Journal of rehabilitation welfare engineering & assistive technology (재활복지공학회논문지)

Rehabilitation Engineering And Assistive Technology Society of Korea (한국재활복지공학회)
권호 표지
DOI QR코드

DOI QR Code

Recording and Analysis of Peripheral Nerve Activity Using Multi-Electrode Array

다채널 신경전극 어레이를 이용한 말초 신경신호의 측정 및 분석

  • Received : 2016.08.22
  • Accepted : 2016.09.02
  • Published : 2016.11.30
Download PDF
⟨ Previous Next ⟩

Abstract

Reliable recording and analysis of peripheral nerve activity is important to recognize the user's intention for controlling a neuro-prosthetic hand. In this paper, we present a peripheral nerve recording system that consisted of an intrafascicular multi-electrode array, an electrode insertion device, and a multi-channel neural amplifier. The 16 channel multi-electrode array was stably implanted into the sciatic nerve of the rat under anesthesia using the electrode insertion device. During passive movements and mechanical stimuli, muscle and cutaneous afferent signals were recorded with the multi-channel neural amplifier. Furthermore, we propose a spike sorting method to isolate individual neuronal unit. The muscle proprioceptive units were classified as muscle spindle afferents or Golgi tendon organ afferents, and the skin exteroceptive units were categorized as slow adapting afferents or fast adapting afferents. Experimental results showed that the proposed method could be applicable to record and analyze peripheral nerve activity in neuro-prosthetic systems.

신경보철 의수를 제어하기 위해서는 말초 신경신호를 측정하고 분석함으로써 사용자의 동작의도를 인식해야 한다. 본 논문에서는 다채널 신경전극 어레이, 전극 삽입 장치, 신경신호 증폭기로 구성된 말초 신경신호 측정 시스템을 제안한다. 마취상태에서 전극 삽입 장치를 이용하여 16 채널의 신경전극 어레이를 백서의 좌골신경에 안정적으로 삽입하였다. 수동적 관절 운동을 유도하거나 기계적 피부 자극을 인가하였을 때, 신경신호 증폭기를 통해 근육 또는 피부 감각 신경신호가 측정됨을 확인하였다. 또한, 개별 신경 단위를 분리하기 위해 활동전위 분류방법을 제안한다. 근육의 내부 수용기들은 근방추와 골지건 기관 수용기로 구분되었으며, 피부의 외부 수용기들은 완만적응과 급속적응 수용기로 분리되었다. 이와 같은 실험결과는 제안한 방법이 신경보철 시스템에서 말초 신경신호의 측정과 분석에 적용될 수 있음을 보였다.

Keywords

References

  1. S. Y. Kang, S. H. Eom, M. S. Jang, E. H. Lee, "A Study on Robotic Arm Control Method Based on Upper Extremity Electromyogram", J. of Rehab. Welfare Engineering & Assistive Technology, vol. 9, no. 1, pp.73-80, 2015.
  2. T. S. Davis, H. A. C. Wark, D. T. Hutchinson, D. J. Warren, K. O'Neill, T. Scheinblum, G. A. Clark, R. A. Normann, and B. Greger, "Restoring motor control and sensory feedback in people with upper extremity amputations using arrays of 96 microelectrodes implanted in the median and ulnar nerves," Journal of Neural Engineering, vol. 13, pp. 1-15, 2016.
  3. P. M. Rossini, S. Micera, A. Benvenuto, J. Carpaneto, G. Cavallo, L. Citi, C. Cipriani, L. Denaro, V. Denaro, G. D. Pino, F. Ferreri, E. Guglielmelli, K. Hoffmann, S. Raspopovic, J. Rigosa, L. Rossini, M. Tombini, and P. Dario, "Double nerve intraneural interface implant on a human amputee for robotic hand control," Clinical Neurophysiology, vol. 121, pp. 777-783, 2010. https://doi.org/10.1016/j.clinph.2010.01.001
  4. S. Raspopovic, M. Capogrosso, F. M. Petrini, M. Bonizzato, J. Rigosa, G. D. Pino, J. Carpaneto, M. Controzzi, T. Boretius, E. Fernandez, G. Granata, C. M. Oddo, L. Citi, A. L. Ciancio, C. Cipriani, M. C. Carrozza, W. Jensen, E. Guglielmelli, T. Stieglitz, P. M. Rossini, and S. Micera, "Restoring natural sensory feedback in real-time bidirectional hand prostheses," Science Translational Medicine, vol. 6, pp. 222ra19, 2014. https://doi.org/10.1126/scitranslmed.3006820
  5. D. W. Tan, M. A. Schiefer, M. W. Keith, J. R. Anderson, J. Tyler, and D. J. Tyler, "A neural interface provides long-term stable natural touch perception," Science Translational Medicine, vol. 6, pp. 257ra138, 2014. https://doi.org/10.1126/scitranslmed.3008669
  6. A. Ramachandran, M. Schuettler, N. Lago, T. Doerge, K. P. Koch, X. Navarro, K.-P. Hoffmann, and T. Stieglitz, "Design, in vitro and in vivo assessment of a multi-channel sieve electrode with integrated multiplexer," Journal of Neural Engineering, vol. 3, pp. 114-124, 2006. https://doi.org/10.1088/1741-2560/3/2/005
  7. G. E. Loeb and R. A. Peck, "Cuff electrodes for chronic stimulation and recording of peripheral nerve activity," Journal of Neuroscience Methods, vol. 64, pp. 95-103, 1996. https://doi.org/10.1016/0165-0270(95)00123-9
  8. S. Musallam, M. J. Bak, P. R. Troyk, and R. A. Andersen, "A floating metal microelectrode array for chronic implantation," Journal of Neuroscience Methods, vol. 160, pp. 122-127, 2007. https://doi.org/10.1016/j.jneumeth.2006.09.005
  9. S. Gibson, J. W. Judy, and D. Markovic, "Spike sorting," IEEE Signal processing magazine, vol. 29, pp. 124-143, 2012.
  10. A. Hyvarinen, "Fast and robust fixed-point algorithms for independent component analysis," IEEE Transactions on Neural Networks, vol. 10, pp. 626-634, 1999. https://doi.org/10.1109/72.761722
  11. J.-U. Chu and Y.-J. Lee, "Conjugate-priorpenalized learning of Gaussian mixture models for multifunction myoelectric hand control," IEEE Transactions on Neural System and Rehabilitation Engineering, vol. 17, pp. 287-297, 2009. https://doi.org/10.1109/TNSRE.2009.2015177
  12. H. Schmalbruch, "Fiber composition of the rat sciatic nerve," The Anatomical Record, vol. 215, pp. 71-81, 1986. https://doi.org/10.1002/ar.1092150111