About this trial
The goal of this study is to investigate the effect of AI integration into clinical physical therapy clinical decision in improving cost effectiveness and clinical outcomes purposes of the study are:
1. Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on management of pain in myofascial pain syndrome. 2. Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on improving joint range of motion limitations in myofascial pain syndrome. 3. Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on improving muscle strength in myofascial pain syndrome. 4. Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on management of functional limitation in myofascial pain syndrome. 5. Compare the effectiveness of AI driven and human driven clinical decision in physical therapy clinical practice on cost-effectiveness in physical therapy management of myofascial pain syndrome.
Eligibility criteria
Qualifiers
A- Demographic: Adult individuals 18-65 both sex
Localized pain.
Intensity: baseline pain score of 4 or higher on the VAS . C- Duration: chronic pain 3-6 months
Disqualifiers
• Severe cognitive impairment or illness.
Recent history of major surgery or trauma (within 3 months).
Other chronic conditions that could significantly interfere with the study.
Widespread Pain Index (WPI) (appendix (2): Measures the number of painful areas across the body. A score of 7 or more indicates a higher likelihood of FMS (Wang et al. ,2025).
Trial design
Treatments tested in this trial
- dry needling
- neuromuscular facilitation (PNF) stretching
- strengthening exercises (isometric & dynamic)
- Transcutaneous electrical nerve stimulation
- Ultrasound
- Hot pack
- Stretching exercises