Shoulder and Elbow Joint Angle Tracking With Inertial Sensors

Abstract

Wearable inertial systems have recently been used to track human movement in and outside of the laboratory. Continuous monitoring of human movement can provide valuable information relevant to individuals' level of physical activity and functional ability. Traditionally, orientation has been calculated by integrating the angular velocity from gyroscopes. However, a small drift in the measured velocity leads to increasing integration error over time. To compensate that drift, complementary data from accelerometers are normally fused into tracking systems using the Kalman or extended Kalman filter. In this study, we combine kinematic models designed for control of robotic arms with state-space methods to continuously estimate the angles of human shoulder and elbow using two wearable inertial measurement units. We use the unscented Kalman filter to implement the nonlinear state-space inertial tracker. Shoulder and elbow joint angles obtained from 8 subjects using our inertial tracker were compared to the angles obtained from an optical-tracking reference system. On average, there was an RMS angle error of less than 8° for all shoulder and elbow angles. The average correlation coefficient for all movement tasks among all subjects was r ≥ 0.95 . This agreement between our inertial tracker and the optical reference system was obtained for both regular and fast-speed movement of the arm. The same method can be used to track movement of other joints.

Wearable Sensing for Solid Biomechanics

“…Estimation errors of less than 3°and 12°were achieved, respectively, for upper-arm motion and forearm motion. Peppoloni et al [80] and ElGohary et al [81] also present similar ideas for kinematic analysis using wearable inertial sensors.…”

Compensation technique for environmental and light source power variations applied in a polymer optical fiber curvature sensor for wearable devices

“…This technique, however, is expensive, time-consuming, and limited to laboratory environment (El-Gohary and McNames, 2012). For these reasons, wearable and portable sensors have been proposed.…”

“…One of the most popular technologies are the inertial measurement units (IMUs) that comprise of tri-axial gyroscopes, accelerometers, and magnetometers. Sensor fusion algorithms provide the sensor interaction and complementary information (El-Gohary and McNames, 2012). IMUs are employed in many applications, such as timed-up and go tests (Coulthard et al, 2015), sit-stand and step-up transfer tests (Bolink et al, 2016), evaluation of kinematics and the capacity of post-stroke patients to grasp objects (Braidot et al, 2013).…”

“…IMUs are employed in many applications, such as timed-up and go tests (Coulthard et al, 2015), sit-stand and step-up transfer tests (Bolink et al, 2016), evaluation of kinematics and the capacity of post-stroke patients to grasp objects (Braidot et al, 2013). However, it presents high sensitivity with magnetic field interferences and need frequent calibration (El-Gohary and McNames, 2012). Other common devices are the potentiometers that usually need mechanical supports precisely assembled Compensation technique for environmental and light source power variations applied in a polymer optical fiber curvature sensor for wearable devices to the joint, which are a widely applied technology to measure angles in active orthosis and exoskeletons (Moreno et al, 2008;Villa-Parra et al, 2015).…”

The dynamics of the human arm with an observer for the capture of body motion parameters

“…The development of IMU measurement systems launched studies on the use of not one, but a set of such devices to acquire human motion [16,17]. This approach allows for unlimited motion parameter measurements regardless of where they occur.…”