4th International ICST Conference on Body Area Networks

Research Article

Heart Rate and Blood Pressure Estimation from Compressively Sensed Photoplethysmograph

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  • @INPROCEEDINGS{10.4108/ICST.BODYNETS2009.6023,
        author={Pawan K. Baheti and Harinath Garudadri},
        title={Heart Rate and Blood Pressure Estimation from Compressively Sensed Photoplethysmograph},
        proceedings={4th International ICST Conference on Body Area Networks},
        publisher={ICST},
        proceedings_a={BODYNETS},
        year={2010},
        month={5},
        keywords={BAN Pulse oximeter Low power sensors Compressed sens- ing Matching pursuit Blood pressure},
        doi={10.4108/ICST.BODYNETS2009.6023}
    }
    
  • Pawan K. Baheti
    Harinath Garudadri
    Year: 2010
    Heart Rate and Blood Pressure Estimation from Compressively Sensed Photoplethysmograph
    BODYNETS
    ICST
    DOI: 10.4108/ICST.BODYNETS2009.6023
Pawan K. Baheti1,*, Harinath Garudadri1,*
  • 1: Qualcomm Inc. 5775 Morehouse Drive San Diego, CA 92121
*Contact email: pbaheti@qualcomm.com, hgarudad@qualcomm.com

Abstract

In this paper we consider the problem of low power SpO2 sensors for acquiring Photoplethysmograph (PPG) signals. Most of the power in SpO2 sensors goes to lighting red and infra-red LEDs. We use compressive sensing to lower the amount of time LEDs are lit, thereby reducing the signal acquisition power. We observe power savings by a factor that is comparable to the sampling rate. At the receiver, we reconstruct the signal with suffcient integrity for a given task. Here we consider the tasks of heart rate (HR) and blood pressure (BP) estimation. For BP estimation we use ECG signals along with the reconstructed PPG waveform. We show that the reconstruction quality can be improved at the cost of increasing compressed sensing bandwidth and receiver complexity for a given task. We present HR and BP estimation results using the MIMIC databas