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Recumbent Cycling and Functional Electrical Stimulation for Lower Limb Rehabilitation
Sponsor: National Council of Scientific and Technical Research, Argentina
Summary
This study evaluates two different control strategies for a rehabilitation device that combines recumbent leg-cycling with functional electrical stimulation (FES) of the quadriceps muscle. The device assists pedaling using a motor and electrical stimulation, and is intended for use after knee surgery (such as ACL reconstruction) or in other lower-limb rehabilitation. During muscle stimulation, fatigue can develop, which reduces the force produced by the stimulated muscle. This study compares a standard control strategy with a new strategy that adjusts stimulation based on the muscle's fatigue level, measured in real time. Healthy adult volunteers will complete two sessions on a recumbent stationary bicycle, 2 to 7 days apart. Each session lasts about 60 minutes and includes periods of pedaling with electrical stimulation, as well as isometric wall squats to induce muscle fatigue. Muscle activity, pedal force, and pedal position will be recorded throughout. The goal is to determine which control strategy produces more mechanical work from the leg muscles and better tracks the desired pedaling pattern, especially as fatigue develops.
Official title: Rehabilitation Mechanisms Based on Recumbent Pedaling and Functional Electrical Stimulation
Key Details
Gender
All
Age Range
18 Years - 60 Years
Study Type
INTERVENTIONAL
Enrollment
30
Start Date
2026-08-20
Completion Date
2026-11-30
Last Updated
2026-10-14
Healthy Volunteers
Yes
Interventions
Fatigue-Feedback FES Control Strategy
A closed-loop control strategy for the FES-assisted recumbent cycling device that explicitly incorporates real-time estimation of muscle fatigue (based on pedal force variation and M-wave median frequency) into the calculation of motor and electrical stimulation control signals.
Standard FES Control Strategy
A closed-loop control strategy for the FES-assisted recumbent cycling device based on a previously published approach, without explicit real-time incorporation of muscle fatigue estimation into the control signal calculation.
Locations (1)
Facultad de Ingeniería - Universidad Nacional de Entre Ríos
Oro Verde, Entre Ríos Province, Argentina