Classification of Mental Stress Using CNN-LSTM Algorithms with Electrocardiogram Signals

The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation

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CNN and LSTM-Based Emotion Charting Using Physiological Signals

(2020) Muhammad Najam Dar et al.   SENSORS

A Comparison of Power Quality Disturbance Detection and Classification Methods Using CNN, LSTM and CNN-LSTM

(2020) Carlos Iturrino Garcia et al.   Applied Sciences-Basel

Car Driver's Sympathetic Reaction Detection Through Electrodermal Activity and Electrocardiogram Measurements

(2020) Pamela Zontone et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Identifying mental health status using deep neural network trained by visual metrics

(2020) Somayeh B. Shafiei et al.   Translational Psychiatry

Ambulatory and Laboratory Stress Detection Based on Raw Electrocardiogram Signals Using a Convolutional Neural Network

(2019) Hyun-Myung Cho et al.   SENSORS

Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals

(2018) Bosun Hwang et al.   Telemedicine and e-Health

Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals

(2018) Bosun Hwang et al.   Telemedicine and e-Health

Confusion-Matrix-Based Kernel Logistic Regression for Imbalanced Data Classification

(2017) Miho Ohsaki et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Experimentally Induced Stress Validated by EMG Activity

(2014) Rosan Luijcks et al.   PLoS One

A Human ECG Identification System Based on Ensemble Empirical Mode Decomposition

(2013) Zhidong Zhao et al.   SENSORS