Irish Journal of Medical Science

, Volume 183, Issue 2, pp 187–197 | Cite as

Acquisition technology research of EEG and related physiological signals under +Gz acceleration

  • Y. Li
  • T. ZhangEmail author
  • L. Deng
  • B. Wang
Original Article



With the continuous improvement of maneuvering performance of modern high-performance aircraft, the protection problem of flight personnel under high G acceleration, the development as well as research on monitoring system and the equipment for human physiological signals processing which include electroencephalogram (EEG) have become more and more important. Due to the particularity of +Gz experimental conditions, the high-risk of human experiments and the great difficulty of dynamic measurement, there is little research on the synchronous acquisition technology of EEG and related physiological signals under +Gz acceleration environment.


We propose a framework to execute human experiments using the three-axial high-performance human centrifuge, develop reasonable operation mode and design a new experimental research method for EEG signal acquisition and variation characteristics on three-axial high-performance human centrifuge under the environment of +Gz acceleration. We also propose to build the synchronous real-time acquisition plan of EEG, electrocardiogram, brain blood pressure, ear pulse and related physiological signals under centrifuge +Gz acceleration with different equipments and methods.


The good profiles of EEG, heart rate, brain blood pressure and ear pulse are obtained and analyzed comparatively. In addition, the FMS hop-by-hop continuous blood pressure and hemodynamic measurement system Portapres are successfully applied to the ambulatory blood pressure measure under centrifuge +Gz acceleration environment.


The proposed methods establish the basis and have an important guiding significance for follow-up experiment development, EEG features spectral analysis and correlation research of all signals.


+Gz EEG, ECG Ambulatory blood pressure Ear pulse Acquisition technology 



The research is supported by the fund of State Key Laboratory of Digital Manufacturing Equipment and Technology of China. Number: DMETKF2012008.


