Data analysis and visualization
Obesity and overweight have become a global issue and one of the most pressing concerns. According to the World Health Organization, nearly 2 billion persons are overweight, with 650 million obese [1]. As a result, there has been a rise in the number of people discussing weight loss. However, uninte...
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sg-ntu-dr.10356-1564482022-04-16T14:24:11Z Data analysis and visualization Tan, Eugene Teck Heng Shen Zhiqi School of Computer Science and Engineering ZQShen@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Obesity and overweight have become a global issue and one of the most pressing concerns. According to the World Health Organization, nearly 2 billion persons are overweight, with 650 million obese [1]. As a result, there has been a rise in the number of people discussing weight loss. However, unintentional weight loss can occur, where a person loses more than 5% of their body weight in 6 to 12 months without actively attempting to [2]. Many who experience unintentional weight loss do not realize it. Such unintentional weight loss could be a symptom of a potentially fatal major health condition, thus, it is critical to detect it. To address this issue, this project aims to introduce unobtrusive health monitoring which uses ambient sensor technology to collect human health-related data without disrupting their daily life [4]. This project has developed a doormat prototype where human weight data is collected by simply stepping on it without having to stop. Models that were utilized include Random Forest Regression and CatBoost Regression to train the data collected to build a prediction model. This model will be integrated into a web application where it can predict human weight and send a warning notification whenever it detects an occurrence of unintentional weight loss. Bachelor of Engineering (Computer Science) 2022-04-16T14:24:11Z 2022-04-16T14:24:11Z 2022 Final Year Project (FYP) Tan, E. T. H. (2022). Data analysis and visualization. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156448 https://hdl.handle.net/10356/156448 en SCSE21-0465 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Tan, Eugene Teck Heng Data analysis and visualization |
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Obesity and overweight have become a global issue and one of the most pressing concerns. According to the World Health Organization, nearly 2 billion persons are overweight, with 650 million obese [1]. As a result, there has been a rise in the number of people discussing weight loss. However, unintentional weight loss can occur, where a person loses more than 5% of their body weight in 6 to 12 months without actively attempting to [2]. Many who experience unintentional weight loss do not realize it. Such unintentional weight loss could be a symptom of a potentially fatal major health condition, thus, it is critical to detect it. To address this issue, this project aims to introduce unobtrusive health monitoring which uses ambient sensor technology to collect human health-related data without disrupting their daily life [4]. This project has developed a doormat prototype where human weight data is collected by simply stepping on it without having to stop. Models that were utilized include Random Forest Regression and CatBoost Regression to train the data collected to build a prediction model. This model will be integrated into a web application where it can predict human weight and send a warning notification whenever it detects an occurrence of unintentional weight loss. |
author2 |
Shen Zhiqi |
author_facet |
Shen Zhiqi Tan, Eugene Teck Heng |
format |
Final Year Project |
author |
Tan, Eugene Teck Heng |
author_sort |
Tan, Eugene Teck Heng |
title |
Data analysis and visualization |
title_short |
Data analysis and visualization |
title_full |
Data analysis and visualization |
title_fullStr |
Data analysis and visualization |
title_full_unstemmed |
Data analysis and visualization |
title_sort |
data analysis and visualization |
publisher |
Nanyang Technological University |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/156448 |
_version_ |
1731235784015478784 |