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

Data Sheet 2 from a study by Yadanuch Boonyaratana evaluates the validity and reliability of a real-time AI-based neck exercise program. The dataset includes results from 30 healthy participants aged 18–29 years across five exercises, measuring accuracy and execution time. The study was published on figshare in May 2026 under a CC-BY-4.0 license.

Use Cases

• Validate AI-based exercise assessment algorithms based on reported content validity index (IOC) and intraclass correlation coefficient (ICC) metrics.
• Analyze the relationship between exercise accuracy and execution time based on the Pearson correlation coefficient mentioned in the description.
• Benchmark performance of digital physiotherapy programs using the reported accuracy and timing data from five specific neck exercises.

Strengths

• Includes validity scores (IOC values between 0.86 and 1.00) and reliability metrics (ICC = 0.63 for accuracy, 0.622 for time) for five exercises.
• Data is from a controlled study with 30 participants in a defined age range (18–29 years).
• Published under a permissive CC-BY-4.0 license for reuse.

Limitations

• Row count and column-level documentation are unknown, which limits suitability assessment.
• The dataset is very small (224.4 KB), indicating limited scope.
• Data may reflect geographic and demographic bias inherent to the study's sample of young adults in Thailand.

Provenance

Source

Yadanuch Boonyaratana via figshare.

Collection Method

Evaluation study of an AI neck exercise program with 30 healthy participants.

Freshness

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

Geography

Thailand