通过打字行为、智能手机传感器和机器学习技术进行急性应激检测

Objectives: To examine whether acute stress can be recognised from smartphone typing behaviour and device motion without wearable sensors, and to identify the classifier family best suited to such data. Method: A browser-based application recorded keystroke events together with accelerometer and gyroscope readings (2 Hz) while 288 participants typed simple number series (calm condition) and mental-arithmetic sequences (stress condition), yielding 2,016 samples. Five keystroke timing features and the inertial features were combined, and ten supervised classifiers were trained and tested on the