Indoor Activity and Vital Sign Monitoring for Moving People with Multiple Radar Data Fusion
The monitoring of human activity and vital signs plays a significant role in remote health-care. Radar provides a non-contact monitoring approach without privacy and illumination concerns. However, multiple people in a narrow indoor environment bring dense multipaths for activity monitoring, and the...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/18/3791 |
| _version_ | 1797517314833252352 |
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| author | Xiuzhu Yang Xinyue Zhang Yi Ding Lin Zhang |
| author_facet | Xiuzhu Yang Xinyue Zhang Yi Ding Lin Zhang |
| author_sort | Xiuzhu Yang |
| collection | DOAJ |
| description | The monitoring of human activity and vital signs plays a significant role in remote health-care. Radar provides a non-contact monitoring approach without privacy and illumination concerns. However, multiple people in a narrow indoor environment bring dense multipaths for activity monitoring, and the received vital sign signals are heavily distorted with body movements. This paper proposes a framework based on Frequency Modulated Continuous Wave (FMCW) and Impulse Radio Ultra-Wideband (IR-UWB) radars to address these challenges, designing intelligent spatial-temporal information fusion for activity and vital sign monitoring. First, a local binary pattern (LBP) and energy features are extracted from FMCW radar, combined with the wavelet packet transform (WPT) features on IR-UWB radar for activity monitoring. Then the additional information guided fusing network (A-FuseNet) is proposed with a modified generative and adversarial structure for vital sign monitoring. A Cascaded Convolutional Neural Network (CCNN) module and a Long Short Term Memory (LSTM) module are designed as the fusion sub-network for vital sign information extraction and multisensory data fusion, while a discrimination sub-network is constructed to optimize the fused heartbeat signal. In addition, the activity and movement characteristics are introduced as additional information to guide the fusion and optimization. A multi-radar dataset with an FMCW and two IR-UWB radars in a cotton tent, a small room and a wide lobby is constructed, and the accuracies of activity and vital sign monitoring achieve 99.9% and 92.3% respectively. Experimental results demonstrate the superiority and robustness of the proposed framework. |
| first_indexed | 2024-03-10T07:14:56Z |
| format | Article |
| id | doaj.art-e82b7c9614e54cab9b6381ed2c6a10d5 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T07:14:56Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-e82b7c9614e54cab9b6381ed2c6a10d52023-11-22T15:08:26ZengMDPI AGRemote Sensing2072-42922021-09-011318379110.3390/rs13183791Indoor Activity and Vital Sign Monitoring for Moving People with Multiple Radar Data FusionXiuzhu Yang0Xinyue Zhang1Yi Ding2Lin Zhang3School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSchool of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSchool of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSchool of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaThe monitoring of human activity and vital signs plays a significant role in remote health-care. Radar provides a non-contact monitoring approach without privacy and illumination concerns. However, multiple people in a narrow indoor environment bring dense multipaths for activity monitoring, and the received vital sign signals are heavily distorted with body movements. This paper proposes a framework based on Frequency Modulated Continuous Wave (FMCW) and Impulse Radio Ultra-Wideband (IR-UWB) radars to address these challenges, designing intelligent spatial-temporal information fusion for activity and vital sign monitoring. First, a local binary pattern (LBP) and energy features are extracted from FMCW radar, combined with the wavelet packet transform (WPT) features on IR-UWB radar for activity monitoring. Then the additional information guided fusing network (A-FuseNet) is proposed with a modified generative and adversarial structure for vital sign monitoring. A Cascaded Convolutional Neural Network (CCNN) module and a Long Short Term Memory (LSTM) module are designed as the fusion sub-network for vital sign information extraction and multisensory data fusion, while a discrimination sub-network is constructed to optimize the fused heartbeat signal. In addition, the activity and movement characteristics are introduced as additional information to guide the fusion and optimization. A multi-radar dataset with an FMCW and two IR-UWB radars in a cotton tent, a small room and a wide lobby is constructed, and the accuracies of activity and vital sign monitoring achieve 99.9% and 92.3% respectively. Experimental results demonstrate the superiority and robustness of the proposed framework.https://www.mdpi.com/2072-4292/13/18/3791activity monitoringvital sign monitoringFMCW radarIR-UWB radarfeature extraction and fusionCCNN |
| spellingShingle | Xiuzhu Yang Xinyue Zhang Yi Ding Lin Zhang Indoor Activity and Vital Sign Monitoring for Moving People with Multiple Radar Data Fusion Remote Sensing activity monitoring vital sign monitoring FMCW radar IR-UWB radar feature extraction and fusion CCNN |
| title | Indoor Activity and Vital Sign Monitoring for Moving People with Multiple Radar Data Fusion |
| title_full | Indoor Activity and Vital Sign Monitoring for Moving People with Multiple Radar Data Fusion |
| title_fullStr | Indoor Activity and Vital Sign Monitoring for Moving People with Multiple Radar Data Fusion |
| title_full_unstemmed | Indoor Activity and Vital Sign Monitoring for Moving People with Multiple Radar Data Fusion |
| title_short | Indoor Activity and Vital Sign Monitoring for Moving People with Multiple Radar Data Fusion |
| title_sort | indoor activity and vital sign monitoring for moving people with multiple radar data fusion |
| topic | activity monitoring vital sign monitoring FMCW radar IR-UWB radar feature extraction and fusion CCNN |
| url | https://www.mdpi.com/2072-4292/13/18/3791 |
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