Title: Architecture and design of real-time system for elderly health monitoring

Authors: Achraf Ben Ahmed; Abderazek Ben Abdallah

Addresses: Graduate School of Computer Science and Engineering, Adaptive Systems Laboratory, University of Aizu, Fukushima-ken, Aizu-Wakamatsu-shi 965-8580, Japan ' Graduate School of Computer Science and Engineering, Adaptive Systems Laboratory, University of Aizu, Fukushima-ken, Aizu-Wakamatsu-shi 965-8580, Japan

Abstract: Despite the decreased human mortality rate, heart disorders are one of the main causes of death around the world. As a result, detection of irregularities in the rhythms of the heart is a growing concern in medical researches. The collection, processing, and visualisation of such biomedical data in real-time is a challenging task due to the large amounts of data that need to be processed, especially when the records are made for a long time. Recent technological advances in sensors and low-power microelectronics enabled the development of a single embedded biomedical chip capable of running computationally intensive biomedical applications, such as remote analysis and monitoring of human heart activity, which is still a challenging problem for biomedical engineers. In this work, we present a novel architecture and hardware/software prototyping of a real-time system, targeted for elderly health monitoring, named BANSMOM. The proposed system achieves its real-time performance via parallel processing techniques and a period-peak-detection algorithm (PPD) for processing multi-lead electrocardiography records in parallel. We tested the proposed system with real ECG fixed length records (10 s/sample) from the MIT database. From the evaluation results, we found that the system meets its real-time requirements and achieves about 69% accuracy.

Keywords: multi-core system-on-chip; MCSoC; embedded systems; real-time monitoring; hardware/software prototyping; parallel.

DOI: 10.1504/IJES.2017.086718

International Journal of Embedded Systems, 2017 Vol.9 No.5, pp.484 - 494

Received: 19 Nov 2013
Accepted: 02 Mar 2014

Published online: 24 Sep 2017 *

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