Cognitive Brain Age Estimation Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.47392/irjaeh.2025.0089
· OA: W4408803598
Cognitive brain age estimation combines computational techniques with health sciences to assess cognitive health. Traditional methods like neuroimaging and clinical evaluations are costly and not scalable. This research proposes a machine learning-based system for cognitive age estimation using non-invasive data, including speech patterns, behavioral metrics, and lifestyle factors. The system follows a modular architecture with data collection, preprocessing, feature extraction, and predictive modelling. By analyzing behavioral logs, speech characteristics, and lifestyle metrics, it generates real-time cognitive age estimates. This scalable and cost-effective approach, free from neuroimaging, enables deployment in healthcare settings and wearable devices. It also supports large-scale applications, such as public health monitoring and aging studies, enhancing accessibility, early detection, and personalized interventions in cognitive health.
