Artificial Intelligence and Digital Technologies in Prakriti Assessment: Toward Standardized Evidence-Based Ayurvedic...

Area of Science:

• Integrative Medicine and Computational Health
• Ayurvedic Science and Digital Health Technology

Background:

• Prakriti, an Ayurvedic concept, classifies individuals by physical, physiological, and psychological attributes for personalized health strategies.
• Traditional Prakriti assessment methods suffer from subjectivity, limited reproducibility, and lack of standardization.

Purpose of the Study:

• To systematically review and synthesize literature on digital, AI, and ML tools for Prakriti assessment.
• To identify technologies applicable to the Central Council for Research in Ayurvedic Sciences (CCRAS) Prakriti Assessment Manual parameters.

Main Methods:

• Systematic literature search across scientific databases and institutional repositories.
• Categorization of identified digital tools based on relevance to physical, physiological, psychological, and behavioral domains.
• Emphasis on technologies enabling objective measurement and computational analysis.

Main Results:

• Emerging digital, AI, and ML tools offer potential for objective and reliable Prakriti assessment.
• Integration of physiological sensors, image analysis, and algorithms can improve accuracy and clinical relevance.
• Convergence of Ayurveda and digital health shows promise for evidence generation and interdisciplinary research.

Conclusions:

• Digital innovations can significantly enhance the rigor, reach, and impact of Prakriti assessment in integrative healthcare.
• Addressing challenges in data quality, interoperability, interpretability, and validation is crucial for adoption.
• Modernizing Prakriti assessment through technology supports personalized and evidence-based medicine.