An intelligent humidity sensing system for human behavior recognition
Abstract An intelligent humidity sensing system has been developed for real-time monitoring of human behaviors through respiration detection. The key component of this system is a humidity sensor that integrates a thermistor and a micro-heater. This sensor employs porous nanoforests as its sensing m...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2025-01-01
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| Series: | Microsystems & Nanoengineering |
| Online Access: | https://doi.org/10.1038/s41378-024-00863-6 |
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| _version_ | 1832585638139920384 |
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| author | Huabin Yang Qiming Guo Guidong Chen Yuefang Zhao Meng Shi Na Zhou Chengjun Huang Haiyang Mao |
| author_facet | Huabin Yang Qiming Guo Guidong Chen Yuefang Zhao Meng Shi Na Zhou Chengjun Huang Haiyang Mao |
| author_sort | Huabin Yang |
| collection | DOAJ |
| description | Abstract An intelligent humidity sensing system has been developed for real-time monitoring of human behaviors through respiration detection. The key component of this system is a humidity sensor that integrates a thermistor and a micro-heater. This sensor employs porous nanoforests as its sensing material, achieving a sensitivity of 0.56 pF/%RH within a range of 60–90% RH, along with excellent long-term stability and superior gas selectivity. The micro-heater in the device provides a high operating temperature, enhancing sensitivity by 5.8 times. This significant improvement enables the capture of weak humidity variations in exhaled gases, while the thermistor continuously monitors the sensor’s temperature during use and provides crucial temperature information related to respiration. With the assistance of a machine learning algorithm, a behavior recognition system based on the humidity sensor has been constructed, enabling behavior states to be classified and identified with an accuracy of up to 96.2%. This simple yet intelligent method holds great potential for widespread applications in medical assistance analysis and daily health monitoring. |
| format | Article |
| id | doaj-art-5f8fa5f006e5455ca141d730631419fb |
| institution | Kabale University |
| issn | 2055-7434 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Publishing Group |
| record_format | Article |
| series | Microsystems & Nanoengineering |
| spelling | doaj-art-5f8fa5f006e5455ca141d730631419fb2025-01-26T12:38:22ZengNature Publishing GroupMicrosystems & Nanoengineering2055-74342025-01-0111111110.1038/s41378-024-00863-6An intelligent humidity sensing system for human behavior recognitionHuabin Yang0Qiming Guo1Guidong Chen2Yuefang Zhao3Meng Shi4Na Zhou5Chengjun Huang6Haiyang Mao7Institute of Microelectronics of the Chinese Academy of SciencesInstitute of Microelectronics of the Chinese Academy of SciencesInstitute of Microelectronics of the Chinese Academy of SciencesInstitute of Microelectronics of the Chinese Academy of SciencesInstitute of Microelectronics of the Chinese Academy of SciencesInstitute of Microelectronics of the Chinese Academy of SciencesInstitute of Microelectronics of the Chinese Academy of SciencesInstitute of Microelectronics of the Chinese Academy of SciencesAbstract An intelligent humidity sensing system has been developed for real-time monitoring of human behaviors through respiration detection. The key component of this system is a humidity sensor that integrates a thermistor and a micro-heater. This sensor employs porous nanoforests as its sensing material, achieving a sensitivity of 0.56 pF/%RH within a range of 60–90% RH, along with excellent long-term stability and superior gas selectivity. The micro-heater in the device provides a high operating temperature, enhancing sensitivity by 5.8 times. This significant improvement enables the capture of weak humidity variations in exhaled gases, while the thermistor continuously monitors the sensor’s temperature during use and provides crucial temperature information related to respiration. With the assistance of a machine learning algorithm, a behavior recognition system based on the humidity sensor has been constructed, enabling behavior states to be classified and identified with an accuracy of up to 96.2%. This simple yet intelligent method holds great potential for widespread applications in medical assistance analysis and daily health monitoring.https://doi.org/10.1038/s41378-024-00863-6 |
| spellingShingle | Huabin Yang Qiming Guo Guidong Chen Yuefang Zhao Meng Shi Na Zhou Chengjun Huang Haiyang Mao An intelligent humidity sensing system for human behavior recognition Microsystems & Nanoengineering |
| title | An intelligent humidity sensing system for human behavior recognition |
| title_full | An intelligent humidity sensing system for human behavior recognition |
| title_fullStr | An intelligent humidity sensing system for human behavior recognition |
| title_full_unstemmed | An intelligent humidity sensing system for human behavior recognition |
| title_short | An intelligent humidity sensing system for human behavior recognition |
| title_sort | intelligent humidity sensing system for human behavior recognition |
| url | https://doi.org/10.1038/s41378-024-00863-6 |
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