Chintawar, Ajinkya Gajananrao (2024) The Fusion of Mind and Motion: Classifying Activity Levels with Biometric and Psychological Insights. Masters thesis, Dublin, National College of Ireland.
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Abstract
This study explores the application of machine learning models for classifying physical activities using biometric measures and personality traits. A dataset from Figshare, integrated with survey responses, was analyzed using two algorithms: Gradient Boosting and a Tuned Stacking Classifier. Gradient Boosting achieved the highest accuracy at 73%, while the Stacking Classifier demonstrated balanced performance across all metrics, achieving 72% and effectively addressing class imbalances. The study highlights the models’ real-world applicability through validation and visualization using a Tableau dashboard. Key predictors included Resting Heart Rate, Honesty-Humility personality trait, and BMI. Challenges such as class imbalance were addressed using SMOTE and imputation techniques. The findings emphasize the potential of machine learning in personalized health monitoring and promoting active lifestyles via wearable devices.
Item Type: | Thesis (Masters) |
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Supervisors: | Name Email Clifford, William UNSPECIFIED |
Uncontrolled Keywords: | Physical Activity Classification; Machine Learning; Biometric Data; Gradient Boosting; Personalized Health Interventions |
Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Biometric Identification Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine > Personal Health and Hygiene |
Divisions: | School of Computing > Master of Science in Data Analytics |
Depositing User: | Ciara O'Brien |
Date Deposited: | 02 Sep 2025 09:34 |
Last Modified: | 02 Sep 2025 09:34 |
URI: | https://norma.ncirl.ie/id/eprint/8687 |
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