Overview

Artificial intelligence (AI) is currently one of the global focal points for industrial development, with its applications in healthcare steadily increasing, such as in disease prediction, image diagnosis, and drug development. AI assists healthcare professionals in clinical decision-making by training relevant models through algorithms, thereby enhancing medical efficiency and quality.

Currently, standardized tools are used in clinical settings to screen and assess various aspects of child development. Children's motor development levels are determined by comparing their performance against established norms. However, the current assessment methods primarily rely on on-site visual observation and recording by evaluators, which demands significant time and human resources.

This research aims to establish an automated screening tool for gross motor development in early intervention, suitable for independently walking children aged one to six years old in Taiwan. The goal is to reduce the time cost of manual assessment and enable remote healthcare applications.

Eligibility

Inclusion Criteria:

• Legal guardian willing to provide written informed consent.
• Males and females aged 1 to 6 years old.
• Capable of independent walking.

Exclusion Criteria:

• Non-native Chinese speakers.