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NCT Number: NCT07230366

Clinical Validation of AI-powered Smart Vehicle Assisted Gait Training in Neurodegenerative Disorders

This study aims to verify the safety and preliminary clinical benefits of long-term gait training using AI-powered smart electric vehicles for patients with neurodegenerative diseases such as Parkinson's disease and dementia.

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Key information

Age range

50 year–85 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

About this study

This study is a single-center, prospective, open-label clinical intervention trial aimed at verifying the clinical safety and preliminary efficacy of an AI-powered smart electric vehicle in gait training for patients with Parkinson's disease and dementia. It is expected to recruit 120 participants aged 50-85 years, who will be randomly assigned to different training durations (2~12 weeks), with training sessions conducted two or three times a week, each lasting 30 to 60 minutes. The primary assessment indicators include gait speed, number of falls, and gait confidence scale, while secondary assessments include satisfaction and balance function. All study data will be coded and preserved for 10 years. The study is funded by the "Healthy Taiwan Cultivation Plan."

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • Patients with neurodegenerative diseases (such as Parkinson's disease or dementia).
  • Age between 50-85 years.
  • Capable of walking for at least 10 meters, but may have unsteady gait or history of falls.
  • Able to understand the trial procedures and give informed consent.

Exclusion criteria

  • Severe cardiopulmonary disease or recent major surgery.
  • Unable to walk or requiring comprehensive physical support.
  • Severe cognitive impairment preventing understanding of the trial procedures or giving informed consent.
  • Visual or auditory impairments severe enough to prevent following trial instructions.

Treatment and study plan

BestShape Go Intelligent Generation Transformable Electric Vehicle

Device

The specific applications of artificial intelligence in intelligent electric vehicles mainly include gait monitoring and analysis, real-time feedback and guidance, autonomous adaptive assistance, safety prevention and warnings, data collection and longterm tracking, as well as adding interactive and entertainment elements.

Primary outcomes

  1. Gait speed

    Time frame: Before & after training (the training sessions will last for 2~12 weeks).

Secondary outcomes

  1. Gait length

    Time frame: Before & after training (the training sessions will last for 2~12 weeks).

  2. Number of falls

    Time frame: During 2~12 training sessions.

  3. Patients' gait confidence scale

    Time frame: Before & after training (the training sessions will last for 2~12 weeks).

  4. Patients' balance function

    Time frame: Before & after training (the training sessions will last for 2~12 weeks).

    Timed-up-and-Go Test

  5. Patients' feedback

    Time frame: Before & after training (the training sessions will last for 2~12 weeks).

    Clinical Global Impression (CGI)

Study contacts

Contact information is provided by the study sponsor or research team.

Chien Tai Hong, MD, PhD

CONTACT

[email protected]

+886 970747668

Likai Huang, MD

CONTACT

[email protected]

Sponsors and collaborators

Lead sponsor

Taipei Medical University Shuang Ho Hospital

Other

Registry information

Important dates

Study start
2026
Primary completion
2028
Study completion
2028
First posted
Nov 17, 2025
Registry last updated
Dec 10, 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.

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