SADHealth : A E-Health Profile for Cataloging Life Statistics based on Light Exposure

Sammanfattning: Seasonal Affective Disorder or "Winter blues" is a problem that affects many individuals around the world. The afflicted typically have to arrange to see health care specialist who may require them to recall details which pertain to the symptoms encountered  in SAD. SADHealth represents  a solution which allows anyone to electronically record data that would be used in SAD diagnosis and avoid the problem of recalling details long past. Users simply download and install the application for Android smartphones through the Google Play store and the system will automatically collect the light, location, accelerometer  and weather data through the use of the built in hardware sensors on the phone while a questionnaire relies on electronic input of mood, sleep, energy and sociability data. SADHealth is the first unique application available which offers a simple to use user interface and informational graphs that enables the public with no idea of the medical terminology to understand, interpret  and use the collected data to their benefit by monitoring their behavior change and well being across seasons. The result is a system which is power efficient, stable, works on various android devices, fully integrated and connected into android's system applications and allows for exportation  of SAD related data as well as possibly improving both physical and mental health. SADHealth has proven to be able to expose the trends such as positive relationship between the light values recorded  outside and the reported  mood and energy. As well as confirming general intuitions about the relationships between sleep, energy and sociability. In addition to furthering SAD related research the system can also provide insight into user behavior and test new data collection features provided by Google engineers. Test users were found to provide more data samples during months with low light conditions and Google activity recognition system does not yet seem to be trustworthy  enough to be used in studies which choose to use activity recognition as a main driving component.