Radio-frequency (RF) sensing for deep awareness of human physical status
In recent years, there are a rise in studies of contactless Radio Frequency (RF) sensing for human physical status like one’s respiration behaviour. In these studies, a radar sensor will be used to collect the raw data from a human subject to provide insights on the respiration. This conventional me...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/157017 |
| _version_ | 1824456020733198336 |
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| author | Koh, Bernard Sheng Hui |
| author2 | Luo Jun |
| author_facet | Luo Jun Koh, Bernard Sheng Hui |
| author_sort | Koh, Bernard Sheng Hui |
| collection | NTU |
| description | In recent years, there are a rise in studies of contactless Radio Frequency (RF) sensing for human physical status like one’s respiration behaviour. In these studies, a radar sensor will be used to collect the raw data from a human subject to provide insights on the respiration. This conventional method includes the use of complex signal processing and domain expert for feature engineering to produce a result. This came the motivation of using deep learning to leverage or avoid this complication. In this project, an attempt is made to implement deep learning techniques on relatively unexplored field of predicting human respiration rate. Techniques like Denoising Convolutional Autoencoder (DCAE) is applied to denoise the potential noisy data then coupled with a 1-Dimensional Convolutional Neural Network (1-D CNN) to learn from these processed data to make a prediction. Despite the prediction results shown in this project are far from ideal, the proposed approach can be a good foundation for future study to build on. |
| first_indexed | 2025-02-19T03:47:28Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/157017 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:47:28Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1570172022-05-06T05:46:36Z Radio-frequency (RF) sensing for deep awareness of human physical status Koh, Bernard Sheng Hui Luo Jun School of Computer Science and Engineering junluo@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Computer science and engineering::Computing methodologies::Pattern recognition In recent years, there are a rise in studies of contactless Radio Frequency (RF) sensing for human physical status like one’s respiration behaviour. In these studies, a radar sensor will be used to collect the raw data from a human subject to provide insights on the respiration. This conventional method includes the use of complex signal processing and domain expert for feature engineering to produce a result. This came the motivation of using deep learning to leverage or avoid this complication. In this project, an attempt is made to implement deep learning techniques on relatively unexplored field of predicting human respiration rate. Techniques like Denoising Convolutional Autoencoder (DCAE) is applied to denoise the potential noisy data then coupled with a 1-Dimensional Convolutional Neural Network (1-D CNN) to learn from these processed data to make a prediction. Despite the prediction results shown in this project are far from ideal, the proposed approach can be a good foundation for future study to build on. Bachelor of Engineering (Computer Science) 2022-05-06T05:46:36Z 2022-05-06T05:46:36Z 2022 Final Year Project (FYP) Koh, B. S. H. (2022). Radio-frequency (RF) sensing for deep awareness of human physical status. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157017 https://hdl.handle.net/10356/157017 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Computer science and engineering::Computing methodologies::Pattern recognition Koh, Bernard Sheng Hui Radio-frequency (RF) sensing for deep awareness of human physical status |
| title | Radio-frequency (RF) sensing for deep awareness of human physical status |
| title_full | Radio-frequency (RF) sensing for deep awareness of human physical status |
| title_fullStr | Radio-frequency (RF) sensing for deep awareness of human physical status |
| title_full_unstemmed | Radio-frequency (RF) sensing for deep awareness of human physical status |
| title_short | Radio-frequency (RF) sensing for deep awareness of human physical status |
| title_sort | radio frequency rf sensing for deep awareness of human physical status |
| topic | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Computer science and engineering::Computing methodologies::Pattern recognition |
| url | https://hdl.handle.net/10356/157017 |
| work_keys_str_mv | AT kohbernardshenghui radiofrequencyrfsensingfordeepawarenessofhumanphysicalstatus |