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This paper examines the challenges of using electrocardiogram (ECG) monitoring in wearable computing systems for addressing drowsiness detection while driving. The approaches for extrapolating a person's waking/sleeping state using time-series data is provided and verified against real ECG data available from the PhysioBank data archives. A system incorporating an off-the-shelf wearable ECG monitor...
The identification of invalid data in recordings obtained using wearable sensors is of particular importance since data obtained from mobile patients is, in general, noisier than data obtained from nonmobile patients. In this paper, we present a signal quality index (SQI), which is intended to assess whether reliable heart rates (HRs) can be obtained from electrocardiogram (ECG) and photoplethysmogram...
A robust medical monitoring device should be able to provide intelligent diagnosis based on accurate analysis of physiological parameters in real-time. At the same time, such device must be able to adapt to the characteristics of a specific patient and desired diagnostic needs, and continue to operate even in presence of unexpected artifacts and accidental errors. A reconfigurable architecture is...
Intensive Care Unit (ICU) false alarm rates can be as high as 86%, leading to a desensitization of the clinical attending staff, slowing of response times and even ignoring true alarms. False alarms are commonly caused by single channel artifacts and could be avoided if information from other independent signals were fused to form a more robust hypothesis of the etiology of the alarm. We used a standard...
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