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Predicting driving accident prevention indicators for the elderly using machine learning algorithms based on physical abilities improved through agility & quickness exercise program treatment

Predicting driving accident prevention indicators for the elderly using machine learning algorithms based on physical abilities improved through agility & quickness exercise program treatment

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
CRIS
Registry ID
KCT0010808
Enrollment
60
Registered
2025-07-25
Start date
2024-07-01
Completion date
Unknown
Last updated
2025-08-18

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Interventions

Sponsors

Kangwon National University
Lead Sponsor

Eligibility

Sex/Gender
Female

Inclusion criteria

Inclusion criteria: Min 65 years ~ Max 78 years (1) Individuals aged 65 years or older who were able to participate in regular resistance exercise, (2) Individuals who voluntarily agreed to participate in the study, (3) A person with a driver's license

Exclusion criteria

Exclusion criteria: (1) Individuals diagnosed with a musculoskeletal disorder in the past 6 months that prevents them from participating in walking or exercise programs; (2) Individuals with severe cardiovascular disease that precludes participation in resistance exercise programs; (3) Individuals unable to perform daily activities independently due to depression, anxiety, or insomnia; (4) Individuals currently taking any medication to lower blood glucose levels; (5) Individuals who are currently on a diet or planning to start a diet, or those already participating in two or more structured exercise sessions per week; (6) Individuals deemed unsuitable for participation in this clinical trial due to other medical conditions that may affect the outcomes, as determined by the attending physician or research staff. However, individuals taking antihypertensive or lipid-lowering medications will be allowed to participate if their medication regimen remains stable throughout the study period.

Design outcomes

Primary

MeasureTime frame
Body compositon(Height, Muscle mass, Fat mass, Fat percent);Driving simulation;Trail Making Test;Neurokines

Secondary

MeasureTime frame
physical fitness ;Agility & Reaction time test

Countries

Korea, Republic of

Contacts

Public ContactDeokhwa Jeong

Kangwon National University

93deokgoo@kangwon.ac.kr+82-33-250-6780

Outcome results

None listed

Source: CRIS (via WHO ICTRP) · Data processed: Feb 4, 2026