7th International Conference on Body Area Networks

Research Article

Design of Energy Efficient and Dependable Health Monitoring Systems under Unreliable Nanometer Technologies

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  • @INPROCEEDINGS{10.4108/icst.bodynets.2012.249935,
        author={Mohamed Sabry and Georgios Karakonstantis and David Atienza and Andreas Burg},
        title={Design of Energy Efficient and Dependable Health Monitoring Systems under Unreliable Nanometer Technologies},
        proceedings={7th International Conference on Body Area Networks},
        publisher={ICST},
        proceedings_a={BODYNETS},
        year={2012},
        month={11},
        keywords={ecg monitoring biomedical applications error-resilience memory failures energy-efficiency reliability hardware software co-design},
        doi={10.4108/icst.bodynets.2012.249935}
    }
    
  • Mohamed Sabry
    Georgios Karakonstantis
    David Atienza
    Andreas Burg
    Year: 2012
    Design of Energy Efficient and Dependable Health Monitoring Systems under Unreliable Nanometer Technologies
    BODYNETS
    ICST
    DOI: 10.4108/icst.bodynets.2012.249935
Mohamed Sabry1,*, Georgios Karakonstantis1, David Atienza1, Andreas Burg1
  • 1: EPFL
*Contact email: mohamed.sabry@epfl.ch

Abstract

In this paper we investigate the impact of potential hardware misbehavior induced by reliability issues and scaled voltages in wireless body sensor network (WBSN) nodes. Our study reveals the inherent resilience of popular algorithms in cardiac monitoring applications and argues that by exploiting the unique characteristics of such algorithms the energy efficiency and reliability of such WBSNs can be improved. The main idea of our multi-layer design (HW/SW) approach is the selective application of costly robust techniques only to the most critical tasks identified at the application layer that are detrimental for obtaining sufficient output quality. Our results show that by ensuring the correct operation of only 37% of the total computations in an electrocardiogram (ECG) monitoring WBSN node we can achieve up to 70% power savings with only 9% degradation in ECG output quality.