The goal of this observational study is to assess the accuracy of Artificial Intelligence (AI) software to assist ultrasound scanning prior to peripheral nerve blocks. 40 healthy volunteers are going to be accepted to this study in which ultrasound scanning will be performed for four different block types.

The main questions it aims to answer are:

• Can Nerveblox, the artificial intelligence software highlight and find the key anatomical landmarks on the provided nerve or plane block correctly?
• Can the user obtain a correct view of provided nerve or plane block, when the AI software scan success reaches 100%?

Participants will be evaluated under four nerve block regions to identify their key anatomical landmarks using ultrasound-guided artificial intelligence software.

Three residents with different levels of Ultrasound-guided Regional Anesthesia(UGRA) experience but eligible to perform UGRA techniques will collect the ultrasound images when the artificial intelligence software scan success fed by ultrasound reached 100%. After collecting US images, each pair of US images(highlighted and raw ) will be evaluated by 2 experts for the accuracy of AI assistance, independently and blindly.

Ultrasound-guided Regional Anesthesia (UGRA) is currently an effective method for the anesthesiologist. In this single-centered study, we aim to assess the accuracy of artificial intelligence effectiveness. All scans will be performed on an FDA-cleared general-purpose ultrasound device (GE Logiq, Wisconsin, USA) and software setup will be provided by the sponsor also having the software (Nerveblox, Smart Alfa Teknoloji San. Ve Tic. A.S., Ankara, Turkey).

The methodology of the study is that:

• Three independent residents, in the 2nd, 3rd, and 4th years of education in the field of anesthesiology and also eligible to perform UGRA, will be recruited for using the artificial intelligence software (Nerveblox v1.0).

• 40 (20 male and 20 female) volunteers will be recruited for the study and the volunteer's demographic information (body mass index, gender, age) will be considered and recorded.

• The order of volunteers will be randomized between participants.

• Considered peripheral nerve and plane blocks are:

  1. Interscalene brachial plexus
  2. Supraclavicular brachial plexus
  3. Infraclavicular brachial plexus
  4. Transversus abdominis plane

• Each trainee will reach 100% "scan success" on the Nerveblox to record the raw and highlighted images.

• Each trainee will scan only 1 time.

On the data analysis:

• Evaluation of the accuracy of artificial intelligence software will be completed independently by 2 experts in the field of regional anesthesia using the grading scale (0: mislocated, 1: very poor, 2: poor, 3: good, 4: very good, 5: excellent).
• Experts will be asked the evaluate the accuracy of Nerveblox highlighting performance when it reached 100%.
• Demographic data averages will be presented on the result of the study.
• Data will be analyzed by using SPSS 25.0 software at a 95% confidence level. For the measurements, the mean, standard deviation (SD), minimum, maximum, and median statistics will be provided.

Inclusion Criteria:

• Volunteers over the age of 18
• Able to accept and sign the Informed Consent Form before participating in the study

Exclusion Criteria:

• Volunteers below the age of 18
• Unwilling to accept or having psychiatric/neurological diseases to sign an Informed Consent Form before participating in the study
• Inability to lie flat
• Anatomical deformity in the selected regions

In total, 20 female and 20 male healthy volunteers participated to study by accepting an informed consent form. Volunteers' body mass index, age, and gender information have been recorded. Sponsor, Smart Alfa Teknoloji San. ve Tic. A.S. paid the volunteer's logistic expenses during the study.

Residents who participated in the study must be in the 2nd, 3rd, and 4th years of education scanned ultrasound images, and also have the knowledge to perform UGRA.

2 experts, who have strong knowledge and 15 years of experience least in regional anesthesia, will participate for rating the collected scans.