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Motion capture technology, widely recognized for its applications in fields such as film and animation, also plays a pivotal role in movement research across various disciplines. This study explores low-cost methods for analyzing cycling movement on an adapted trike for Functional Electrical Stimulation (FES) intended for patients with Spinal Cord Injury (SCI). The methods consist of two approaches: (1) Video processing with the use of Kinovea software, and (2) data obtained from IMUs combined with OpenSim software. The study results show that both methodologies provide satisfactory and comparable measurements of hip and knee angles, with slight discrepancies due to protocol limitations. The findings suggest that combining IMUs with OpenSim and video analysis with Kinovea can be effective tools for analyzing cycling motion in FES cycling setups. These results have significant implications for improving rehabilitation techniques and enhancing patient outcomes in clinical settings, particularly for patients with SCI.

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Feasibility of Low-Cost Alternatives to Estimate Hip and Knee Angles of Adapted Cycling Movement

  • 会议论文

  • 发表日期：

    2025年

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  • Alexandre Bernardi Peres,
  • Marina Pinho Garcia,
  • Roberto de Souza Baptista

摘要

Motion capture technology, widely recognized for its applications in fields such as film and animation, also plays a pivotal role in movement research across various disciplines. This study explores low-cost methods for analyzing cycling movement on an adapted trike for Functional Electrical Stimulation (FES) intended for patients with Spinal Cord Injury (SCI). The methods consist of two approaches: (1) Video processing with the use of Kinovea software, and (2) data obtained from IMUs combined with OpenSim software. The study results show that both methodologies provide satisfactory and comparable measurements of hip and knee angles, with slight discrepancies due to protocol limitations. The findings suggest that combining IMUs with OpenSim and video analysis with Kinovea can be effective tools for analyzing cycling motion in FES cycling setups. These results have significant implications for improving rehabilitation techniques and enhancing patient outcomes in clinical settings, particularly for patients with SCI.