Telemedicine journal and e-health : the official journal of the American Telemedicine Association
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Case Reports
Long-term monitoring of heart rate, respiration rhythm, and body movement during sleep based upon a network.
A method for accurately recording heart rate (HR), respiration rhythm (RR), and body movement (BM) during sleep using a network-based system is proposed in this article. Its application to the long-term monitoring of HR, RR, and BM during sleep was examined. HR, RR, and BM were detected by pressure variations corresponding to changes in the heartbeat and respiratory motion, which were measured by a sensor unit placed beneath a pillow during sleep under completely unconstrained conditions. ⋯ Periodic biorhythms can also be assessed using the profiles of the average HR and certain frequency-domain parameters of HR variability. The rhythmic property of these profiles was confirmed to coincide with the subject's menstrual cycle. The results of this 13-month trial operation show that this system can be installed in the home environment; used to monitor HR, RR, and BM during sleep; and analyze various physiological rhythms in humans over prolonged periods.
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This work evaluates the feasibility of using 802.11 g ad hoc and 3G cellular broadband networks to wirelessly stream ultrasound video in real-time. Telemedicine ultrasound applications in events such as disaster relief and first-response triage can incorporate these technologies, enabling onsite medical personnel to receive assistance with diagnostic decisions by remote medical experts. The H.264 scalable video codec was used to encode echocardiographic video streams at various image resolutions (video graphics array [VGA] and quarter video graphics array [QVGA]) and frame rates (10, 15, 20, and 30 frames/s). ⋯ The transmitted ultrasound video streams were subsequently recorded and evaluated by physicians with expertise in medical ultrasonography who evaluated the diagnostic value of the received video streams relative to the original videos. They expressed the opinion that image quality in the case of both 802.11 g and 3G was fully to adequately preserved, but missed frames could momentarily decrease the diagnostic value. This research demonstrates that 3G and 802.11 g wireless networks combined with efficient video compression make diagnostically valuable wireless streaming of ultrasound video feasible.