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System for Detection and Monitoring of Physical Activity through the Use of Accelerometers 

Abstract This work consists of a system for monitoring footsteps of a person, in order to determine characteristic and statistical parameters of their movement, in a non-invasive way. This is achieved by sensing the vibration of the floor of a room with the help of an accelerometer, the captured signal is analyzed by using neural networks that help to classify types or styles of walking and identify the person's gender, age, as well as their body mass index (BMI). Different signal parameters’ values help to obtain information from each study subject, which is stored in a database, so that with the implementation of classifiers, physical characteristics can be grouped, focusing on achieving diagnoses or identifications based on particular data. Finally, the results obtained from the tests performed on 30 different people are presented, in order to verify the accelerometer’s performance and the algorithm’s effectiveness.

Keywords— Capacitive accelerometer, vibration, artificial intelligence, footprint analysis, human activity. 

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