Abstract: A method and system for dynamic, non-obtrusive monitoring of locomotion of a person using wearable sensor units includes motion sensors arranged to generate a sensor signal, and a wearable communication unit configured to process the sensor signal using a signal processing unit to extract and transmit biometric data to a mobile device that can analyze it using a machine learning-based risk prediction algorithm to identify patterns related to falling and thereby identify a fall event or calculate risk of falling of the person.

Abstract: A method and device for optimizing running performance for an individual. Movements of a foot are monitored using one or more accelerometers. The data is transmitted to a portable electronic processing device, e.g. in the form of a cellular phone, where the data is processed to derive a movement pattern of the foot. Based on a comparison of the derived movement pattern and an optimal movement pattern, the portable electronic processing device provides feedback to the individual in order to adjust the movement pattern of the foot of the individual, thereby improving a running performance. Thereby the risk of injuries and overload of muscles, joints and tendons can be reduced.