Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications
Background: Cardiovascular diseases (CVDs), being the culprit for one-third of deaths globally, constitute a challenge for biomedical instrumentation development, especially for early disease detection. Pulsating arterial blood flow, providing access to cardiac-related parameters, involves the whole...
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| Format: | Article |
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MDPI AG
2023-08-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/16/7111 |
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| author | Margus Metshein Anar Abdullayev Antoine Gautier Benoit Larras Antoine Frappe Barry Cardiff Paul Annus Raul Land Olev Märtens |
| author_facet | Margus Metshein Anar Abdullayev Antoine Gautier Benoit Larras Antoine Frappe Barry Cardiff Paul Annus Raul Land Olev Märtens |
| author_sort | Margus Metshein |
| collection | DOAJ |
| description | Background: Cardiovascular diseases (CVDs), being the culprit for one-third of deaths globally, constitute a challenge for biomedical instrumentation development, especially for early disease detection. Pulsating arterial blood flow, providing access to cardiac-related parameters, involves the whole body. Unobtrusive and continuous acquisition of electrical bioimpedance (EBI) and photoplethysmography (PPG) constitute important techniques for monitoring the peripheral arteries, requiring novel approaches and clever means. Methods: In this work, five peripheral arteries were selected for EBI and PPG signal acquisition. The acquisition sites were evaluated based on the signal morphological parameters. A small-data-based deep learning model, which increases the data by dividing them into cardiac periods, was proposed to evaluate the continuity of the signals. Results: The highest sensitivity of EBI was gained for the carotid artery (0.86%), three times higher than that for the next best, the posterior tibial artery (0.27%). The excitation signal parameters affect the measured EBI, confirming the suitability of classical 100 kHz frequency (average probability of 52.35%). The continuity evaluation of the EBI signals confirmed the advantage of the carotid artery (59.4%), while the posterior tibial artery (49.26%) surpasses the radial artery (48.17%). The PPG signal, conversely, commends the location of the posterior tibial artery (97.87%). Conclusions: The peripheral arteries are highly suitable for non-invasive EBI and PPG signal acquisition. The posterior tibial artery constitutes a candidate for the joint acquisition of EBI and PPG signals in sensor-fusion-based wearable devices—an important finding of this research. |
| first_indexed | 2024-03-10T23:35:30Z |
| format | Article |
| id | doaj.art-3bec0d8f2fa14e438e0309814fe2d829 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T23:35:30Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-3bec0d8f2fa14e438e0309814fe2d8292023-11-19T02:56:57ZengMDPI AGSensors1424-82202023-08-012316711110.3390/s23167111Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable ApplicationsMargus Metshein0Anar Abdullayev1Antoine Gautier2Benoit Larras3Antoine Frappe4Barry Cardiff5Paul Annus6Raul Land7Olev Märtens8Thomas Johann Seebeck Department of Electronics, Tallinn University of Technology, Ehitajate Tee 5, 19086 Tallinn, EstoniaThomas Johann Seebeck Department of Electronics, Tallinn University of Technology, Ehitajate Tee 5, 19086 Tallinn, EstoniaUniversity Lille, CNRS, Centrale Lille, Junia, University Polytechnique Hauts-de-France, UMR 8520-IEMN, F-59000 Lille, FranceUniversity Lille, CNRS, Centrale Lille, Junia, University Polytechnique Hauts-de-France, UMR 8520-IEMN, F-59000 Lille, FranceUniversity Lille, CNRS, Centrale Lille, Junia, University Polytechnique Hauts-de-France, UMR 8520-IEMN, F-59000 Lille, FranceSchool of Electrical and Electronic Engineering, University College Dublin, D04V1W8 Dublin, IrelandThomas Johann Seebeck Department of Electronics, Tallinn University of Technology, Ehitajate Tee 5, 19086 Tallinn, EstoniaThomas Johann Seebeck Department of Electronics, Tallinn University of Technology, Ehitajate Tee 5, 19086 Tallinn, EstoniaThomas Johann Seebeck Department of Electronics, Tallinn University of Technology, Ehitajate Tee 5, 19086 Tallinn, EstoniaBackground: Cardiovascular diseases (CVDs), being the culprit for one-third of deaths globally, constitute a challenge for biomedical instrumentation development, especially for early disease detection. Pulsating arterial blood flow, providing access to cardiac-related parameters, involves the whole body. Unobtrusive and continuous acquisition of electrical bioimpedance (EBI) and photoplethysmography (PPG) constitute important techniques for monitoring the peripheral arteries, requiring novel approaches and clever means. Methods: In this work, five peripheral arteries were selected for EBI and PPG signal acquisition. The acquisition sites were evaluated based on the signal morphological parameters. A small-data-based deep learning model, which increases the data by dividing them into cardiac periods, was proposed to evaluate the continuity of the signals. Results: The highest sensitivity of EBI was gained for the carotid artery (0.86%), three times higher than that for the next best, the posterior tibial artery (0.27%). The excitation signal parameters affect the measured EBI, confirming the suitability of classical 100 kHz frequency (average probability of 52.35%). The continuity evaluation of the EBI signals confirmed the advantage of the carotid artery (59.4%), while the posterior tibial artery (49.26%) surpasses the radial artery (48.17%). The PPG signal, conversely, commends the location of the posterior tibial artery (97.87%). Conclusions: The peripheral arteries are highly suitable for non-invasive EBI and PPG signal acquisition. The posterior tibial artery constitutes a candidate for the joint acquisition of EBI and PPG signals in sensor-fusion-based wearable devices—an important finding of this research.https://www.mdpi.com/1424-8220/23/16/7111cardiovascular systemconvolutional neural networkselectrical bioimpedancedeep learningphotoplethysmographynon-invasive measurements |
| spellingShingle | Margus Metshein Anar Abdullayev Antoine Gautier Benoit Larras Antoine Frappe Barry Cardiff Paul Annus Raul Land Olev Märtens Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications Sensors cardiovascular system convolutional neural networks electrical bioimpedance deep learning photoplethysmography non-invasive measurements |
| title | Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications |
| title_full | Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications |
| title_fullStr | Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications |
| title_full_unstemmed | Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications |
| title_short | Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications |
| title_sort | sensor location specific joint acquisition of peripheral artery bioimpedance and photoplethysmogram for wearable applications |
| topic | cardiovascular system convolutional neural networks electrical bioimpedance deep learning photoplethysmography non-invasive measurements |
| url | https://www.mdpi.com/1424-8220/23/16/7111 |
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