Performance evaluation of a tri-axial accelerometry-based respiration monitoring for ambient assisted living

Ambient assisted living (AAL) technology is often proposed as a way to tackle the increasing cost of healthcare caused by population aging. However, the sensing technology for continuous respiratory monitoring at home is lacking. Known approaches of respiratory monitoring are based on measuring either respiratory effect, e.g. tracheal sound recording by a bio-acoustic sensor, or respiratory effort, e.g. abdomen movement measurement by a tri-axial accelerometer. This paper proposes a home respiration monitoring system using a tri-axial accelerometer. Three different methods to extract a single respiratory signal from the tri-axial data are proposed and analyzed. The performance of the methods is evaluated for various possible respiration conditions, defined by the sensor orientation and respiration-induced abdomen movement. The method based on principal component analysis (PCA) performs better than selecting the best axis. The analytical approach called full angle shows worse results than the best axis when the gravity vector is close to one of the sensor's axes

ИСТОРИЯ ІІ МИРОВОЙ: МЕЖДУ СКИЛЛОЙ РЕВИЗИОНИЗМА И ХАРИБДОЙ СТЕРЕОТИПОВ, В ПЛЕНУ АКТУАЛЬНОСТИ

В статті аналізується висвітлення в сучасній історіографії пострадянських країн низки проблемісторії ІІСвітової війни, насамперед концепції ревізіоністського характеру, та дається оцінка їхньої обґрунтованості.This article analyzes coverage of contemporary historiography of post-Soviet countries, a number of problems in the history ofWorldWar II, especially the concept of a revisionist nature, and assesses their validity

Performance evaluation of a tri-axial accelerometry-based respiration monitoring for ambient assisted living

Ambient assisted living (AAL) technology is often proposed as a way to tackle the increasing cost of healthcare caused by population aging. However, the sensing technology for continuous respiratory monitoring at home is lacking. Known approaches of respiratory monitoring are based on measuring either respiratory effect, e.g. tracheal sound recording by a bio-acoustic sensor, or respiratory effort, e.g. abdomen movement measurement by a tri-axial accelerometer. This paper proposes a home respiration monitoring system using a tri-axial accelerometer. Three different methods to extract a single respiratory signal from the tri-axial data are proposed and analyzed. The performance of the methods is evaluated for various possible respiration conditions, defined by the sensor orientation and respiration-induced abdomen movement. The method based on principal component analysis (PCA) performs better than selecting the best axis. The analytical approach called full angle shows worse results than the best axis when the gravity vector is close to one of the sensor's axes

Predicting Neurally Mediated Syncope Based on Pulse Arrival Time: Algorithm Development and Preliminary Results

Prediction of Neurally Mediated Syncope. Background: Neurally mediated syncope (NMS) is a common disorder that is triggered by orthostatic stress. The circulatory adjustments to orthostatic stress occur just prior to a sudden loss of consciousness. NMS prediction would protect patients from falls or accidents. Methods and Results: Based on simultaneously recorded heart rate (HR) and pulse wave during 70° head‐up tilt (HUT) table testing we investigated a syncope warning system. In 14 patients with a history of suspected NMS we tested 2 algorithms based on HR and/or pulse arrival time (PAT). When the cumulative risk exceeded the threshold, which was calculated during the first 2 minutes following the posture change to upright position, a syncope prediction alarm was triggered. All syncopes (n = 7) were detected more than 16 seconds before the onset of dizziness or unconsciousness by using a prediction alarm based on HR and PAT (syncope prediction algorithm 2). No false alarm was generated in patients with negative HUT (n = 7). Syncope prediction was improved by detecting the slope of HR changes as compared with monitoring PAT changes alone (syncope prediction algorithm 1). The duration between the prediction alarm and the occurrence of syncope was 99 ± 108 seconds. Conclusion: Predicting NMS is feasible by monitoring HR and the onset of the pulse wave at the periphery. This approach might improve NMS management. </p