Sensing and Control Strategies Used in FES Systems Aimed at Assistance and Rehabilitation of Foot Drop: A Systematic Literature Review

Author:

González-Graniel Estefanía1,Mercado-Gutierrez Jorge A.2,Martínez-Díaz Saúl1ORCID,Castro-Liera Iliana1ORCID,Santillan-Mendez Israel M.1,Yanez-Suarez Oscar3,Quiñones-Uriostegui Ivett2,Rodríguez-Reyes Gerardo2

Affiliation:

1. División de estudios de Posgrado e Investiagación, TecNM-Instituto Tecnológico de la Paz, La Paz 28080, Mexico

2. Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City 14389, Mexico

3. Electrical Engineering Department, Universidad Autónoma Metropolitana—Unidad Iztapalapa, Mexico City 09340, Mexico

Abstract

Functional electrical stimulation (FES) is a rehabilitation and assistive technique used for stroke survivors. FES systems mainly consist of sensors, a control algorithm, and a stimulation unit. However, there is a critical need to reassess sensing and control techniques in FES systems to enhance their efficiency. This SLR was carried out following the PRISMA 2020 statement. Four databases (PubMed, Scopus, Web of Science, Wiley Online Library) from 2010 to 2024 were searched using terms related to sensing and control strategies in FES systems. A total of 322 articles were chosen in the first stage, while only 60 of them remained after the final filtering stage. This systematic review mainly focused on sensor techniques and control strategies to deliver FES. The most commonly used sensors reported were inertial measurement units (IMUs), 45% (27); biopotential electrodes, 36.7% (22); vision-based systems, 18.3% (11); and switches, 18.3% (11). The control strategy most reported is closed-loop; however, most of the current commercial FES systems employ open-loop strategies due to their simplicity. Three main factors were identified that should be considered when choosing a sensor for gait-oriented FES systems: wearability, accuracy, and affordability. We believe that the combination of computer vision systems with artificial intelligence-based control algorithms can contribute to the development of minimally invasive and personalized FES systems for the gait rehabilitation of patients with FDS.

Funder

Secretaría de Educación, Ciencia, Tecnologia e Innovacion

Tecnológico Nacional de México

Publisher

MDPI AG

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