Application of Smart Electric Vehicles in Analyzing Gait Abnormalities in Patients With Neurodegenerative Diseases
NCT ID: NCT07143006
Last Updated: 2025-12-03
Study Results
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Basic Information
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COMPLETED
NA
120 participants
INTERVENTIONAL
2025-08-20
2025-10-30
Brief Summary
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Detailed Description
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As Taiwan enters a super-aged society, the number of patients with neurodegenerative diseases is growing yearly. Despite Long-Term Care 2.0 addressing this issue, there is a lack of therapists, leading to insufficient training for patients. Therefore, an innovative way to promote gait training is needed. The use of Artificial Intelligence (AI)-driven smart electric vehicles for detecting and improving gait abnormalities is becoming feasible with the advancement of AI. This technology can monitor and analyze gait in real time and provide feedback to users to improve stride, speed, or balance. The application of AI smart electric vehicles in gait training and assistance for patients with neurodegenerative diseases could span multiple settings, including hospitals and subacute rehabilitation centers, residential care institutions, home environments, and community health centers and aging community hubs.
Inventec Medical Technology's BestShape Go Intelligent Generation Transformable Electric Vehicle represents profound care for the related population and those with mobility difficulties. This smart electric vehicle has dual modes of riding and assisted walking. The assisted walking function provides users with a sense of security and appropriate guidance while immediately tracking and detecting potential danger, making it a potential AI gait training partner.
Project Objective: To explore the possibility of smart electric vehicles providing comprehensive gait assistance and improvement for patients with neurodegenerative diseases. Research Design: As a phase one study, this project tests the ability of smart electric vehicles to detect and analyze the abnormal gait of patients with neurodegenerative diseases during short-term (60 minutes) gait training, and the improvement in walking and balance when using smart electric vehicles after training.
Research Goal: To assess the effect of detection and training under the guidance of smart electric vehicles in improving the walking speed and stability of patients with neurodegenerative diseases.
Research Method: The target group consists of patients diagnosed with mild neurodegenerative diseases and walking disabilities. Selection criteria include age, walking ability, cognitive status, etc. Inventec's smart vehicle is equipped with sensors for monitoring gait and analyzing gait data through AI. Participants undergo initial gait assessment, including walking speed and balance tests, using the 6-meter Timed-up-and-Go method. They then engage in 45 minutes of gait training, using the smart electric vehicle for stride adjustment, speed control, and balance practice, with real-time feedback. Finally, participants undergo the 6-meter Timed-up-and-Go test again to compare progress. Expected Outcome: Training with the smart electric vehicle will significantly improve the walking speed and balance ability of patients with neurodegenerative diseases.
Conditions
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Study Design
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NA
SINGLE_GROUP
SUPPORTIVE_CARE
NONE
Study Groups
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Treatment arm
Gait abnormalities in patients with neurodegenerative diseases.
BestShape Go Intelligent Generation Transformable Electric Vehicle
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 long-term tracking, as well as adding interactive and entertainment elements.
Interventions
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BestShape Go Intelligent Generation Transformable Electric Vehicle
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 long-term tracking, as well as adding interactive and entertainment elements.
Eligibility Criteria
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Inclusion Criteria
2. Age: 60-85 years.
3. Capable of walking to some extent, but may have mild to moderate gait disturbances.
4. Able to understand the trial procedures and give informed consent.
Exclusion Criteria
2. Conditions such as heart disease, uncontrolled high blood pressure, or a history of major surgery.
3. Severe cognitive impairment preventing understanding of the trial procedures or giving informed consent.
4. Visual or auditory impairments severe enough to prevent following trial instructions.
5. Participation in other clinical trials within a certain period in the past, which could affect the assessment of results.
60 Years
85 Years
ALL
No
Sponsors
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Taipei Medical University Shuang Ho Hospital
OTHER
Responsible Party
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Chien Tai Hong
Doctor, Professor, Principal Investigator
Principal Investigators
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Lung Chan, MD, PhD
Role: PRINCIPAL_INVESTIGATOR
Taipei Medical University Shuang Ho Hospital
Locations
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Shuang Ho Hospital
New Taipei City, , Taiwan
Countries
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Other Identifiers
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N202402036
Identifier Type: -
Identifier Source: org_study_id
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