Medical & Healthcare CPS

medicalCPS_AsthmaGuide

To achieve the important aims of identifying and marking disease progression, cell counting is crucial for various biological and medical procedures, especially in a Point-Of-Care (POC) setting. In contrast to the conventional manual method of counting cells, a software-based approach provides improved reliability, faster speeds, and greater ease of use. We present a novel software-based approach to count in-line holographic cell images using the calculation of a normalized 2D cross-correlation. …

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Assessing upper-limb motor function impairment, such as Fugl-Meyer Assessment (FMA), is a critical aspect of rehabilitation after neurological disorders. The assessment typically takes long time (about 30 minutes for FMA) for clinician to perform on a patient, which is a severe burden in a clinical environment. In this paper, we propose a framework for automating the assessment that uses low-cost sensors to collect movement data. The sensor data is then processed through a machine learning …

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AsthmaGuide is a smartphone and cloud based asthma system in which a smart phone is used as a hub for collecting a comprehensive collection of information. The data, including data over time, is then displayed in a cloud web application for both patients and healthcare providers to view. AsthmaGuide also provides an advice and alarm infrastructure based on the collected data and parameters set by healthcare providers. With these components, AsthmaGuide provides a comprehensive ecosystem …

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Sleep plays an important role in recovering physical and metal functions. In this research, we focused on two research topics. First research topic is tracking sleep positions by wearable sensors. most of existing sleep trackers merely show quantitative information about sleep patterns and duration at each sleep stage overlooking the importance of sleep positions upon sleep qualities. To have sound sleep, one has to avoid bad sleep positions associated with health conditions such as obstructive sleep¬†…

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Smart watches are increasingly being used in various applications to monitor heart rate for exercise and health care purposes. It is crucial that the readings from these devices are accurate so that users can take proper actions according to the intensity of the heart rate. Taking actions from inaccurate readings can negatively impact the health of the user. In this work, we run a preliminary study that verifies the accuracy of wearable platforms by comparing the measurements with a clinically-grade device.

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