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Gait-Triggered Neuromuscular Electrical Stimulation with Unloader Knee Braces: A Feasibility Study

Authors :

Mohadeseh Jafarian¹ Reza Khosrozadeh Sarijalou² Amin Komeili³ Kourosh Barati⁴ Navid Arjmand⁵

1- Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran 2- Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran 3- Department of Biomedical Engineering, University of Calgary, Calgary, Canada 4- Department of Orthotics and Prosthetics, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran 5- Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran

Keywords :

Knee osteoarthritis،Unloader brace،Neuromuscular electrical stimulation (NMES)،Gait event detection

Abstract :

Objective. Knee osteoarthritis (OA) commonly involves the medial compartment of the joint. Valgus unloader braces can reduce joint loading in this region but may also suppress quadriceps activation. Neuromuscular electrical stimulation (NMES) can strengthen quadriceps when voluntary activation is limited. We evaluated the feasibility of a gait-triggered NMES system used in combination with a valgus unloader brace. Methods. A portable module was developed incorporating a commercial NMES stimulator, a microcontroller, and an inertial measurement unit (IMU). Gait events (mid-swing, initial contact, and toe-off) were detected in real time to trigger quadriceps stimulation. The system was tested in eight adults with medial knee OA and five healthy controls, each completing a 30-minute supervised walking session. Results. The device operated continuously throughout all sessions. In patients with OA, mean cadence was 1.14 ± 0.39 steps·s⁻¹ with cycle detection accuracy of 91.2 ± 8.2%. In healthy controls, cadence was 2.01 ± 0.44 steps·s⁻¹ with accuracy of 93.2 ± 4.3%. No serious adverse events occurred. Conclusion. The proposed brace-compatible, gait-triggered NMES system is feasible, safe, and well tolerated. This proof-of-concept provides a foundation for future works on miniaturization, algorithm refinement, and multi-week clinical trials.