Cotton R James, Rogers John
IEEE Int Conf Rehabil Robot. 2019 Jun;2019:258-263. doi: 10.1109/ICORR.2019.8779538.
Simultaneous tracking of muscle activity and joint rotation is of significant interest in rehabilitation, but gold-standard methods with optical motion tracking and wireless electromyography recording typically restricts this to the laboratory setting. There has been significant progress using wear-able inertial measurement units (IMUs) for motion tracking, but there are no systems that can easily be deployed to home and provide simultaneous electromyography. We addressed this gap by developing a flexible, wearable, Bluetooth-connected sensor that records both IMU and EMG activity. The sensor runs an efficient quaternion-based complementary filter that estimates the sensor orientation while correcting for estimate drift and constraining magnetometer estimates to only influence heading. The difference in two sensor orientations is used to estimate the joint angle, which can be further improved with joint axis estimation. We demonstrate successful tracking of joint angle and muscle activity in a home environment with just the sensors and a smartphone.
在康复领域,同时跟踪肌肉活动和关节旋转具有重大意义,但采用光学运动跟踪和无线肌电图记录的金标准方法通常将其限制在实验室环境中。使用可穿戴惯性测量单元(IMU)进行运动跟踪已经取得了显著进展,但目前还没有能够轻松部署到家庭并同时提供肌电图的系统。我们通过开发一种灵活、可穿戴、蓝牙连接的传感器来填补这一空白,该传感器可记录IMU和肌电图活动。该传感器运行一种高效的基于四元数的互补滤波器,在纠正估计漂移并将磁力计估计约束为仅影响航向的同时,估计传感器方向。两个传感器方向的差异用于估计关节角度,通过关节轴估计可进一步改善该估计。我们展示了仅使用传感器和智能手机就能在家庭环境中成功跟踪关节角度和肌肉活动。