Energy-Efficient Assessment of Physical Activity Level Using Duty-Cycled Accelerometer Data

This paper describes an energy efficiency improvement of the IMA accelerometer-based method for estimating the level of physical activity of a person. The sensor sampling and data processing requirements are significantly reduced by duty-cycling sensor sampling, thus making implementation and long-lasting operation possible on resource-constrained devices as sensor nodes. By duty-cycling, the system maintains adequate bandwidth, while still reducing the effective number of samples taken per unit of time. We analyze in detail the impact of duty-cycling on the accuracy of the method and show that we can reduce the duty-cycle to as little as 10%, incurring a mean error of only about 4%. This translates into energy saving of up to 60% on the sensor node.