Low-Cost, Home-Oriented Neuro-Patient Monitoring: Towards an Information Geometry Based Manifold Assembly for Gait Irregularity and Disorder Capture (ItMAGIC)

Despite the extremely high medical cost of neuro-disorder diseases (NDDs), up to this point we still rely on labor-intensive observations to determine neuro-disorder symptoms. Therefore, it is critical to design a gait anomaly and motor disorder (GAMD) recognition system for accurate capture of NDD symptoms. Such an automatic GAMD monitoring system has to be low-cost, and uses highly motion-sensitive sensors and accurate GAMD pattern recognition algorithms. In this chapter we have introduced our low-cost, home-oriented system architecture that aims to monitor neurodisorder patients. Our system can be used for both daytime and nighttime patient motion disorder monitoring, and link those motor disorders to specific neuro diseases. The three major contributions of this research are: (1) Adaptive determination of GAMD observation window size via on-line signal segmentation; (2) Nighttime motor disorder capture through multi-manifold fusion and learning; and (3) Daytime accurate capture of abnormal gaits through delicate signal pattern analysis. We also proposed to use both in-lab and practical clinical test to study the performance of the low-cost, home-oriented neuro-disorder monitoring platform the ItMAGIC mechanisms. Low-Cost, Home-Oriented Neuro-Patient Monitoring: Towards an Information Geometry Based Manifold Assembly for Gait Irregularity and Disorder Capture (ItMAGIC)

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