Analog Integrated Circuits and Signal Processing

, Volume 74, Issue 2, pp 317–330 | Cite as

A new non-uniform adaptive-sampling successive approximation ADC for biomedical sparse signals

  • Maryam Zaare
  • Hassan Sepehrian
  • Mohammad Maymandi-Nejad


This paper presents a new sampling technique and a successive approximation analog to digital converter (SA-ADC) which samples sparse signals in a non-uniform adaptive way. The proposed sampling technique has the capability to be incorporated in the structure of the SA-ADC. The proposed SA-ADC changes the rate of sampling in accordance with the rate of changes of the signal. In this way, the data volume is reduced considerably without losing the important information in the signal. Simulation results in the 0.18 um CMOS technology shows a power saving of up to 90.5 % and a compression ratio of 7.5 compared to the conventional sampling technique of ECG signals.


Successive approximation ADC Low power Non-uniform sampling Signal specific sampling Biomedical signal Electrocardiogram 


  1. 1.
    Yazicioglu, R.F., Kim, S., Torfs, T., Kim H., Hoof, C.V., A 30uW analog signal processor ASIC for portable biopotential signal monitoring. IEEE Jornal of Solid-State Circuits, 46(1), Jan. 2011.Google Scholar
  2. 2.
    Jalaleddine, S., Hutchens, C., Strattan, R., & Coberly, W. (1990). ECG data compression techniques—A unified approach. IEEE Transactions on Biomedical Engineering, 37, 329–343.CrossRefGoogle Scholar
  3. 3.
    Chen, J., & Itoh, S. (1998). A wavelet transform-based ECG compression method guaranteeing desired signal quality. IEEE Transactions on Biomedical Engineering, 45(12), 1414–1419.CrossRefGoogle Scholar
  4. 4.
    Rajoub, B. A. (2002). An efficient coding algorithm for the compression of ECG signals using the wavelet transform. IEEE Transactions of Biomedical Engineering, 49(4), 355–362.CrossRefGoogle Scholar
  5. 5.
    Michaeli, T., & Eldar, Y. C. (2012). Xampling at the rate of innovation. Signal Processing, IEEE Transactions on, 60(3), 1121–1133.MathSciNetCrossRefGoogle Scholar
  6. 6.
    Bendifallah, A., Benzid, R., & Boulemden, M. (2011). Improved ECG compression method using discrete cosine transform. Electronics Letters, 47(2), 87–89.CrossRefGoogle Scholar
  7. 7.
    Hong, H., & Lee, G. (2007). A 65fJ/conversion-step 0.9-V 200-kS/s rail-to-rail 8-bit successive approximation ADC. IEEE Journal Solid-State Circuits, 42(10), 2161–2168.CrossRefGoogle Scholar
  8. 8.
    Lotfi, R., Majidi, R., Maymandi-Nejad, M., Serdijn W.A. (2009). An ultra-low-power 10-Bit 100-kS/s successive-approximation analog-to-digital converter. Proceedings IEEE International Symposium on Circuits and Systems (ISCAS), 1117–1120.Google Scholar
  9. 9.
    Elzakker M., et al. (2008) A 1.9 μW 4.4fJ/conversion-step 10b 1MS/s charge-redistribution ADC. IEEE Solid-State Circuits Conference Digest of Technical Papers, 244–246.Google Scholar
  10. 10.
    Sepehrian, H., Saberi, M., Lotfi, R. (2011) A signal-specific successive-approximation analog-to-digital converter. Proceeding IEEE International Symposium on Circuits and Systems, 1624–1627.Google Scholar
  11. 11.
    Liew, W.-S., Yao, L., Lian, Y. (2008). A moving binary search SAR-ADC for low power biomedical data acquisition system. Proceeding IEEE Asia Pacific Conference on Circuits and Systems, 646–649.Google Scholar
  12. 12.
    Zou, X., et al. (2008). A 1-V 1.1-μW sensor interface IC for wearable biomedical devices. Proceeding IEEE International Symposium on Circuits and Systems, 2725–2728.Google Scholar
  13. 13.
    Rieger, R., Chen, S. (2006). A signal based clocking scheme for A/D converters in body sensor networks, TENCON 2006. 2006 IEEE Region 10 Conference, 1–4.Google Scholar
  14. 14.
    Agarwal, R., & Sonkusale, S. R. (2011). Input-feature correlated asynchronous analog to information converter for ECG monitoring. IEEE Transactions on Biomedical Circuits Systems, 5(5), 459–467.CrossRefGoogle Scholar
  15. 15.
    Ellis, P. H. (1959). Extension of phase plane analysis to quantized systems. IRE Transactions on Automatic Control, 4, 43–59.CrossRefGoogle Scholar
  16. 16.
    Mamaghanian, H., Khaled, N., Atienza, D., & Vandergheynst, P. (2011). Compressed sensing for real-time energy-Efficient ECG compression on wireless body sensor nodes. IEEE Transactions Biomedical Engineering, 58(9), 2456–2466.CrossRefGoogle Scholar
  17. 17.
    Allstot, E.G., Chen, A.Y., Dixon, A.M.R., Gangopadhyay, D., Allstot, D.J. (2010) compressive sampling of ecg bio-signals: quantization noise and sparsity considerations. Proceeding IEEE Biomedical Circuits and Systems Conference, 41–44.Google Scholar
  18. 18.
    Aviyente, S. (2007). Compressed sensing framework for EEG compression. Proceedings of the IEEE Workshop on Statistical Signal Proccessing, 181–184.Google Scholar
  19. 19.
    Enay, S.S., Chaparro, L.F. Sun, M., Sclabassi, R.J. (2008). Compressive sensing and random filtering of EEG signals using slepian basis. Proceedings of the EURASIP EUSIPCO’08.Google Scholar
  20. 20.
    Chen, F., Chandrakasan, A. P., & Stojanović, V. M. (2012). Design and analysis of a hardware-Efficient compressed sensing architecture for data compression in wireless sensors. IEEE Journal of Solid-State Circuits, 47(3), 744–756.CrossRefGoogle Scholar
  21. 21.
    Feizi, S., Goyal, V. K., & Médard, M. Time-stampless adaptive nonuniform sampling for stochastic signals. Accessed 17 Oct 2011.
  22. 22.
    Goodwin, M. M. (1997). Adaptive signal models: Theory, algorithms, and audio applications, PhD dissertation, university of California, Berkeley.Google Scholar
  23. 23.
    MIT-BIH arrhythmia database. [Online].
  24. 24.
    Zigel, Y., Cohen, A., & Katz, A. (2000). The weighted diagnostic distortion (WDD) measure for ECG signal compression. IEEE Transactions on Biomedical Enggineering, 47, 1422–1430.CrossRefGoogle Scholar
  25. 25.
    Moradi, F., Wisland, D.T., Mahmoodi, H., Aunet, S., Cao, T.V., Peiravi, A. (2009) Ultra low power full adder topologies. Proceeding IEEE International Symposium Circuits and Systems, 3158–3161.Google Scholar
  26. 26.
    Abo, A. M., & Gray, P. R. (1999). A 1.5-V, 10-bit, 14.3-MS/s CMOS pipeline analog-to-digital converter. IEEE Journal of Solid-State Circuits, 34(5), 599–606.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Maryam Zaare
    • 1
  • Hassan Sepehrian
    • 1
  • Mohammad Maymandi-Nejad
    • 1
  1. 1.Integrated Systems Lab., Department of Electrical EngineeringFerdowsi University of MashhadMashhadIran

Personalised recommendations