Monitoring and alerting system for sleep apnea patients
Obstructive Sleep Apnea is known as one of the chronic disorders and defined as a repeated episode of obstructive apnea during sleep. The standard diagnosis of the disorder can be complicated and costly. This report will address the implementation of a monitoring and alerting system for patients suf...
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2018
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sg-ntu-dr.10356-747232023-07-07T16:44:01Z Monitoring and alerting system for sleep apnea patients Lee, Shawn Yvonne Lam Ying Hung School of Electrical and Electronic Engineering DRNTU::Engineering Obstructive Sleep Apnea is known as one of the chronic disorders and defined as a repeated episode of obstructive apnea during sleep. The standard diagnosis of the disorder can be complicated and costly. This report will address the implementation of a monitoring and alerting system for patients suffering from this condition with the use of biosensor. Biological signals measured are the heart rate and oxygen saturation. The raw biological data will then be sent to a Raspberry Pi for further processing. Filters which includes moving average was used for the calibration. After filtering, the data will pass through a monitoring and alert algorithm. With that, the system will be able to send an alert once an apnea attack is detected. Bachelor of Engineering 2018-05-23T05:32:56Z 2018-05-23T05:32:56Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/74723 en Nanyang Technological University 54 p. application/pdf |
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Singapore Singapore |
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DRNTU::Engineering Lee, Shawn Monitoring and alerting system for sleep apnea patients |
| description |
Obstructive Sleep Apnea is known as one of the chronic disorders and defined as a repeated episode of obstructive apnea during sleep. The standard diagnosis of the disorder can be complicated and costly. This report will address the implementation of a monitoring and alerting system for patients suffering from this condition with the use of biosensor. Biological signals measured are the heart rate and oxygen saturation. The raw biological data will then be sent to a Raspberry Pi for further processing. Filters which includes moving average was used for the calibration. After filtering, the data will pass through a monitoring and alert algorithm. With that, the system will be able to send an alert once an apnea attack is detected. |
| author2 |
Yvonne Lam Ying Hung |
| author_facet |
Yvonne Lam Ying Hung Lee, Shawn |
| format |
Final Year Project |
| author |
Lee, Shawn |
| author_sort |
Lee, Shawn |
| title |
Monitoring and alerting system for sleep apnea patients |
| title_short |
Monitoring and alerting system for sleep apnea patients |
| title_full |
Monitoring and alerting system for sleep apnea patients |
| title_fullStr |
Monitoring and alerting system for sleep apnea patients |
| title_full_unstemmed |
Monitoring and alerting system for sleep apnea patients |
| title_sort |
monitoring and alerting system for sleep apnea patients |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10356/74723 |
| _version_ |
1772827819595792384 |