The Effect of Sensor Feature Inputs on Joint Angle Prediction across Simple Movements

TL;DR

This study investigates how adding more inertial measurement units (IMUs) affects the accuracy of predicting joint angles during simple movements.

Contribution

The study provides empirical evidence that adding adjacent or non-adjacent IMUs does not significantly improve joint angle prediction accuracy.

Findings

Adding adjacent IMUs did not significantly improve joint angle prediction accuracy (RMSE comparisons at ankle, knee, and hip).

Including non-adjacent IMUs also did not improve prediction accuracy (RMSE comparisons at ankle, knee, and hip).

Future joint angle prediction during simple movements does not benefit from additional IMUs alongside current joint angle inputs.

Abstract

The use of wearable sensors, such as inertial measurement units (IMUs), and machine learning for human intent recognition in health-related areas has grown considerably. However, there is limited research exploring how IMU quantity and placement affect human movement intent prediction (HMIP) at the joint level. The objective of this study was to analyze various combinations of IMU input signals to maximize the machine learning prediction accuracy for multiple simple movements. We trained a Random Forest algorithm to predict future joint angles across these movements using various sensor features. We hypothesized that joint angle prediction accuracy would increase with the addition of IMUs attached to adjacent body segments and that non-adjacent IMUs would not increase the prediction accuracy. The results indicated that the addition of adjacent IMUs to current joint angle inputs did not significantly increase the prediction accuracy (RMSE of 1.92° vs. 3.32° at the ankle, 8.78° vs. 12.54° at the knee, and 5.48° vs. 9.67° at the hip). Additionally, including non-adjacent IMUs did not increase the prediction accuracy (RMSE of 5.35° vs. 5.55° at the ankle, 20.29° vs. 20.71° at the knee, and 14.86° vs. 13.55° at the hip). These results demonstrated how future joint angle prediction during simple movements did not improve with the addition of IMUs alongside current joint angle inputs.

Figures