一种基于压缩传感的超低功耗脉搏血氧计传感器

P. Baheti, H. Garudadri
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引用次数: 92

摘要

我们描述了一种超低功率脉搏血氧计传感器,用于长期、无创地监测体域网络(BAN)中的SpO2和心率。商用脉搏血氧计传感器在连续运行期间消耗约20-60兆瓦的功率。其他研究人员已经证明,精确且噪声强的无线脉搏血氧计传感器可以设计为低至1.5 mW的工作功率。led消耗了脉搏血氧计传感器的大部分功率预算。在这项工作中,我们描述了一种压缩感知方法来采样光电探测器输出,使led可以关闭更长时间,从而节省传感器功率。我们随机采样光容积脉搏图(PPG)信号,样本数量比均匀采样少10-40倍,并证明使用MIMIC数据库,心率估计和血压估计的准确性不会受到损害。通过减少led需要打开的持续时间,这为脉搏血氧计传感器节省了10-40倍的功率。
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An Ultra Low Power Pulse Oximeter Sensor Based on Compressed Sensing
We describe an ultra low power pulse oximeter sensor for long term, non-invasive monitoring of SpO2 and heart rate in Body Area Networks (BAN). Commercial pulse oximeter sensors consume about 20-60 mW of power during continuous operation. Other researchers have shown that accurate and noise robust wireless pulse oximeter sensors can be designed to operate with as little as 1.5 mW. The LEDs consume bulk of the power budget in pulse oximeter sensors. In this work, we describe a compressed sensing approach to sample the photodetector output, so that the LEDs can be turned off for longer periods and thus save sensor power. We randomly sample Photoplethysmogram (PPG) signals with about 10-40x fewer samples than with uniform sampling and demonstrate that the accuracy of heart rate estimation and blood pressure estimation are not compromised, using MIMIC database. This provides power savings of the order of 10-40x for a pulse oximeter sensor, by reducing the duration LEDs need to be turned on.
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