This paper addresses the issue of low-power posture and gesture recognition in indoor or outdoor environments without any additional equipment. For applications based on predefined postures such as environment control and physical rehabilitation, we show that low cost and fully distributed solutions, that minimize radio communications, can be efficiently implemented. Considering that radio links provide distance information, we also demonstrate that the matrix of estimated inter-node distances offers complementary information that allows for the reduction of communication load. Our results are based on a simulator that can handle various measured input data, different algorithms and various noise models. Simulation results are useful and used for the development of real-life prototype.

A body network of Inertial Measurement Units (IMUs) is a well known solution for posture recognition based on accelerometer and magnetometer data fusion. However sensors and especially the magnetometer can be disturbed by the environment. Considering a Wireless Body Sensor Network (WBSN), we propose to use available radio received power measurements as an alternative to the magnetometer. We show with simulation and real data, that the radio signal used for WBSN communications can also provide useful location information despite highly noisy Received Signal Strength Indications (RSSI). We propose a solution for the static case that leads to a very simple yet Efficient algorithm.