Home // CENTRIC 2023, The Sixteenth International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services // View article

Towards a Minimalistic Stress Classification Method Based on HRV

Authors:
Roswitha Duwenbeck
Elsa Andrea Kirchner

Keywords: Heart rate variability; stress prediction; Machine Learnin

Abstract:
Stress is a feeling of emotional and physical tension, that poses as a risk factor in many diseases, for example the nervous, musculoskeletal, cardiovascular or gastrointestinal system. Fast and easy detection could be a first step in order to help people manage their stress-levels. This paper depicts an ongoing work in the domain of stress prediction with Heart Rate Variability related features by classifying two different levels on the Stress-Predict Dataset. The performance of different classifiers was tested with Leave-One-Subject-Out Cross Validation and compared to each other. The best performance was reached with the Aggregated Mondrian Forest Classifier and a mean balanced accuracy of 97.87%

Pages: 52 to 56

Copyright: Copyright (c) IARIA, 2023

Publication date: November 13, 2023

Published in: conference

ISSN: 2308-3492

ISBN: 978-1-68558-100-8

Location: Valencia, Spain

Dates: from November 13, 2023 to November 17, 2023