There are 0 repository under stress-detector topic.
Voice stress analysis (VSA) aims to differentiate between stressed and non-stressed outputs in response to stimuli (e.g., questions posed), with high stress seen as an indication of deception. In this work, we propose a deep learning-based psychological stress detection model using speech signals. With increasing demands for communication between humans and intelligent systems, automatic stress detection is becoming an interesting research topic. Stress can be reliably detected by measuring the level of specific hormones (e.g., cortisol), but this is not a convenient method for the detection of stress in human- machine interactions. The proposed algorithm first extracts Mel- filter bank coefficients using pre-processed speech data and then predicts the status of stress output using a binary decision criterion (i.e., stressed or unstressed) using CNN (Convolutional Neural Network) and dense fully connected layer networks.
API to detect if user is stressed or not using ML.
StressNet: Detecting Stress in Thermal Videos. StressNet introduces a fast and novel algorithm of obtaining physiological signals and classify stress states from thermal videos.
API to detect Stress through real-time facial recognition using Deep learning and CNN
Demo of a "Stress Display" using Chrome Bluetooth. Reads Heart-rate data, and displays "stress" colors to a smart bulb. (Uses a SBT5007 smart bulb)
Human Stress Detection project utilizes machine learning techniques to detect stress in an individual