Monitoring of Needle-placement With Multiple Frequency Bioimpedance Monitoring

Oslo University Hospital32 enrolled

Overview

A novel algorithm for bioimpedance measurements to detect nerve tissue, and discriminate it from other tissue types has been developed in a porcine model, by analysing a complex impedance dataset based on multiple measurement frequencies. It must now be confirm that the previous results are applicable in humans. Measurements from 24 predefined needle positions will be obtained in 16 of the 32 volunteers that are included in the study (part A). A new algorithm to detect nerve tissue will be developed based on these measurement results. Further impedance algorithms will be developed for other tissue type. The efficacy of the algorithms (sensitivity and specificity) will be evaluated in the 16 following volunteers (part B).

Study Type

OBSERVATIONAL

Enrollment

Conditions

Electric Impedance Human Hypodermic Needles Tissues Nerve

Interventions

Eligibility

Sex: ALLMin age: 18 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * Age ≥ 18 years * American society of anaesthesiologists score (ASA) 1 or 2 * Volunteers that have given informed written consent Exclusion Criteria: * Volunteers that cannot cooperate for the examination * Volunteers with neurologic disease, nerve- or vascular impairment * ASA \> 2

Outcomes

Primary Outcomes

Success in the identification of nerve tissue by the use of an algorithm based on a multiple frequency impedance measurement (MFIM) algorithm. The outcome is binary (success vs failure).

Time frame: From day 1 up to 12 months