AI-Based Tai Chi and Baduanjin for Improving Balance and Reducing Fall Risk in Adults With Chronic Diseases

June 22, 2026 updated by: Mohamed Fakhry Ahmed Salem, Alexandria University

Comparative Effects of an AI-Based Mobile Application Delivering Tai Chi and Baduanjin on Balance and Fall Risk in Adults With Chronic Diseases: A Randomized Controlled Trial

This study aims to examine the effects of an AI-based mobile application delivering Tai Chi and Baduanjin exercises on balance and fall risk in adults with chronic diseases.

Participants will be randomly assigned to Tai Chi, Baduanjin, or a control group over a 12-week period. The AI application will provide exercise guidance and basic feedback.

Outcomes will focus on balance and, fall risk, along with user interaction with the technology.

The results are expected to support the use of AI-assisted exercise programs in improving balance and reducing fall risk in individuals with chronic conditions.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

120

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • Egypt
      • Alexandria, Egypt, 21511
        • Faculty of Nursing, Alexandria University
        • Principal Investigator:
          • Mohamed Fakhry Ahmed Salem, PhD in Medical-Surgical Nursin
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Adults
  • Individuals with one or more health conditions relevant to the study
  • Able to participate in physical activity
  • Able to understand study instructions
  • Willing to provide informed consent

Exclusion Criteria:

  • - Any condition that may limit safe participation in the study
  • Any medical or other issue that may interfere with study procedures, as determined by the research team

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Tai Chi Group
Participants will perform Tai Chi exercises guided by an AI-based mobile application over a 12-week period.
Behavioral: Tai Chi Exercise Program
Participants will perform Tai Chi exercises guided by an AI-based mobile application. The program includes structured exercise sessions aimed at improving balance and mobility, with basic feedback provided by the application.
Experimental: Baduanjin Group
Participants will perform Baduanjin exercises guided by an AI-based mobile application over a 12-week period.
Behavioral: Baduanjin Exercise Program
Participants will perform Baduanjin exercises guided by an AI-based mobile application. The program consists of structured movements designed to support balance and physical function, with feedback delivered through the application.
No Intervention: Control Group
Participants will receive usual care and general physical activity advice without a structured exercise intervention.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Balance Performance (Mini-BESTest Score)
Time Frame: Baseline and Week 12
Balance will be assessed using the Mini-Balance Evaluation Systems Test (Mini-BESTest), a performance-based clinical scale measuring dynamic balance and postural control. Scores range from 0 to 28, with higher scores indicating better balance.
Baseline and Week 12
Fall Risk (Timed Up and Go Test Time)
Time Frame: Baseline and Week 12
Fall risk will be assessed using the Timed Up and Go (TUG) test, measured in seconds. Lower time indicates better functional mobility and lower risk of falls.
Baseline and Week 12

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Technology Acceptance
Time Frame: Week 12
User acceptance of the AI-based intervention will be evaluated using a structured questionnaire.
Week 12
Participant Experience (Qualitative Feedback)
Time Frame: Post-intervention after 12 weeks
Assessed using open-ended questions to explore participant experiences with the intervention.
Post-intervention after 12 weeks

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Alexandria University

Investigators

  • Principal Investigator: Mohamed Fakhry Ahmed Salem, PhD in Medical-Surgical Nursin, Alexandria University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

June 16, 2026

Primary Completion (Estimated)

July 20, 2026

Study Completion (Estimated)

July 30, 2026

Study Registration Dates

First Submitted

June 13, 2026

First Submitted That Met QC Criteria

June 22, 2026

First Posted (Actual)

June 29, 2026

Study Record Updates

Last Update Posted (Actual)

June 29, 2026

Last Update Submitted That Met QC Criteria

June 22, 2026

Last Verified

June 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • AU-20-10-478

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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