Detection of Behavioral Data Based on Recordings from Energy Usage Sensor

Monitoring of human behavior in the natural living habitat requires a hidden yet accurate measurement. Several previous attempts showed, that this can be achieved by recording and analysing interactions of the supervised human with sensorized equipment of his or her household. We propose an imperceptible single-sensor measurement, already applied for energy usage profiling, to detect the usage of electrically powered domestic appliances and deduct important facts about the operator’s functional health. This paper proposes a general scheme of the system, discusses the personalization and adaptation issues and reveals benefits and limitations of the proposed approach. It also presents experimental results showing reliability of device detection based on their load signatures and areas of applicability of the load sensor to analyses of device usage and human performance.