AI-Based Neck Exercise Program Validity and Reliability Study in Thailand

Thailand-based study evaluating a real-time AI neck exercise program with 30 healthy participants aged 18–29 years. The dataset likely contains results from five exercises, including content validity index (IOC) scores for accuracy, execution times, and intraclass correlation coefficients (ICC) for reliability. The data was uploaded by Yadanuch Boonyaratana on May 19, 2026, under a CC-BY-4.0 license.

Use Cases

• Validate AI algorithm performance for exercise monitoring based on reported content validity index (IOC) scores.
• Analyze the relationship between exercise accuracy and execution time based on Pearson correlation coefficients mentioned.
• Assess the reliability of digital health metrics based on reported intraclass correlation coefficient (ICC) values for accuracy and time.
• Benchmark AI-based exercise programs against traditional methods based on the study's validity and reliability framework.

Strengths

• Includes validity scores with reported IOC values between 0.86 and 1.00 across five exercises.
• Provides reliability metrics with reported ICC values of 0.63 for accuracy and 0.622 for execution time.
• Data is from a controlled study with 30 participants in a defined age range (18–29 years).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The 1.7 MB file size suggests a small-scale dataset, potentially limiting statistical power.

Provenance

Source

figshare, uploaded by Yadanuch Boonyaratana.

Collection Method

Study evaluating validity and reliability of an AI-based neck exercise program among 30 healthy participants.

Freshness

Last updated 2026-05-19 05:38:23; freshness should be verified.

Geography

Thailand