9th International Conference on Pervasive Computing Technologies for Healthcare

Research Article

A Fault-Tolerant Hardware Architecture for Robust Wearable Heart Rate Monitoring

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  • @INPROCEEDINGS{10.4108/icst.pervasivehealth.2015.259289,
        author={Qingkun Li and Homa Alemzadeh and Zbigniew Kalbarczyk and Ravishankar Iyer},
        title={A Fault-Tolerant Hardware Architecture for Robust Wearable Heart Rate Monitoring},
        proceedings={9th International Conference on Pervasive Computing Technologies for Healthcare},
        publisher={IEEE},
        proceedings_a={PERVASIVEHEALTH},
        year={2015},
        month={8},
        keywords={heart rate monitor reconfigurable architectures fault tolerance biomedical monitoring wearable monitoring},
        doi={10.4108/icst.pervasivehealth.2015.259289}
    }
    
  • Qingkun Li
    Homa Alemzadeh
    Zbigniew Kalbarczyk
    Ravishankar Iyer
    Year: 2015
    A Fault-Tolerant Hardware Architecture for Robust Wearable Heart Rate Monitoring
    PERVASIVEHEALTH
    ICST
    DOI: 10.4108/icst.pervasivehealth.2015.259289
Qingkun Li1, Homa Alemzadeh1,*, Zbigniew Kalbarczyk1, Ravishankar Iyer1
  • 1: Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL, USA
*Contact email: alemzad1@illinois.edu

Abstract

This paper presents a fault-tolerant hardware architecture for robust wearable heart rate monitoring. The proposed architecture is designed for fusion of the heart rates estimated from both electrocardiogram (ECG) and arterial blood pressure (ABP) signals, with small hardware footprint and low energy consumption. It benefits from the following unique features: (1) an optimized heart beat (peak) detection algorithm that can be dynamically configured for either ECG or ABP analysis, resulting in about 38% reduction of the hardware footprint, (2) coarse-grained reconfigurable functional units (FUs) that can be programmed for different processing flows, and (3) a low overhead fault detection and recovery unit that enables dynamic recovery from transient hardware faults in the FUs. Both FPGA and ASIC prototypes of the proposed hardware have achieved much better performance and energy efficiency compared to an Android implementation of the same algorithm, and can recover from transient faults with low resource (~15%) and energy (~34%) overheads and no (0%) performance impact.