Multi-sensor integration and data fusion for enriching gait assessment in and out of the laboratory

This paper deals with the design of a wearable multi-sensor system (INDIP) that exploits a synergistic integration of different sensor types to provide a “best available” solution for digital gait assessment in real world scenarios. The system includes in its full bilateral configuration 2 Magneto-IMU, 4 distance sensors and 2 plantar pressure insoles. Multi-sensor selection was operated to take full advantage of complementary characteristics of each sensing technology to obtain a richer set of information to enhance gait assessment. For instance, thanks to the use of distance sensors, foot displacements estimated from the inertial data can be supplemented with information on foot clearance and inter-shank distance. Finally, geolocation techniques can be easily integrated via BLE to correlate gait variables with contextual factors.