The help4mood wearable sensor network for inconspicuous activity measurement

The Help4Mood EU FP7 project (H4M) [1] proposes to significantly advance the state-of-the-art in computerized support for people with Major Depression by monitoring mood, physical activity and voice characteristics while promoting activities in reaction to examined inputs. Employing actigraphy can provide supplementary data about patients with depression. Nonetheless, its use is not standardized and there is a lack of public analyses about treated patients with depression using this technique, which is the objective of the project. The purpose of the Personal Monitoring System (PMS) used in H4M is to compile objective data about the changes and trends of activity patterns during long periods of time. This would comprise daily activity, rest time and, if possible, sleep quality. The PMS uses inconspicuous methods but keeping the cost associated with sensor installation at the patient¿s home to a minimum. This work focuses on the Wireless Sensor Network (WSN) enhancements introduced after real testbeds and considering User Quality of Experience (QoE), mainly oriented to reduce energy consumption and required data transmission and consequently improving the autonomy and range of the sensors.