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Mood Detection and Memory Performance Evaluation with Body Sensors

Authors:
Jonathan Bohbot
Zeljko Zilic

Keywords: Mood Detection, Brain Waves, Heart Rate Variability, Body Sensors, Android Application

Abstract:
This paper provides the design of a system employing an Android application connected to body sensors, which is capable of assessing the mood and memory performance of humans. The mood detection is based on the heart rate, its variability, as well as on the captured brain waves. The memory performance is evaluated based on specific brain waves observed as well. Experiments were conducted to assess the main features of the system. The mood experiment has been successful at raising the mood levels of the majority of participants when being shown stimuli composed of images and sounds. Negative or neutral mood levels could be explained by participants having other thoughts or emotions during the experiment, and by the attenuation and dampening of the body sensors' signals. The ability of participants to reach a particular mood (relaxed, engaged, and sad) more quickly in response to a conducive stimulus is related to a person's physical characteristics; for example, younger participants reach a particular mood more quickly than older participants. The memory experiment has been successful at raising the memory levels of the majority of participants when being asked to perform a modified Sternberg memory task. Results show a positive memory activity for the majority of participants, even in the presence of signal attenuation in the body sensors.

Pages: 62 to 68

Copyright: Copyright (c) IARIA, 2017

Publication date: March 19, 2017

Published in: conference

ISSN: 2308-4359

ISBN: 978-1-61208-540-1

Location: Nice, France

Dates: from March 19, 2017 to March 23, 2017