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Combining EEG and EMG Signals in a Wireless System for Preventing Fall in Neurodegenerative Diseases

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Ambient Assisted Living

Part of the book series: Biosystems & Biorobotics ((BIOSYSROB,volume 11))

Abstract

We present an innovative wireless wearable, low power, noninvasive neuroprosthetic system that is geared towards detecting and preventing falls. The system allows continuous monitoring of EEG/EMG, detecting in particular pre-motor potentials to prevent falls of elder and motor-impaired patients by introducing a feedback action to stabilize gait.

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References

  1. Do, A.H., et al.: Brain-computer interface controlled robotic gait orthosis. J. Neuro Eng. Rehabil. 10, 111 (2013)

    Google Scholar 

  2. http://ec.europa.eu/health/mental_health/docs/services_older.pdf

  3. http://www.cdc.gov/homeandrecreationalsafety/falls/adultfalls.html

  4. http://www.ncoa.org/press-room/fact-sheets/falls-prevention-fact-sheet.html

  5. Zijlstra, W., et al.: A body-fixed -sensor-based analysis of power during sit-to-stand movements, vol. 31, pp. 272–278. Gait & Posture, Elsevier (2010)

    Google Scholar 

  6. Tamura, T., et al.: A wearable airbag to prevent fall injuries. IEEE Trans. Inf. Technol. Biomed. 13(6), 910–4, (2009). doi:10.1109/TITB.2009.2033673.Epub

  7. Nyan, M.N., Tay, F.E.H., Murugasu, E.: A wearable system for pre-impact fall detection. J. Biomech. 41(16), 3475–3481 (2008) doi:10.1016/j.jbiomech.2008.08.009

  8. Pfurtscheller, G., Guger, C.: Brain-Computer Communication System: EEG-based control of hand orthesis in a tetraplegic patient. In: Acta Chirurgica Austriaca., S. 23–25 (1999)

    Google Scholar 

  9. Shibasaki, H., Hallett, M.: What is the Bereitschaftspotential? Clin. Neurophysiol. 117, 2341–2356 (2006)

    Article  Google Scholar 

  10. Millán, et al.: Combining brain–computer interfaces and assistive technologies: state-of-the-art and challenges. Front. Neurosci. 4, article 161 (2010)

    Google Scholar 

  11. Nielsen, K.D., et al.: EEG based BCI—towards a better control. Brain-Computer Interface Research at Aalborg University. IEEE Trans. Neural Syst. Rehabil. Eng. 14(2) (2006)

    Google Scholar 

  12. Green, J.B., St. Arnold, P.A., Rozhkov, L., Strother, D.M., Garrott, N.: EEG/EPT Bereitschaft (readiness potential) and supplemental motor area interaction in movement generation: spinal cord injury and normal subjects. J. Rehabil. Res. Dev. 40(3), 225–234 (2003)

    Google Scholar 

  13. Wagner, J., et al.: Level of participation in robotic-assisted treadmill walking modulates midline sensorimotor EEG rhythms in able-bodied subjects. Neuroimage 15, 63(3), 1203–1211 (2012)

    Google Scholar 

  14. Raethjen, J., Muthuraman, M.: Corticomuscular coupling in human locomotion: muscle drive or gait control? J. Physiol. 15, 590(Pt 16). 3631–3632 (2012). doi:10.1113/jphysiol.2012.232645

  15. De Venuto, D., Sangiovanni Vincentelli, A.: Dr. Frankenstein’s dream made possible: implanted electronic devices. In: Design, Automation & Test in Europe Conference & Exhibition (DATE) Grenoble (France), pp. 18–22, March 2013

    Google Scholar 

  16. Kornhuber, H.H.; Deecke, L. Readiness for movement – The Bereitschaftspotential-Story,Current Contents Life Sciences 33: 14.1990

    Google Scholar 

  17. Dai, J., Bai, X., Yang, Z., Shen, Z., Xuan, D.: A pervasive fall detection system using mobile phones. In: IEEE International Conference on Pervasive Computing and Communications Workshops, pp. 292–297. Mannheim (2010)

    Google Scholar 

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Correspondence to D. De Venuto .

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De Venuto, D., Annese, V.F., de Tommaso, M., Vecchio, E., Sangiovanni Vincentelli, A.L. (2015). Combining EEG and EMG Signals in a Wireless System for Preventing Fall in Neurodegenerative Diseases. In: Andò, B., Siciliano, P., Marletta, V., Monteriù, A. (eds) Ambient Assisted Living. Biosystems & Biorobotics, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-319-18374-9_30

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  • DOI: https://doi.org/10.1007/978-3-319-18374-9_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18373-2

  • Online ISBN: 978-3-319-18374-9

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