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MAHNOB dataset for emotion recognition
The MAHNOB dataset is a collection of physiological signals (EEG, EDA, facial expressions, and speech) for emotion recognition. -
SEED dataset for emotion recognition
The SEED dataset is a collection of physiological signals (EEG, EDA, facial expressions, and speech) for emotion recognition. -
DEAP dataset for emotion recognition
The DEAP dataset is a collection of physiological signals (EEG, EDA, facial expressions, and speech) for emotion recognition. -
PMEmo dataset for emotion recognition
User independent emotion recognition with large scale physiologically signals is a tough problem. The PMEmo dataset is the currently largest dataset with EDA and music signals... -
Empatica E4 Dataset
The dataset used in the MHDeep framework, containing physiological signals and ambient information collected from wearable medical sensors. -
MHDeep Dataset
The dataset used in the MHDeep framework, containing physiological signals and ambient information collected from wearable medical sensors. -
SAKAMOTO: ULTRA-WIDEBAND RADAR AND WIRELESS HUMAN SENSING
The dataset used for radar-based human sensing and imaging, including wireless human body imaging techniques, human micro-Doppler measurements, and radar-based noncontact... -
UCSF Medical Center PPG Dataset
A large-scale dataset of photoplethysmography (PPG) signals from hospitalized intensive care patients. -
UCI HAR dataset
The dataset used in this study is the UCI HAR dataset, a collection of acceleration and velocity data from a smartphone's gyroscope. -
PhysioNet database
The PhysioNet database which consists of 3153 recordings, including 2488 normal and 665 abnormal cases.