Gesture Recognition using Hidden Markov Models

This project presents an approach for recognizing and classifying different arm motion gestures by using IMU sensor readings from gyroscopes and accelerometers to train a set of Hidden Markov Models, which gives the result as log-likelihood for each class and the class with the highest likelihood is chosen as the result.

The data format of the IMU readings collected from consumer mobile device is:

ts	Ax Ay Az	Wx Wy Wz
Time (ms)	3x Accelerometer (m/s2)	3x Gyroscope (rad/s)