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PIEE-f : Enhanced Exercise Intensity Prediction

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dc.contributor.author Selvarajah, Harivarshan
dc.date.accessioned 2024-03-04T05:08:42Z
dc.date.available 2024-03-04T05:08:42Z
dc.date.issued 2023
dc.identifier.citation Selvarajah, Harivarshan (2023) PIEE-f : Enhanced Exercise Intensity Prediction. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2018141
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1815
dc.description.abstract "Fitness is getting increasingly saturated with new technology and new inventions every day, and it is both a blessing and complexity. With modern advancements in fitness, we can measure fitness levels to a fair extent. With technological advancement, we can maintain our fitness with new and advanced equipment and medical procedure. However, it can often be alarming for a beginner to navigate the fitness world and can be overwhelming. To step into the realm of fitness, one must have significant knowledge gathered or have a coach or system that would guide them through the early process in today's world. It's become much more complex due to competition and the spread of social media and misinformation. As a beginner or an average gym goer, it is overwhelming to decide what type of training we should require, and coaches and online fitness prediction tools can help us with this but even though there are many problems with that, such as accessibility issues due to finance, geographic restriction and misinformation and fake gimmicks. Exercise intensity-based systems can resolve this dilemma. It gives beginners and others a very simplified approach to fitness and easy-to-follow guidelines based on their smartwatches' health metrics, or they could measure easily in a very cost-effective method. It combines a supervised machine learning method with an existing fitness level prediction algorithm to give simplistic and direct advice to the users, where they can immediately apply the advice, see the benefit, and constantly reevaluate their training according to their needs. " en_US
dc.language.iso en en_US
dc.publisher IIT en_US
dc.subject Supervised Machine Learning en_US
dc.subject Explainability Integrated en_US
dc.subject Exercise Intensity prediction en_US
dc.title PIEE-f : Enhanced Exercise Intensity Prediction en_US
dc.type Thesis en_US


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