Detection of Needle to Nerve Contact based on Electric Bioimpedance and Machine Learning Methods

Håvard Kalvøy, Christian Tronstad, Kyrre Ullensvang1, Torsten Steinfeldt2, Axel R. Sauter3

  • 1Division of Emergencies and Critical Care, Dept. of Anaesth
  • 2Philipps University of Marburg, Marburg an der Lahn, Hesse, Germ
  • 3Dept. of Research and Development, Division of Emergencies

Details

08:30 - 08:45 | Wed 12 Jul | Min Room | WeAT4.3

Session: Novel Sensing Methods I

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Abstract

In an ongoing project for electrical impedance-based needle guidance we have previously showed in an animal model that intraneural needle positions can be detected with bioimpedance measurement. To enhance the power of this method we in this study have investigated whether an early detection of the needle only touching the nerve also is feasible. Measurement of complex impedance during needle to nerve contact was compared with needle positions in surrounding tissues in a volunteer study on 32 subjects. Classification analysis using Support-Vector Machines demonstrated that discrimination is possible, but that the sensitivity and specificity for the nerve touch algorithm not is at the same level of performance as for intra-neuralintraneural detection.