  1. 1.
    Xie BS, Xue YY (1992) Detecting systems of physiological information for G-LOC. Int Aviat 10:59–60Google Scholar
  2. 2.
    Dias NS, Carmo JP, Mendes PM, Correia JH (2012) Wireless instrumentation system based on dry electrodes for acquiring EEG Signals. Med Eng Phys 34:972–981PubMedCrossRefGoogle Scholar
  3. 3.
    Fonseca C, Silva Cunha JP, Martins RE et al (2007) A Novel Dry Active Electrode for EEG Recording. IEEE Trans Biomed Eng (TBME) 54(1):162–165CrossRefGoogle Scholar
  4. 4.
    Vangu Kitoko, Tuan NN, Jordan SN, Yvonne T,Hung T. Nguyen (2011) Performance of dry electrode with bristle in recording EEG rhythms across brain state changes. 33rd Annual International Conference of the IEEE EMBS 2011, 59–62Google Scholar
  5. 5.
    Filipe S, Charvet G, Foerster M.A (2011) wireless multichannel EEG recording platform. 33rd Annual International Conference of the IEEE EMBS 2011, 6319–6322Google Scholar
  6. 6.
    Saadi H, Ferroukhi M, Attari M (2011) Development of wireless high immunity EEG recording system. IEEE International Conference on Electronic Devices,Systems and Applications(ICEDSA) 2011, 120–124Google Scholar
  7. 7.
    Engine M, Dalbasti T, Gulduren M, Davash E (2007) Engin EZ.A prototype portable system for EEG measurements. Measurement 40:936–942CrossRefGoogle Scholar
  8. 8.
    Sun XQ, Li YH (2009) Gravity physiology theory and practice. Xi An :Fourth Military Medical University Press, 1(1):44Google Scholar
  9. 9.
    Wu B, Xue YY, You GX et al (2011) Study on prodromic responses and method for warning acceleration induced loss of consciousness. Med J Airf 27(1):28–32Google Scholar
  10. 10.
    Buick F, Maloan J (1992) Ear opacity shows head- level blood flow cycling during steady- state exposure to +Gz. Aviat Space Environ Med 63(5):419Google Scholar
  11. 11.
    Wood EH, Lambert EH (1989) Objective documentation and monitoring of human Gz tolerance when unprotected and when protected by anti G suits or M1 type straining maneuvers alone or in combination. SAFE 19(1):39–48Google Scholar
  12. 12.
    Holewijn M (1997) The relationship between ear pulse and the loss of peripheral vision. Flight Surg 25(1):20–21Google Scholar
  13. 13.
    Nakamura M, Chen Q, Sugi T, Ikeda A, Shibasaki H (2005) Technical quality evaluation of EEG recording based on electroencephalographers’ knowledge. Med Eng Phys 27:93–100PubMedCrossRefGoogle Scholar
  14. 14.
    Sugi T, Kawana F, Nakamura M (2009) Automatic EEG arousal detection for sleep apnea syndrome. Biomed Signal Process Control 4:329–337CrossRefGoogle Scholar
  15. 15.
    Li J, Wu XY, Sun XQ (1997) Experimental study on monitoring of loss of consciousness during lower body negative pressure in rabbits. Chin J Aerosp Med 8(3):167–171Google Scholar
  16. 16.
    Xie BS, Qi ZN, Xue YY et al (1992) Effects of +Gy Stress on Human Body. Space Med Med Eng 5(3):206–211Google Scholar
  17. 17.
    Interactive Encyclopedia. Overweight. EB/OL.,(2010-02-16 11:09:16)
  18. 18.
    Li BN, Dong MC, Vai MI (2010) On an automatic delineator for arterial blood pressure waveforms. Biomed Signal Process Control 5:76–81CrossRefGoogle Scholar
  19. 19.
    Tang C, Yang GS, Xi T (2004) Research progress of noninvasive continuous blood pressure measurement methods. Chin Med Equip J 10(26–27):34Google Scholar
  20. 20.
    Tanaka S, Gao S, Nogawa M et al (2005) Non-invasive Measurement of Instantaneous Blood pressure in the Radial Artery. IEEE Eng Med Biol Mag 24(4):32–37PubMedCrossRefGoogle Scholar
  21. 21.
    Tanaka S, Nogawa M, Yamakoshi T et al (2007) Accuracy assessment of a noninvasive device for monitoring beat-by-beat blood pressure in the radial artery using the volume-compensation method. IEEE Trans Biomed Eng (TBME) 54(10):1892–1895CrossRefGoogle Scholar
  22. 22.
    Fortino G,Giampà V (2010) PPG-based methods for non invasive and continuous blood pressure measurement: overview and development issues in body sensor networks. 2010 IEEE International Workshop on Medical measurements and applications proceedings, Ottawa: IEEE Press, 2010, 10–13Google Scholar
  23. 23.
    McCombie DB, Shaltis PA, Reisner AT, Asada HH (2007) Adaptive hydrostatic blood pressure calibration: Development of a wearable, autonomous pulse wave velocity blood pressure monitor. Proceedings of the 29th Annual International Conference of the IEEE EMBS 2007, 371–373Google Scholar
  24. 24.
    Chen Y, Wen CY, Tao GC, Bi M (2010) A new methodology of continuous and noninvasive blood pressure measurement by pulse wave velocity. IEEE 11th Int. Conf. Control, Automation, Robotics and Vision 2010, 1018–1023Google Scholar
  25. 25.
    Lopez G, Ushida H, Hidaka K, et al. (2009) Continuous blood pressure measurement in daily activities. IEEE SENSORS 2009 Conference 2009; 827–831Google Scholar
  26. 26.
    Fung P, Dumont G, Ries C, Mott C, Ansermino M (2004) Continuous noninvasive blood pressure measurement by pulse transit time. Proceedings of the 26th Annual International Conference of the IEEE EMBS 2004, 738–741Google Scholar
  27. 27.
    Lass J, Meigas K, Karai D, et al. (2004) Continuous blood pressure monitoring during exercise using pulse wave transit time measurement. Proceedings of the 26th Annual International Conference of the IEEE EMBS 2004, 2239–2242Google Scholar
  28. 28.
    Deb S, Nanda C, Goswami D, Mukhopadhyay J, Chakrabarti S (2007) Cuff-less estimation of blood pressure using pulse transit time and pre-ejection period. IEEE 2007 International Conference on Convergence Information Technology 2007, 941–944Google Scholar
  29. 29.
    Wang L, Lo BPL, Yang GZ (2007) Multichannel reflective ppg earpiece sensor with passive motion cancellation. IEEE Trans Biomed Circuits Syst(TBioCAS) 1(4):235–241CrossRefGoogle Scholar
  30. 30.
    Asada HH, Shaltis P, Reisner A et al (2003) Mobile monitoring with wearable photoplethysmographic biosensors. IEEE Eng Med Biol Mag 22(3):28–40PubMedCrossRefGoogle Scholar

Copyright information

© Royal Academy of Medicine in Ireland 2013

Authors and Affiliations

  1. 1.Department of Automation, School of Information Science and TechnologyTsinghua UniversityBeijingChina
  2. 2.State Key Laboratory of Digital Manufacturing Equipment and Technology of ChinaBeijingChina
  3. 3.Air Force Institute of AeromedicineBeijingChina
  4. 4.Department of AutomationEast China University of Science and TechnologyShanghaiChina

Personalised recommendations