Electric Impedance, Human, Hypodermic Needles, Nerve, Tissues
Conditions
Brief summary
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).
Interventions
OTHERNeedle placement in different tissue types
Bioimpedance will be measured for needle positions in different tissue types
Sponsors
Oslo University Hospital
Study design
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
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
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| 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). | From day 1 up to 12 months |
Countries
Norway
Contacts
Primary ContactAxel R Sauter, PhD
Outcome results
None listed