Skip to main content
OpenTrials
Completed

NCT Number: NCT05291377

ML for Neck Disability Using Muscle and Joint

conduct machine learning models to identify different aspects that can give us an impression about the disability in patients with neck pain.

By using 17 different classifier and regressor models. to identify disability from emg, pain, ROM and curve measurements

Completed

Looking for future studies?

Notify Me

Key information

Age range

30 year–55 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Faculty of physical therapy, Kafrelsheik university

Cairo, Egypt

About this study

ninety patients from both sexes suffering from mechanical neck dysfunction were participated in this study.

Patients were participated in the study if they fulfilled the following criteria

  • Ninety patients from both sexes with their ages ranged from 20-35 years old.
  • Subjects Referred from orthopedic consultant with chronic mechanical neck pain (<3months duration)
  • The neck disability index is above 15, a minimal score to reflect the presence of at least a mild neck pain disorder
  • cervical lordotic curve less than 34°
  • Subjects whose dull aching pain increased by sustained posture, neck movement, palpation of cervical musculatur
  • Agreements of patients.

Exclusion criteria

  • Cervical disc problems or cervical spondylosis.
  • History of previous neck trauma or head injuries.
  • Ankylosing spondylitis
  • Acute inflammation, contracture or surgery affecting cervical spine.
  • Current participation in supervised physical therapy for neck pain.
  • Any skin disease or injury that may affect technique.
  • Osteoporotic and rheumatic arthritic patients.
  • Positive skin sensitivity test to kinesiotape.
  • Unhealed wounds or scars at the treated area
  • Visual or auditory problems Pain intensity was measured by the VAS. The patients were asked to mark on the line of VAS to the point that they felt the pain. Then the score was determined by measuring from the left end of the line to the point that the patient marked It was measured by The NDI which is a 10-item questionnaire consist of pain intensity, personal care, lifting, reading, headache, concentration, work, driving, sleeping and recreation. The subject was instructed to circle one of the six options which describes the severity of each item (0-5)55.Then the marks were counted and divided by 50 or 45 if one section was missing with total score ranging from 0 (no pain or disability) to 50 (severe pain and disability) 57. Then was multiplied by 100 for the percentage (score/ 50) x 100=---% points88. A score of 10-28% is considered mild disability, 30-48% is moderate, 50-68% is sever and 72% or more is complete

Activation pattern of the examined ms was recorded and analyzed using electromyography as follow:

Skin preparation67 After history taking and physical examination, subjects were allowed to rest for 10 minutes for acclimatization. During this period each subject was prepared for the experimental set as follow;

  • The site of the electrode placement had been shaved when needed
  • The skin was cleaned with alcohol with a piece of cotton to reduce skin impedance at the site of recorded muscle and at the site of the reference electrode

Electrodes positions10:

The electrodes sites were located on each subject's dominant side as follows:

levator scapulae:was centered lateral to the C3-4 spinous process between the posterior margin of the sternocleidomastoid and the anterior margins of the upper trapezius Upper trapezius: 2 cm lateral to the midpoint of a line drawn between C7 spinous process and the posterolateral acromion Reference electrode: was situated over the C7 spinous process. The sites of electrodes placement were determined using a marker and a tape measurement and confirmed through palpation and manual resistance.

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Complaining from pain
  • Able to read and write

Exclusion criteria

  • no anomalies

Treatment and study plan

Primary outcomes

  1. Correlation between neck disability and emg signals

    Time frame: 2 weeks

    using logistic regression, we can get this outcome

  2. Correlation between neck disability and range of motion

    Time frame: 2 weeks

    using logistic regression, we can get this outcome

Sponsors and collaborators

Lead sponsor

Kafrelsheikh University

Other

Registry information

Official study title

Machine Learning Models for Identifying Disability in Neck Pain Patients Using Muscle and Joint Parameters

Important dates

Study start
2022
Primary completion
2023
Study completion
2023
First posted
Mar 22, 2022
Registry last updated
Apr 24, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.