Using Wearable Sensors for Gait Analysis: Measurement Accuracy for Linear Measurements

Measurement and analysis of human movement are necessary in a broad range of clinical, sports performance, and artistic applications. Historically, motion data were typically collected using optical motion capture systems. However, these systems are expensive and can only be used in lab spaces, which limits the range and speeds of human behavior. More recently, inexpensive, wearable sensors called Inertial Measurement Units (IMUs) have enabled motion measurement in natural settings, but these systems require validation before use. In this study, we evaluate measurement accuracy for linear displacements obtained using Sparkfun OpenLog Artemis IMUs. We conducted a series of tests, moving the sensor along predetermined distances in different directions and evaluating its ability to capture displacement accurately. IMU data were processed using custom MATLAB algorithms to calibrate, filter, and double-integrate acceleration data to obtain recorded linear displacements in all three planes of motion (e.g., x, y, and z axes). Our results indicated that the IMUs could not accurately measure linear displacements, with average measurement errors ranging from 22.5% to 83.7%. We also found that the degree of measurement error differed based on the direction of measurement for this device. These results indicate that additional calibration steps should be pursued before using these devices for clinical distance measurement. In the future, we will incorporate an assessment of device accuracy to operating temperature and sensitivity settings, as well as inter-device error variation. This research is part of a larger series of IMU validation experiments that, if successful, will enable inexpensive IMU-based measurement of human motion with a broad range of applications.