Skip to main content

2018 | OriginalPaper | Buchkapitel

8. An Ultra-low Power, Robust Photoplethysmographic Readout Exploiting Compressive Sampling, Artifact Reduction, and Sensor Fusion

verfasst von : Venkata Rajesh Pamula, Chris Van Hoof, Marian Verhelst

Erschienen in: Hybrid ADCs, Smart Sensors for the IoT, and Sub-1V & Advanced Node Analog Circuit Design

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This paper describes an ultra-low power yet robust photoplethysmographic (PPG) readout exploiting various mixed-signal processing techniques. Firstly, compressive sampling (CS) enables to reduce the LED driver power consumption by up to 30x. Feature extraction is performed in the compressed domain, using a Lomb-Scargle periodogram (LSP) to extract the average heart rate and variability, without requiring complex signal reconstruction techniques. Secondly, we demonstrate, in simulations, increased robustness through digital motion artifact reduction for PPG signals, using a spectral subtraction technique. Finally, simulations show further signal enhancement through sensor fusion, enabling electrocardiogram (ECG)-assisted PPG acquisition for cuffless blood pressure (BP) monitoring. The power consumption gains of compressive sampling and feature extraction directly from the compressed domain are demonstrated through a 172 μW compressive sampling PPG acquisition ASIC fabricated in a 0.18 μm CMOS process. The ASIC achieves up to 30x reduction in LED driver power consumption while extracting heart rate with an accuracy conforming to ANSI-AAMI standards.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Fußnoten
1
The benefits of CS encoding and decoding, followed by feature extraction, all on the sensor node, over the conventional approach of performing feature extraction on the Nyquist rate sampled signal might not be obvious. CS-based approach can be useful in cases where high-power stimulation is involved, as in the case with PPG acquisition as well as in the cases where the maximum achievable sampling frequency of the ADC is limited [15].
 
2
Standard database [19] PPG signals lack annotations and hence sinusoidal modulation is chosen.
 
3
The LED driver power consumption is measured while acquiring the PPG signal of a healthy individual. At the reported power levels, the resulting photocurrent is measured to have an AC component of 45 nApp, while the DC component is measured to be 1.6 μA.
 
