We propose Long Short-Term Memory (LSTM) to decode the two classes of mental stress based on the fNIRS time series. Five-fold cross validation, two LSTM layers, ...
Abstract— Mental stress is a significant factor in the development of a wide variety of psychological, emotional, behavioral, and physical illnesses.
Jan 30, 2023 · PDF | On Oct 9, 2022, Rateb Katmah and others published Mental Stress Assessment Using fNIRS and LSTM | Find, read and cite all the research ...
We propose Long Short-Term Memory (LSTM) to decode the two classes of mental stress based on the fNIRS time series. Five-fold cross validation, two LSTM layers, ...
In this paper, we review the existing EEG signal analysis methods on the assessment of mental stress. The review highlights the critical differences between ...
Sep 12, 2024 · This paper presents a comprehensive portable and real-time biofeedback system that aims at boosting stress management and consequently performance enhancement.
Jul 1, 2024 · Experiment results showed that the proposed fusion of EEG and fNIRS measurements improves the classification accuracy of mental stress by +3.4% ...
This work classifies cognitive states as a mental task or resting states using fNIRS. Topographical brain images are generated for 2s window with 1s ...
Our study suggests that combination of EEG (frontal alpha rhythm) and fNIRS (concentration change of oxygenated hemoglobin) could be a potential means to ...
Missing: LSTM. | Show results with:LSTM.
May 9, 2024 · This review paper emphasizes the application of Deep Learning (DL) techniques for classifying mental stress using EEG data.