Disclosed embodiments provide data augmentation techniques in which collected sensor data and simulated sensor data created by transforming collected sensor data are used to train a machine learning model (MLM), the MLM is then deployed on an integrated circuit chip of an embedded device, live sensor data received by the embedded device is then either transformed and input to the MLM or input to the MLM without transformation, and the MLM then performs a prediction by, for example, recognizing a gesture made by the user of the embedded device.