An Adaptable Inertial Sensor Fusion-Based Approach for Energy Expenditure Estimation

Abstract

Using multiple inertial sensors for energy expenditure estimation provides a useful tool for the assessment of daily life activities. Due to the high variety of new upcoming sensor types and recommendations for sensor placement to assess physiological human body function, an adaptable inertial sensor fusion-based approach is mandatory. In this paper, two inertial body sensors, consisting of a triaxial accelerometer and a triaxial gyroscope, were placed on hip and ankle. Ten subjects performed two trials of running on a treadmill under three speed levels ([3.2, 4.8, 6.4] km/h). Each sensor source was separately subjected to preprocessing, feature extraction and regression. In the final step, decision level fusion was performed by averaging the predicted results. A mean absolute error of 0.50 MET was achieved against indirect calorimetry. The system allows an easy integration of new sensors without retraining the complete system. This is an advantage over commonly used feature level fusion approaches.