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Anthropometric measurements are commonly employed to evaluate body composition, morphology, and health-related parameters across diverse populations. While a cost-effective and field-friendly method, the COVID-19 pandemic has spurred research on digital anthropometry worldwide. Machine learning, a fusion of artificial intelligence and data mining, holds promise for enhancing data collection and analysis in Kinanthropometry applications. Rather than replacing traditional methods, digital anthropometry presents a significant opportunity to enhance accuracy, validity, practicality, and the implementation of self-monitoring procedures under professional guidance. The CyberMetron Project by DBSS aims to perform additional research and increase scientific literacy among practitioners for public awareness of digital anthropometry.
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