Human Clinical Trial
Official title:
Monitoring of Needle-placement With Multiple Frequency Bioimpedance Monitoring
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).
Status | Recruiting |
Enrollment | 32 |
Est. completion date | December 2017 |
Est. primary completion date | December 2017 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | Both |
Age group | 18 Years and older |
Eligibility |
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 |
Time Perspective: Prospective
Country | Name | City | State |
---|---|---|---|
Norway | Oslo University Hospital | Oslo |
Lead Sponsor | Collaborator |
---|---|
Oslo University Hospital |
Norway,
Kalvøy H, Sauter AR. Detection of intraneural needle-placement with multiple frequency bioimpedance monitoring: a novel method. J Clin Monit Comput. 2016 Apr;30(2):185-92. doi: 10.1007/s10877-015-9698-3. Epub 2015 Apr 23. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | 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 | No |
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