Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors
Microwave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an...
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| Format: | Article |
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MDPI AG
2021-08-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/17/5735 |
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| author | Somayyeh Chamaani Alireza Akbarpour Marko Helbig Jürgen Sachs |
| author_facet | Somayyeh Chamaani Alireza Akbarpour Marko Helbig Jürgen Sachs |
| author_sort | Somayyeh Chamaani |
| collection | DOAJ |
| description | Microwave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an efficient method with good frequency resolution, is applied to back-reflected microwave signals to extract vital signs. It is shown that decomposing of the signal to its damping exponentials fulfilled by MPM gives the opportunity to separate signals, e.g., breathing and heartbeat, with high precision. A publicly online dataset (GUARDIAN), obtained by a continuous wave microwave sensor, is applied to evaluate the performance of MPM. Two methods of bandpass filtering (BPF) and variational mode decomposition (VMD) are also implemented. In addition to the GUARDIAN dataset, these methods are also applied to signals acquired by an ultra-wideband (UWB) sensor. It is concluded that when the vital sign is sufficiently strong and pure, all methods, e.g., MPM, VMD, and BPF, are appropriate for vital sign monitoring. However, in noisy cases, MPM has better performance. Therefore, for non-contact microwave vital sign monitoring, which is usually subject to noisy situations, MPM is a powerful method. |
| first_indexed | 2024-03-10T08:04:06Z |
| format | Article |
| id | doaj.art-9434f7293714440397bd868cc6607ff1 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T08:04:06Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9434f7293714440397bd868cc6607ff12023-11-22T11:11:34ZengMDPI AGSensors1424-82202021-08-012117573510.3390/s21175735Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave SensorsSomayyeh Chamaani0Alireza Akbarpour1Marko Helbig2Jürgen Sachs3Time-Domain Electromagnetics Laboratory, Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran 1631714191, IranTime-Domain Electromagnetics Laboratory, Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran 1631714191, IranBiosignal Processing Group, Technische Universität Ilmenau, 98693 Ilmenau, GermanyElectronic Measurements and Signal Processing Group, Technische Universität Ilmenau, 98693 Ilmenau, GermanyMicrowave sensors have recently been introduced as high-temporal resolution sensors, which could be used in the contactless monitoring of artery pulsation and breathing. However, accurate and efficient signal processing methods are still required. In this paper, the matrix pencil method (MPM), as an efficient method with good frequency resolution, is applied to back-reflected microwave signals to extract vital signs. It is shown that decomposing of the signal to its damping exponentials fulfilled by MPM gives the opportunity to separate signals, e.g., breathing and heartbeat, with high precision. A publicly online dataset (GUARDIAN), obtained by a continuous wave microwave sensor, is applied to evaluate the performance of MPM. Two methods of bandpass filtering (BPF) and variational mode decomposition (VMD) are also implemented. In addition to the GUARDIAN dataset, these methods are also applied to signals acquired by an ultra-wideband (UWB) sensor. It is concluded that when the vital sign is sufficiently strong and pure, all methods, e.g., MPM, VMD, and BPF, are appropriate for vital sign monitoring. However, in noisy cases, MPM has better performance. Therefore, for non-contact microwave vital sign monitoring, which is usually subject to noisy situations, MPM is a powerful method.https://www.mdpi.com/1424-8220/21/17/5735artery pulsation monitoringheart rate variabilitymatrix pencil methodmicrowave sensorvariational mode decompositionvital sign signal processing |
| spellingShingle | Somayyeh Chamaani Alireza Akbarpour Marko Helbig Jürgen Sachs Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors Sensors artery pulsation monitoring heart rate variability matrix pencil method microwave sensor variational mode decomposition vital sign signal processing |
| title | Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors |
| title_full | Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors |
| title_fullStr | Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors |
| title_full_unstemmed | Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors |
| title_short | Matrix Pencil Method for Vital Sign Detection from Signals Acquired by Microwave Sensors |
| title_sort | matrix pencil method for vital sign detection from signals acquired by microwave sensors |
| topic | artery pulsation monitoring heart rate variability matrix pencil method microwave sensor variational mode decomposition vital sign signal processing |
| url | https://www.mdpi.com/1424-8220/21/17/5735 |
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