3 papers
cs.LG2025
Multimodal signal fusion for stress detection using deep neural networks: a novel approach for converting 1D signals to unified 2D images
Yasin Hasanpoor, Bahram Tarvirdizadeh, Khalil Alipour +1
This study introduces a novel method that transforms multimodal physiological signalsphotoplethysmography (PPG), galvanic skin response (GSR), and acceleration (ACC) into 2D image…
eess.IV2024
Continuous Wavelet Transformation and VGG16 Deep Neural Network for Stress Classification in PPG Signals
Yasin Hasanpoor, Bahram Tarvirdizadeh, Khalil Alipour +1
Our research introduces a groundbreaking approach to stress classification through Photoplethysmogram (PPG) signals. By combining Continuous Wavelet Transformation (CWT) with the p…
eess.SP2024
Real-Time Stress Detection via Photoplethysmogram Signals: Implementation of a Combined Continuous Wavelet Transform and Convolutional Neural Network on Resource-Constrained Microcontrollers
Yasin Hasanpoor, Amin Rostami, Bahram Tarvirdizadeh +2
This paper introduces a robust stress detection system utilizing a Convolutional Neural Network (CNN) designed for the analysis of Photoplethysmogram (PPG) signals. Employing the W…