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Falls by the elderly are highly detrimental to health, frequently resulting in injury, high medical costs, and even death. Using a MEMS-based sensing system, algorithms are being developed for detecting falls and monitoring the gait of elderly and disabled persons. In this study, wireless sensors utilize Zigbee protocols were incorporated into planar shoe(More)
Heart and respiration rates can be wirelessly measured by extracting the phase shift caused by the periodic displacement of a patient's chest wall. We have developed a phased-array Doppler-based non-contact vital sign (NCVS) sensor capable of long-term vital signs monitoring using an automatic patient tracking and movement detection algorithm. Our NCVS(More)
Doppler-based non-contact vital signs (NCVS) sensor systems can monitor the heart and respiration rates without touching the patient, but the accuracy of the NCVS sensing can be degraded considerably by background clutters and movements artifacts from the monitored subject or other motions in the measurement environment. We have, therefore, developed a high(More)
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