Literatur
1.
Zurück zum Zitat Wijsman, J., Grundlehner, B., Liu, H., Hermens, H., Penders, J.: Towards mental stress detection using wearable physiological sensors. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1798–1801, Aug 2011 Wijsman, J., Grundlehner, B., Liu, H., Hermens, H., Penders, J.: Towards mental stress detection using wearable physiological sensors. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1798–1801, Aug 2011
2.
Zurück zum Zitat Allen, J.: Photoplethysmography and its application in clinical physiological measurement. Physiol. Meas. 28(3), R1 (2007)CrossRef Allen, J.: Photoplethysmography and its application in clinical physiological measurement. Physiol. Meas. 28(3), R1 (2007)CrossRef
3.
Zurück zum Zitat Webster, J.G.: Design of Pulse Oximeters. Taylor & Francis Group, New York (1997)CrossRef Webster, J.G.: Design of Pulse Oximeters. Taylor & Francis Group, New York (1997)CrossRef
4.
Zurück zum Zitat Rhee, S., Yang, B.-H., Asada, H.: Artifact-resistant power-efficient design of finger-ring plethysmographic sensors. IEEE Trans Biomed. Eng. 48(7), 795–805 (2001)CrossRef Rhee, S., Yang, B.-H., Asada, H.: Artifact-resistant power-efficient design of finger-ring plethysmographic sensors. IEEE Trans Biomed. Eng. 48(7), 795–805 (2001)CrossRef
5.
Zurück zum Zitat Alhawari, M., Albelooshi, N., Perrott, M.H.: A 0.5 V < 4 μW CMOS photoplethysmographic heart-rate sensor IC based on a non-uniform quantizer. In: 2013 IEEE International Solid-State Circuits Conference Digest of Technical Papers, pp. 384–385 (2013) Alhawari, M., Albelooshi, N., Perrott, M.H.: A 0.5 V < 4 μW CMOS photoplethysmographic heart-rate sensor IC based on a non-uniform quantizer. In: 2013 IEEE International Solid-State Circuits Conference Digest of Technical Papers, pp. 384–385 (2013)
6.
Zurück zum Zitat Candès, E.J., Wakin, M.B.: An introduction to compressive sampling. IEEE Signal Process. Mag. 25(2), 21–30 (2008)CrossRef Candès, E.J., Wakin, M.B.: An introduction to compressive sampling. IEEE Signal Process. Mag. 25(2), 21–30 (2008)CrossRef
7.
Zurück zum Zitat Pamula, V.R., Verhelst, M., Van Hoof, C., Yazicioglu, R.F.: Computationally-efficient compressive sampling for low-power pulse oximeter system. In: 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings, pp. 69–72 (2014) Pamula, V.R., Verhelst, M., Van Hoof, C., Yazicioglu, R.F.: Computationally-efficient compressive sampling for low-power pulse oximeter system. In: 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings, pp. 69–72 (2014)
8.
Zurück zum Zitat Dixon, A.M., Allstot, E.G., Gangopadhyay, D., Allstot, D.J.: Compressed sensing system considerations for ECG and EMG wireless biosensors. IEEE Trans. Biomed. Circuits Syst. 6(2), 156–166 (2012)CrossRef Dixon, A.M., Allstot, E.G., Gangopadhyay, D., Allstot, D.J.: Compressed sensing system considerations for ECG and EMG wireless biosensors. IEEE Trans. Biomed. Circuits Syst. 6(2), 156–166 (2012)CrossRef
9.
Zurück zum Zitat Ren, F., Marković, D.: A configurable 12–237 kS/s 12.8 mW sparse-approximation engine for mobile data aggregation of compressively sampled physiological signals. IEEE J. Solid-State Circuits 51(1) 68–78 (2016) Ren, F., Marković, D.: A configurable 12–237 kS/s 12.8 mW sparse-approximation engine for mobile data aggregation of compressively sampled physiological signals. IEEE J. Solid-State Circuits 51(1) 68–78 (2016)
10.
Zurück zum Zitat Maechler, P., Studer, C., Bellasi, D.E., Maleki, A., Burg, A., Felber, N., Kaeslin, H., Baraniuk, R.G.: VLSI design of approximate message passing for signal restoration and compressive sensing. IEEE J. Emerging Sel. Top. Circuits Syst. 2(3), 579–590 (2012)CrossRef Maechler, P., Studer, C., Bellasi, D.E., Maleki, A., Burg, A., Felber, N., Kaeslin, H., Baraniuk, R.G.: VLSI design of approximate message passing for signal restoration and compressive sensing. IEEE J. Emerging Sel. Top. Circuits Syst. 2(3), 579–590 (2012)CrossRef
11.
