The primary goal of this study was to determine body composition of two class of people using Bio-electrical Impedance Analysis (BIA). To execute this task, two class of subjects, each of fifteen members, were formed first. One of the class represented the poor working class people which was the target group and the other class represented average working people which was the control group of this thesis. Data from these two groups were compared where the data from the control group was used as reference. Data collection was done using Maltron Bioscan 920-2-P body composition analyzer. Two tests were performed namely – Full Body test and Real time test and further statistical analysis was done.
In this project our aim was to detect fatigue from human face. We based our research on Facial Action Coding System (FACS). We used the Python language in this project and used Open Computer Vision Library (OpenCV), machine learning library Dlib, and SciKitlearn library. We extracted features from a face and tried to determine the presence of fatigue based on those features. We used extended Cohn-Kanade face database and also faces from other subjects. We have published a paper on this work.