Detection of Episodes of Major Depression in Older Adults through Physiological Markers and Movement Patterns

This paper presents the design of a Detection System Crisis Episodes of depression in older adults. The system allows monitoring wirelessly through two modules: movement patterns and physiological markers of the patient. The first module is open technology based as is Raspberry Pi and Open CV to process images to identify movement patterns. The second module uses an Arduino pro mini with temperature and pulse sensor to logging information of the physiological data (heart rate and temperature). The information obtained is processed on a Web server through an application for viewing in a Web page or mobile device. With this information the attending physician or can correlate the variability of heart rate, temperature and movement pattern and determine by monitoring the state of the Depression in Elderly. This system is designed to send alert messages via MSN to physician and family in emergency situations such as extreme temperatures, irregular heartbeat, and absence or excess movement.