Estimation of Human Body Vital Signs Based on 60 GHz Doppler Radar Using a Bound-Constrained Optimization Algorithm.

In this study, a bound-constrained optimization algorithm is applied for estimating physiological data (pulse and breathing rate) of human body using 60 GHz Doppler radar, by detecting displacements induced by breathing and the heartbeat of a human subject. The influence of mutual phasing between the two movements is analyzed in a theoretical framework and the application of optimization algorithms is proved to be able to accurately detect both breathing and heartbeat rates, despite intermodulation effects between them. Different optimization procedures are compared and shown to be more robust to receiver noise and artifacts of random body motion than a direct spectrum analysis.

Exploring various orientation measurement approaches applied to a serious game system for functional rehabilitation.

Serious games have been established as a complementary tool for conventional rehabilitation. This trend proved to be beneficial for both experts and patients since the first are able to assign and monitor virtual reality games for their patients to be executed at home, and the latter are greatly motivated by the challenges of these games rather than the repeatable and boring rehabilitation movements. In a previous work, we proposed a serious game for lower limb rehabilitation of the musculoskeletal system using the Microsoft KinectTM camera and a virtual environment.

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements.

Exergames have been proposed as a potential tool to improve the current practice of musculoskeletal rehabilitation. Inertial or optical motion capture sensors are commonly used to track the subject's movements. However, the use of these motion capture tools suffers from the lack of accuracy in estimating joint angles, which could lead to wrong data interpretation.