Hybrid exoskeletons combine functional electrical stimulation (FES) and robotic assistance to restore and rehabilitate movement. Real-time control of FES parameters is necessary to maximize outcomes. Recently, muscle deformation captured by ultrasound imaging has been demonstrated as an effective human machine interface. Here, we examine if ultrasound imaging can track joint kinematics in the presence and absence of FES to assess its viability for real-time control of stimulation parameters. Muscle deformation from ultrasound was correlated to limb movement using a simple image similarity metric. One healthy participant performed volitional and FES-driven wrist, ankle, and knee flexion/extension while simultaneous motion capture, surface electromyography, and ultrasound were collected. Ultrasound imaging tracked joint kinematics with and without FES with mean errors of 1.7 ± 20.7% and 3.9 ± 18.1%, respectively, averaged across all three joints. Our results demonstrate the feasibility of ultrasound to track stimulation driven movement and potentially adjust FES parameters in real-time.

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

Tracking Joint Movement with Ultrasound in the Presence of Functional Electrical Stimulation

  • Shriniwas Patwardhan,
  • Katharine E. Alter,
  • Jared A. Stowers,
  • Diane L. Damiano,
  • Thomas C. Bulea

摘要

Hybrid exoskeletons combine functional electrical stimulation (FES) and robotic assistance to restore and rehabilitate movement. Real-time control of FES parameters is necessary to maximize outcomes. Recently, muscle deformation captured by ultrasound imaging has been demonstrated as an effective human machine interface. Here, we examine if ultrasound imaging can track joint kinematics in the presence and absence of FES to assess its viability for real-time control of stimulation parameters. Muscle deformation from ultrasound was correlated to limb movement using a simple image similarity metric. One healthy participant performed volitional and FES-driven wrist, ankle, and knee flexion/extension while simultaneous motion capture, surface electromyography, and ultrasound were collected. Ultrasound imaging tracked joint kinematics with and without FES with mean errors of 1.7 ± 20.7% and 3.9 ± 18.1%, respectively, averaged across all three joints. Our results demonstrate the feasibility of ultrasound to track stimulation driven movement and potentially adjust FES parameters in real-time.