Sensor systems for gesture recognition

Gesture recognition (GR) aims to interpret human gestures, having an impact on a number of different application fields. This Special Issue is devoted to describing and examining up-to-date technologies to measure gestures, algorithms to interpret data, and applications related to GR. These technologies involve camera-based systems (e.g., ground truth system, GTS; Azura Kinect), wearable sensors (e.g., inertial measurement units, IMUs; micro electro-mechanical systems, MEMS; angular displacement sensors, ADS; resistive flex sensors, RFSs), electromagnetic field measurements (e.g., leap motion sensor), acoustic-based inputs (e.g., microphone, stethoscope), radar systems (e.g., continuous wave), and tactile sensors (e.g., pressure sensitive transistors). Data interpretations are detailed by means of classifiers (e.g., neural networks, NN; convolutional neural network, CNN; hidden Markov models, HMM; and k-nearest neighbors, kNN).