NCT06596993

Brief Summary

The aging physiological state of the elderly may lead to problems such as unstable gait, balance disorders, and falls. Previous research has confirmed that exercise training can help improve the physical function, quality of life, and reduce the risk of falls in the elderly. In order to achieve effective and continuous intervention training, somatosensory games have become a trend in recent years. Among them, the use of non-immersive virtual reality training methods not only provides training for the elderly, but also reduces the discomfort caused by the virtual environment; however, there are some limitations in clinical rehabilitation training methods, such as the lack of data-based evaluation and personalization. In order to solve the above problems, this research plan will use the inertial measurement unit as a tool for clinical monitoring and human movement assessment, and use artificial intelligence technology to evaluate and adjust the training plan according to its gait characteristics to achieve personalization Training and prevention strategies.

Trial Health

77
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
120

participants targeted

Target at P50-P75 for not_applicable

Timeline
6mo left

Started Nov 2023

Typical duration for not_applicable

Geographic Reach
1 country

1 active site

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Progress82%
Nov 2023Dec 2026

Study Start

First participant enrolled

November 3, 2023

Completed
10 months until next milestone

First Submitted

Initial submission to the registry

September 11, 2024

Completed
8 days until next milestone

First Posted

Study publicly available on registry

September 19, 2024

Completed
2.2 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 1, 2026

Expected
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

December 1, 2026

Last Updated

November 19, 2025

Status Verified

October 1, 2025

Enrollment Period

3.1 years

First QC Date

September 11, 2024

Last Update Submit

November 16, 2025

Conditions

Community-dwelling Older Adults

Keywords

Inertial Measurement Unit SensingArtificial IntelligenceBalance RehabilitationOlder Adults

Outcome Measures

Primary Outcomes (10)

  • Static Standing Balance Test

    Balance Assessments

    pre-training, post-training(after 6 weeks), follow-up(after 2 weeks)

  • Single Leg Standing Test

    Balance Assessments

    pre-training, post-training(after 6 weeks), follow-up(after 2 weeks)

  • Five Times Sit to Stand Test

    Functional Tests

    pre-training, post-training(after 6 weeks), follow-up(after 2 weeks)

  • Timed Up and Go Test

    Functional Tests

    pre-training, post-training(after 6 weeks), follow-up(after 2 weeks)

  • Six-Minute Walk Test

    Functional Tests

    pre-training, post-training(after 6 weeks), follow-up(after 2 weeks)

  • Over-ground walking

    Walking test

    pre-training, post-training(after 6 weeks), follow-up(after 2 weeks)

  • Walking on a treadmill

    Walking test

    pre-training, post-training(after 6 weeks), follow-up(after 2 weeks)

  • Delsys Trigno EMG analysis system

    Three-Dimensional Motion Analysis

    pre-training, post-training(after 6 weeks), follow-up(after 2 weeks)

  • Vicon Bonita

    Three-Dimensional Motion Analysis

    pre-training, post-training(after 6 weeks), follow-up(after 2 weeks)

  • Force plates

    Three-Dimensional Motion Analysis

    pre-training, post-training(after 6 weeks), follow-up(after 2 weeks)

Study Arms (2)

experimental group

EXPERIMENTAL

IMU-based balance training

Other: IMU-based balance training

control group

OTHER

General health education or exercise training

Other: general health education or exercise training

Interventions

IMU-based balance trainingOTHER

Leveraging AI technology to identify motion deficiencies, the experimental group will undergo IMU-based balance training

experimental group
general health education or exercise trainingOTHER

general health education or exercise training

control group

Eligibility Criteria

Age18 Years - 80 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Aged between 18 and 80 years capable of independent walking-

You may not qualify if:

  • history of lower limb orthopedic surgery, ankylosing spondylitis, rheumatoid arthritis, osteoarthritis, and other medical joint diseases
  • Those who cannot communicate or follow instructions, and those with severe visual or hearing impairments
  • the neurological impairment or vestibular disorders, such as stroke, spinal cord injury, Meniere's syndrome.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

National Taiwan University, College of Medicine, School and Graduate Institute of Physical Therapy

Taipei, 100, Taiwan

RECRUITING

MeSH Terms

Interventions

Exercise

Intervention Hierarchy (Ancestors)

Motor ActivityMovementMusculoskeletal Physiological PhenomenaMusculoskeletal and Neural Physiological Phenomena

Central Study Contacts

Hsu Wei-Li, Ph. D

CONTACT

886-2-33668127wlhsu@ntu.edu.tw

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Purpose
PREVENTION
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

September 11, 2024

First Posted

September 19, 2024

Study Start

November 3, 2023

Primary Completion (Estimated)

December 1, 2026

Study Completion (Estimated)

December 1, 2026

Last Updated

November 19, 2025

Record last verified: 2025-10

Locations

TW(1)