GroupCoach: Compressed Sensing Based Group Activity Monitoring and Correction

Group activities like group dance, military parade, or radio gymnastics have excellent ornamental value with its grand scale and uniform movements, while it also introduces difficulties in practice for coaches to monitor and correct the movements and locations of each participator. Wireless body area network (WBAN) is a promising direction for accurate motion tracking in large-scale group activities. Light-weight sensors can be deployed on participant bodies and transmit motion and channel sensing data through wireless spectrum for further analysis. To keep the high quality of service (QoS) of the WBAN on group activity monitoring and correction, three aspects should be achieved by careful designing: (i) less energy consumption; (ii) higher analysis accuracy; and (iii) lower feedback latency. Due to the low-rankness of motion and channel sensory data, we propose GroupCoach, a Compressed Sensing (CS) based group activity monitoring and correction system. The data is collected and reconstructed by CS, where the spatial and temporal stabilities of group activities are explored for a higher reconstruction accuracy. These reconstructed sensory data are further compared with their anchor values for faulty movement detection and correction. The channel attenuation caused by body shielding is reduced by a near-to-far diffusion model with the consideration of the body impact factor. The correction suggestions are finally fed back to sensors for guidance. Evaluations based on the prototype deployed on real group activity participators prove the high QoS of the GroupCoach. It achieves low sensor energy consumption, high data reconstruction accuracy, accurate faulty motion detection and correction, together with fast alert.