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Omnidirectional endpoint force control through Functional Electrical Stimulation.

作者信息

Sierotowicz Marek, Castellini Claudio

机构信息

Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Werner-von-Siemens Straße 61, Erlangen, 91052, GERMANY.

Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Werner-von-Siemens Str. 61, Erlangen, Bayern, 91052, GERMANY.

出版信息

Biomed Phys Eng Express. 2023 Aug 15. doi: 10.1088/2057-1976/acf04b.

DOI:10.1088/2057-1976/acf04b
PMID:37582346
Abstract

OBJECTIVE

in recent years, Functional Electrical Stimulation has found many applications both within and outside the medical field. However, most available wearable FES devices are not easily adaptable to different users, and most setups rely on task-specific control schemes.

APPROACH

in this article, we present a peripheral stimulation prototype featuring a compressive jacket which allows to easily modify the electrode arrangement to better fit any body frame. Coupled with a suitable control system, this device can induce the output of arbitrary forces at the end-effector, which is the basis to facilitate universal, task-independent impedance control of the human limbs. Here, the device is validated by having it provide stimulation currents that should induce a desired force output. The forces exerted by the user as a result of stimulation are measured through a 6-axis force-torque sensor, and compared to the desired forces. Furthermore, here we present the offline analysis of a regression algorithm, trained on the data acquired during the aforementioned validation, which is able to reliably predict the force output based on the stimulation currents.

MAIN RESULTS

open-loop control of the output force is possible with correlation coefficients between commanded and measured force output direction up to 0.88. A twitch-based calibration procedure shows significant reduction of the RMS error in the online control. The regression algorithm trained offline is able to predict the force output given the injected stimulation with correlations up to 0.94, and average normalized errors of 0.12 RMS.

SIGNIFICANCE

A reliable force output control through FES is the first basis towards higher-level FES force controls. This could eventually provide full, general-purpose control of the human neuromuscular system, which would allow to induce any desired movement in the peri-personal space in individuals affected by e.g. spinal cord injury.

摘要

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