Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

Abstract

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error).

Classification of grasping tasks based on EEG-EMG coherence

“…CMC was also developed in the same field and mainly used to investigate motor tasks where different levels of force were exerted and when contraction was dynamically changed [11]. On the other hand, the most common approach in the engineering and robotics communities made use of inertial sensors (gyroscopes and accelerometers) to track several limb joints during the movement and, throughout a reconstruction of all body segments, the classification was performed [12].…”

Inertial sensor-based centripetal acceleration as a correlate for lateral margin of stability during walking and turning

“…Inertial sensors, comparatively, can provide accurate acceleration, angular velocity, and orientation estimates, but struggle to provide accurate positional distances from one sensor to another. To rectify this issue, static calibration poses and subject-specific anthropometric dimensions have been used to establish initial positions of each sensor [21,22]. However, requiring the subject to hold a neutral pose for calibration before every data capture may not be a viable solution for continuous monitoring in free-living conditions.…”

Magnetic Condition-Independent 3D Joint Angle Estimation Using Inertial Sensors and Kinematic Constraints

“…reference, forming an inertial and magnetic measurement unit (IMMU). Last two decades, much progress has been made in joint angle estimation using IMUs or IMMUs [1,2,5,[7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25].Seel et al[7] estimated the flexion/extension angles of the knee and ankle during walking based on IMUs because the flexion/extension is the rotation around one dominant axis of the joint. El-Gohary and McNames [8] presented an unscented Kalman filter (UKF) incorporated with a kinematic arm model to track the shoulder and elbow joint angles using IMUs.…”