In the project, wearable electrical devices that could measure acceleration in real time were placed on humans. Each device produced a continuous signal of accelerometer data and by analyzing the signals it was possible to detect certain characteristics in the movement of the person wearing them. The result can be used to detect abnormal movement patterns that would indicate the person is not being well. Ongeas participated in the project by developing algorithms for pattern recognition for accelerometer data signals.