Development and Evaluation of a Smart Technology-Assisted System for Shoulder Joint Physical Therapy Assessment

Shoulder pain is one of the most prevalent musculoskeletal conditions. Evidence-based medicine has identified physical therapy as the most effective intervention for managing shoulder disorders. To ensure accurate diagnosis and effective treatment planning, a comprehensive evaluation that integrates various clinical findings is essential. Without timely and accurate diagnosis and intervention, shoulder pain may recur and fail to improve, limiting therapeutic outcomes.

With technological advancements, the application of mobile devices and artificial intelligence (AI) in clinical settings has become increasingly widespread. Motion capture technologies integrated into mobile platforms offer emerging solutions for clinical challenges. If clinicians are equipped with an intelligent system for shoulder assessment and intervention-one that includes image-based quantitative assessment tools, evidence-based clinical guidelines and data repositories, and home-based rehabilitation support-it may enhance diagnostic precision, increase clinical efficiency, and improve patient adherence to home exercise programs.

The aim of this study is to develop a smart technology-assisted assessment system for orthopedic physical therapy of the shoulder joint and to validate its reliability and validity. This system will provide clinicians with objective, data-driven evaluation results. In future development, it will also offer support in treatment goal setting, intervention planning, and home-based exercise guidance. The proposed intelligent system is expected to serve as an evidence-based clinical aid, enhancing both the precision and efficiency of physical therapy interventions.

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

Conditions

Shoulder

Age range

20 year–65 year

Sex eligibility

All sexes

Study type

Observational

Primary location

National Cheng Kung University

Tainan, TNN, 704, Taiwan

Who can participate

Healthy volunteers accepted: Yes

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

Inclusion criteria

for group 1:

BMI (body mass index) between 18.5-24.9
self-perceived good physical condition
no history of shoulder orthopedic disease or nerve damage

Inclusion criteria

for group 2:

Non-acute shoulder orthopedic diseases diagnosed by orthopedic physicians or assessed by physical therapists
may include but are not limited to the following diseases: frozen shoulder, shoulder compression syndrome, shoulder rotator injury, shoulder instability, etc.

Exclusion criteria

Any neurological disease that may cause pain
a history of related surgery in the past six months
acute inflammation of the shoulder joint
open wounds in the shoulder joint area
Principle Investor's teaching students, laboratory assistants

Treatment and study plan

Primary outcomes

Range of Motion

Time frame: Total 3 times. First trail at day1 (after enrollment) Second trail at 1hour after first trial Third trail is at day2

Shoulder Range of Motion

Sponsors and collaborators

Lead sponsor

National Cheng-Kung University Hospital

Other

Registry information

Important dates

Study start: 2025
Primary completion: 2026
Study completion: 2026
First posted: Jul 28, 2025
Registry last updated: Jul 28, 2025

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.

Active, Not Recruiting