Date of Graduation

5-2015

Document Type

Thesis

Degree Name

Bachelor of Science in Electrical Engineering

Degree Level

Undergraduate

Department

Electrical Engineering

Advisor/Mentor

Wu, Jingxian

Abstract

Depression is a serious mental condition affecting many Americans and people across the world. Postpartum depression is a form of depression affecting women who have recently gone through childbirth. Postpartum depression can have serious symptoms that may affect not only the mother, but her newborn as well. Early detection of these symptoms is of critical importance to the welfare of the mother and her child. Many medical professionals express the need for postpartum screening being that treatment has proven to be very effective. This project aims to make early symptom detection convenient and reliable for mothers with newborns. This will be done be selecting measurable symptoms that can be detected using a variety of sensors contained in mobile “smart” phones, specifically Android-powered phones. An important aspect of this project is the selection of these symptoms and sensors. The focus of this project is motion detection and volume of conversations. These can be tracked using the microphone with a getMaxAmplitude filter function and the linear accelerometer. The Android Studio platform is the development tool used for this application. All data gathered by the phone sensors will be compiled using the application and sent to a server to be analyzed to provide warnings to the user about their potential for postpartum depression and urge them to consult a doctor.

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