Scholarlink

Locomotion identification is crucial for high-level exoskeleton control, enabling real-time recognition of transitions across modes (e.g., overground walking, ramps, stairs). This paper presents an approach that relies solely on exoskeleton sensor data, combining a heuristic and a data-driven method based on a normative dataset. Preliminary results from 5 healthy participants show the method’s ability to distinguish between locomotion modes. Future work will integrate a controller that applies the desired torque to assist users in performing each movement.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Locomotion Identification for Lower-Limb Exoskeletons

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Lorenzo Vianello,
  • Clément Lhoste,
  • Emek Barış Küçüktabak,
  • Matthew R. Short,
  • Jose L. Pons

摘要

Locomotion identification is crucial for high-level exoskeleton control, enabling real-time recognition of transitions across modes (e.g., overground walking, ramps, stairs). This paper presents an approach that relies solely on exoskeleton sensor data, combining a heuristic and a data-driven method based on a normative dataset. Preliminary results from 5 healthy participants show the method’s ability to distinguish between locomotion modes. Future work will integrate a controller that applies the desired torque to assist users in performing each movement.