Gesture Recognition Using Wearable Sensors With Bi-Long Short-Term Memory Convolutional Neural Networks

In this study, we propose a gesture recognition system that is applicable for controlling home appliances. We utilized sensors embedded inside common smart watches, such as accelerometers and gyroscopes, for alleviating the obtrusiveness to users. One-dimensional convolutional neural networks and bi-long short-term memory (1D-CNN-biLSTM) are proposed for analyzing, learning, and representing features from the sensor signals. In addition, a...