Detection-of-Depression-Using-Late-Fusion-of-Sequential-Actigraphy-Features

Analyzed time-series data (Depressjon) to detect depression from patient activity recorded via clinical actigraphy watches. Utilized features such as time domain, statistical metrics, and LSTM-extracted attributes.

Done under the supervision of Dr. Anshika Arora & Ankur Maurya (Assistant Professors at Bennett University)

Dataset :

https://datasets.simula.no/depresjon/