Kinematic Training in Patients With Neck Pain Based on Machine Learning Classification Approach

Brief summary (from the registry)

The goal of this clinical trial is to study if kinematic training based on novel kinematic assessment clasification approach can decrease chronic neck pain and prevent its reoccurance better than conventional kinematic training in adults. The main question\[s\] it aims to answer \[is/are\]: Does clustering patients with neck pain based on head and neck movement characteristics lead to more efficient kinematic rehabilitation training and improved clinical outcomes Researchers will compare effects of cluster specific kinematic training to see if it effects pain levels and its reoccurance. Participants will \[describe the main tasks participants will be asked to do, interventions they'll be given and use bullets if it is more than 2 items\].

Study details

Official title

What is the Ability of Datamining Approaches to Cluster Patients With Idiopathic Neck Pain and Can Machine Learning Algorithms Provide More Efficient Rehabilitation and Less Recurrence Based on Kinaesthetic Training Protocols

Conditions

• Chronic Neck Pain

Interventions

• Other: Smallest movement deficit training protocol
• Other: Smaller movement deficit training protocol
• Other: Larger movement deficit training group
• Other: Largest movement deficit training protocol
• Other: Control group intervention protocol

Sponsor

University of Ljubljana

Start date

2026-03-18

Primary completion

2026-06-20

Sex

All

Age range

from 18 Years to 65 Years

Results posted

No results posted in this snapshot

Countries

Slovenia

Total sites listed

1

Eligibility criteria