J. Semicond. > Volume 37 > Issue 5 > Article Number: 055006

An 8.12 μ W wavelet denoising chip for PPG detection and portable heart ratemonitoring in 0.18 μm CMOS

Xiang Li 1, 2, , Xu Zhang 1, , Peng Li 1, , , Xiaohui Hu 1, and Hongda Chen 1,

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Abstract: A low power wavelet denoising chip for photoplethysmography (PPG) detection and portable heart rate monitoring is presented. To eliminate noise and improve detection accuracy, Harr wavelet (HWT) is chosen as the processing tool. An optimized finite impulse response structure is proposed to lower the computational complexity of proposed algorithm, which is benefit for reducing the power consumption of proposed chip. The modulus maxima pair location module is design to accurately locate the PPG peaks. A clock control unit is designed to further reduce the power consumption of the proposed chip. Fabricated with the 0.18 μm N-well CMOS 1P6M technology, the power consumption of proposed chip is only 8.12 μ W in 1 V voltage supply. Validated with PPG signals in multiparameter intelligent monitoring in intensive care databases and signals acquired by the wrist photoelectric volume detection front end, the proposed chip can accurately detect PPG signals. The average sensitivity and positive prediction are 99.91% and 100%, respectively.

Key words: low powerwavelet denosingPPG detectionportable heart rate monitoring

Abstract: A low power wavelet denoising chip for photoplethysmography (PPG) detection and portable heart rate monitoring is presented. To eliminate noise and improve detection accuracy, Harr wavelet (HWT) is chosen as the processing tool. An optimized finite impulse response structure is proposed to lower the computational complexity of proposed algorithm, which is benefit for reducing the power consumption of proposed chip. The modulus maxima pair location module is design to accurately locate the PPG peaks. A clock control unit is designed to further reduce the power consumption of the proposed chip. Fabricated with the 0.18 μm N-well CMOS 1P6M technology, the power consumption of proposed chip is only 8.12 μ W in 1 V voltage supply. Validated with PPG signals in multiparameter intelligent monitoring in intensive care databases and signals acquired by the wrist photoelectric volume detection front end, the proposed chip can accurately detect PPG signals. The average sensitivity and positive prediction are 99.91% and 100%, respectively.

Key words: low powerwavelet denosingPPG detectionportable heart rate monitoring



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Zhang Xu, Liu Ming, Wang Bo. A wide measurement range and fast update rate integrated interface for capacitive sensors array[J]. IEEE Trans Circuits Syst I, 2014, 61: 2.

[2]

Hu X H, Zhang X, Liu M. A flexible capacitive tactile sensor array with micro structure for robotic application[J]. Sci China Inf Sci, 2014, 57(6): 120204.

[3]

Liu Jialin, Zhang Xu, Hu Xiaohui. A CMOS frontend chip for implantable neural recording with wide voltage supply range[J]. Journal of Semiconductors, 2015, 36(10): 105003.

[4]

Wang Yuan, Zhang Xu, Liu Ming. An implantable neurostimulator with an integrated high-voltage inductive power-recovery frontend[J]. Journal of Semiconductors, 2014, 35(10): 105012.

[5]

An J, Lee J H, Ahn C W. An efficient GP approach to recognizing cognitive tasks from fNIRS neural signals[J]. Sci China Inf Sci, 2013, 56(7): 109201.

[6]

Li P, Liu M, Zhang X. A low-complexity ECG processing algorithm based on the Haar wavelet transform for portable health-care devices[J]. Sci China Inf Sci, 2014, 57(14): 122303.

[7]

Mazomenos E B, Biswas D, Acharyya A. A low-complexity ECG feature extraction algorithm for mobile healthcare applications[J]. IEEE J Biomed Health Inf, 2013, 17: 459.

[8]

Mallat S. A wavelet tour of signal processing[J]. New York: Academic, 2009: 102.

[9]

Cohen A, Kovacevic J. Wavelets: the mathematical background[J]. Proc IEEE, 1996, 84: 514.

[10]

G B Moody, R G Mark. A database to support development and evaluation of intelligent intensive care monitoring[J]. Proceedings of the IEEE International Conference on Computers in Cardiology Indianapolis, 1996: 657.

[11]

Ieong C I, Mak P I, Lam C P. A 0.83-μ W QRS detection processor using quadratic spline wavelet transform for wireless ecg acquisition in 0.35-μm CMOS[J]. IEEE Trans Biomedical Circuits and Systems, 2012, 6(6): 586.

[12]

Wai P M, Zhao Y J, Zhao B. A real-time ECG QRS detection ASIC based on wavelet multiscale analysis[J]. Proc IEEE Asian Solid-State Circuits Conf, 2009: 293.

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X Li, X Zhang, P Li, X H Hu, H D Chen. An 8.12 μ W wavelet denoising chip for PPG detection and portable heart ratemonitoring in 0.18 μm CMOS[J]. J. Semicond., 2016, 37(5): 055006. doi: 10.1088/1674-4926/37/5/055006.

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Manuscript received: 29 December 2015 Manuscript revised: Online: Published: 01 May 2016

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