Mobile Health Monitoring Through Biotelemetry

Abstract

As the population ages and the risk of chronic disease increases, the cost of healthcare will rise. Technology for mobile telemetry could reduce cost and improve the efficiency of treatment. In order to achieve these goals, we first need to overcome several technical challenges, including sufficient system lifetime, high signal fidelity, and adequate security. In this paper we present the design, implementation, and evaluation of a Mobile Biotelemetric System (MBS) that addresses these remote medical monitoring challenges. MBS comprises a custom low-power sensor node that accurately collects and analyzes electrocardiogram (ECG) data, a client service with a multifaceted policy engine that evaluates the data, and a web portal interface for visualizing ECG data streams. MBS differs from other remote monitoring systems primarily in the policy engine's ability to provide flexible, robust, and precise system communication from end-to-end and to enable tradeoffs in metrics such as power and transmission frequency. We show that, given a representative set of ECG signals, policies can be set to make the operation of the hardware and software resilient against transient ECG conditions. Further, we incorporate state-of-the-art security practices to safeguard our data and foil common attacks.

A customizable framework of body area sensor network for rehabilitation

“…Numerous wearable sensor systems have been proposed for physical rehabilitation [13] [10], health monitoring [4] [14] [11] [15] [5], and kinetics studies [7] [8]. In this section, we review the existing literature on wearable sensor system designs from the perspective of system architecture, and in particular, the capability of system configuration.…”

MPCS: Mobile-phone based patient compliance system for chronic illness care

“…Recently, there is increasing interest in using mobile phones and wearable sensors for remote health monitoring [39], [17], [23]. On the other hand, using mobile technology to improve patient compliance is still an emerging research area.…”

Development of a Mobile Phone Based e-Health Monitoring Application

“…A typical ECG signal of a normal heartbeat can be divided into 3 parts, as depicted in Figure 3 [12], P wave or P complex, which indicates the start and end of the atrial depolarization of the heart; the QRS complex, which corresponds to the ventricular depolarization; and, finally, T wave or T complex, which indicates the ventricular depolarization [13] [14]. QRS complex can be identified using general ECG parameter detection method.…”