies such as wearable robots and neuromodulation devices.Clinical Relevance- This work proposes a non-invasive framework for the in vivo estimation of person-specific α-motoneuron properties. This will enable predicting neuronal adaptations in response to neurorehabilitation therapies in the intact human.

Original languageEnglish
Title of host publication2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Pages6126-6129
Number of pages4
Volume2021
ISBN (Electronic)978-1-7281-1179-7
DOIs
Publication statusPublished - 9 Dec 2021
Event43rd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2021: Changing Global Health Care in the Twenty-First Century - Virtual
Duration: 1 Nov 20215 Nov 2021
Conference number: 43

Conference

Conference43rd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Abbreviated titleEMBC
Period1/11/215/11/21

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