Arrogyam: Arrhythmia Detection for Ambulatory Patient Monitoring

Abstract

Biomedical Sensor Networks are event driven systems that rely on collective efforts of several sensor nodes. These nodes are used for acquisition of physiological information to monitor health status and physical wellbeing of an individual specifically suffering from chronic diseases. The reliable event detection for such networks is based on multi-sensor data fusion. The physiological signals are multi-dimensional and multi-parametric in nature. The major objective of this paper is to discuss challenges and opportunities for developing an ambulatory patient monitoring system. The proposed prototype model addresses design and development issues required to report any severe condition related to cardiovascular malfunctioning without compromising mobility and convenience of the patient. The analysis of fused cardio-respiratory time series data requires dimensionality reduction before drawing detection decisions related to cardiac arrhythmia. This paper briefs about a simulation model of arrhythmia detection for ambulatory patient monitoring. The early detection of cardiovascular risk factors can reduce expected cost pressure on healthcare and enhance social security issues.