Zurück zum Zitat Maechler, P., Greisen, P., Sporrer, B., Steiner, S., Felber, N., Burg, A.: Implementation of greedy algorithms for LTE sparse channel estimation. In: 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers, Nov 2010 Maechler, P., Greisen, P., Sporrer, B., Steiner, S., Felber, N., Burg, A.: Implementation of greedy algorithms for LTE sparse channel estimation. In: 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers, Nov 2010
12.
Zurück zum Zitat Baheti, P.K., Garudadri, H.: An ultra low power pulse oximeter sensor based on compressed sensing. In: 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks, Jun 2009 Baheti, P.K., Garudadri, H.: An ultra low power pulse oximeter sensor based on compressed sensing. In: 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks, Jun 2009
13.
Zurück zum Zitat Csavoy, A., Molnar, G., Denison, T.: Creating support circuits for the nervous system: Considerations for brain-machine interfacing. In 2009 Symposium on VLSI Circuits, Jun 2009 Csavoy, A., Molnar, G., Denison, T.: Creating support circuits for the nervous system: Considerations for brain-machine interfacing. In 2009 Symposium on VLSI Circuits, Jun 2009
14.
Zurück zum Zitat Pamula, V.R., Verhelst, M., Van Hoof, C., Yazicioglu, R.F.: A novel feature extraction algorithm for on the sensor node processing of compressive sampled photoplethysmography signals. In: 2015 IEEE SENSORS, pp. 1–4. IEEE (2015) Pamula, V.R., Verhelst, M., Van Hoof, C., Yazicioglu, R.F.: A novel feature extraction algorithm for on the sensor node processing of compressive sampled photoplethysmography signals. In: 2015 IEEE SENSORS, pp. 1–4. IEEE (2015)
15.
Zurück zum Zitat Yoo, J., Turnes, C., Nakamura, E.B., Le, C.K., Becker, S., Sovero, E.A., Wakin, M.B., Grant, M.C., Romberg, J., Emami-Neyestanak, A., Candes, E.: A compressed sensing parameter extraction platform for radar pulse signal acquisition. IEEE IEEE J. Emerging Sel. Top. Circuits Syst. 2(3), 626–638 (2012)CrossRef Yoo, J., Turnes, C., Nakamura, E.B., Le, C.K., Becker, S., Sovero, E.A., Wakin, M.B., Grant, M.C., Romberg, J., Emami-Neyestanak, A., Candes, E.: A compressed sensing parameter extraction platform for radar pulse signal acquisition. IEEE IEEE J. Emerging Sel. Top. Circuits Syst. 2(3), 626–638 (2012)CrossRef
16.
Zurück zum Zitat Rajesh, P.V., Valero-Sarmiento, J.M., Yan, L., Bozkurt, A., Van Hoof, C., Van Helleputte, N., Yazicioglu, R.F., Verhelst, M.: A 172 μW compressive sampling photoplethysmographic readout with embedded direct heart-rate and variability extraction from compressively sampled data. In: 2016 IEEE International Solid-State Circuits Conference (ISSCC), pp. 386–387. IEEE, Piscataway (2016) Rajesh, P.V., Valero-Sarmiento, J.M., Yan, L., Bozkurt, A., Van Hoof, C., Van Helleputte, N., Yazicioglu, R.F., Verhelst, M.: A 172 μW compressive sampling photoplethysmographic readout with embedded direct heart-rate and variability extraction from compressively sampled data. In: 2016 IEEE International Solid-State Circuits Conference (ISSCC), pp. 386–387. IEEE, Piscataway (2016)
17.
Zurück zum Zitat Glaros, K.N., Drakakis, E.M.: A sub-mW fully-integrated pulse oximeter front-end. IEEE Trans. Biomed. Circuits Syst. 7(3), 363–375 (2013)CrossRef Glaros, K.N., Drakakis, E.M.: A sub-mW fully-integrated pulse oximeter front-end. IEEE Trans. Biomed. Circuits Syst. 7(3), 363–375 (2013)CrossRef
18.
Zurück zum Zitat Pamula, V.R., Valero-Sarmiento, J.M., Yan, L., Bozkurt, A., Van Hoof, C., Van Helleputte, N., Yazicioglu, R.F., Verhelst, M.: A 172_W compressively sampled photoplethysmographic (PPG) readout ASIC with heart rate estimation directly from compressively sampled data. IEEE Trans. Biomed. Circuits Syst. 11(3), 487–496 (2017). Available online at IEEE Xplore Pamula, V.R., Valero-Sarmiento, J.M., Yan, L., Bozkurt, A., Van Hoof, C., Van Helleputte, N., Yazicioglu, R.F., Verhelst, M.: A 172_W compressively sampled photoplethysmographic (PPG) readout ASIC with heart rate estimation directly from compressively sampled data. IEEE Trans. Biomed. Circuits Syst. 11(3), 487–496 (2017). Available online at IEEE Xplore
19.
Zurück zum Zitat Goldberger, A.L., Amaral, L.A., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C.-K., Stanley, H.E.: Physiobank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals. Circulation 101(23), 215–220 (2000)CrossRef Goldberger, A.L., Amaral, L.A., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C.-K., Stanley, H.E.: Physiobank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals. Circulation 101(23), 215–220 (2000)CrossRef
20.
Zurück zum Zitat ANSI/AAMI-EC13: American National Standards for cardiac monitors, hearth rate meters and alarms (2002) ANSI/AAMI-EC13: American National Standards for cardiac monitors, hearth rate meters and alarms (2002)
21.
Zurück zum Zitat Tavakoli, M., Turicchia, L., Sarpeshkar, R.: An ultra-low-power pulse oximeter implemented with an energy-efficient transimpedance amplifier. IEEE Trans. Biomed. Circuits Syst. 4(1), 27–38 (2010)CrossRef Tavakoli, M., Turicchia, L., Sarpeshkar, R.: An ultra-low-power pulse oximeter implemented with an energy-efficient transimpedance amplifier. IEEE Trans. Biomed. Circuits Syst. 4(1), 27–38 (2010)CrossRef
22.
Zurück zum Zitat Wong, A.K., Pun, K.-P., Zhang, Y.-T., Leung, K.N.: A low-power CMOS front-end for photoplethysmographic signal acquisition with robust DC photocurrent rejection. IEEE Trans. Biomed. Circuits Syst. 2(4), 280–288 (2008)CrossRef Wong, A.K., Pun, K.-P., Zhang, Y.-T., Leung, K.N.: A low-power CMOS front-end for photoplethysmographic signal acquisition with robust DC photocurrent rejection. IEEE Trans. Biomed. Circuits Syst. 2(4), 280–288 (2008)CrossRef
23.
Zurück zum Zitat Winokur, E.S., O’Dwyer, T., Sodini, C.G.: A low-power, dual-wavelength photoplethysmogram (PPG) SoC with static and time-varying interferer removal. IEEE Trans. Biomed. Circuits Syst. 9(4), 581–589 (2015)CrossRef Winokur, E.S., O’Dwyer, T., Sodini, C.G.: A low-power, dual-wavelength photoplethysmogram (PPG) SoC with static and time-varying interferer removal. IEEE Trans. Biomed. Circuits Syst. 9(4), 581–589 (2015)CrossRef
24.
Zurück zum Zitat Boll, S.: Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans. Acoust. Speech Signal Process. 27(2), 113–120 (1979)CrossRef Boll, S.: Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans. Acoust. Speech Signal Process. 27(2), 113–120 (1979)CrossRef
25.
Zurück zum Zitat Helleputte, N.V., Kim, S., Kim, H., Kim, J.P., Hoof, C.V., Yazicioglu, R.F.: A 160 μA biopotential acquisition IC with fully integrated IA and motion artifact suppression. IEEE Trans. Biomed. Circuits Syst. 6(6), 552–561 (2012)CrossRef Helleputte, N.V., Kim, S., Kim, H., Kim, J.P., Hoof, C.V., Yazicioglu, R.F.: A 160 μA biopotential acquisition IC with fully integrated IA and motion artifact suppression. IEEE Trans. Biomed. Circuits Syst. 6(6), 552–561 (2012)CrossRef
26.
Zurück zum Zitat Poon, C., Zhang, Y.: Cuff-less and noninvasive measurements of arterial blood pressure by pulse transit time. In: 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference (2005) Poon, C., Zhang, Y.: Cuff-less and noninvasive measurements of arterial blood pressure by pulse transit time. In: 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference (2005)
27.
Zurück zum Zitat Pamula, V.R., Verhelst, M., Hoof, C.V., Yazicioglu, R.F.: A 17 nA, 47.2 dB dynamic range, adaptive sampling controller for online data rate reduction in low power ECG systems. In: 2016 IEEE Biomedical Circuits and Systems Conference (BioCAS), pp. 272–275, Oct 2016 Pamula, V.R., Verhelst, M., Hoof, C.V., Yazicioglu, R.F.: A 17 nA, 47.2 dB dynamic range, adaptive sampling controller for online data rate reduction in low power ECG systems. In: 2016 IEEE Biomedical Circuits and Systems Conference (BioCAS), pp. 272–275, Oct 2016
Metadaten
Titel
An Ultra-low Power, Robust Photoplethysmographic Readout Exploiting Compressive Sampling, Artifact Reduction, and Sensor Fusion
verfasst von
Venkata Rajesh Pamula
Chris Van Hoof
Marian Verhelst
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-61285-0_8

Neuer Inhalt