Sensor-Location-Specific Joint Acquisition ...
Document type :
Compte-rendu et recension critique d'ouvrage
DOI :
Title :
Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications
Author(s) :
Metshein, Margus [Auteur]
Tallinn University of Technology [TalTech]
Abdullayev, Anar [Auteur]
Tallinn University of Technology [TalTech]
Gautier, Antoine [Auteur]
JUNIA [JUNIA]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Microélectronique Silicium - IEMN [MICROELEC SI - IEMN]
Larras, Benoit [Auteur]
JUNIA [JUNIA]
Microélectronique Silicium - IEMN [MICROELEC SI - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Frappe, Antoine [Auteur]
Microélectronique Silicium - IEMN [MICROELEC SI - IEMN]
JUNIA [JUNIA]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Cardiff, Barry [Auteur]
University College Dublin [Dublin] [UCD]
Annus, Paul [Auteur]
Tallinn University of Technology [TalTech]
Land, Raul [Auteur]
Tallinn University of Technology [TalTech]
Märtens, Olev [Auteur]
Tallinn University of Technology [TalTech]
Tallinn University of Technology [TalTech]
Abdullayev, Anar [Auteur]
Tallinn University of Technology [TalTech]
Gautier, Antoine [Auteur]
JUNIA [JUNIA]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Microélectronique Silicium - IEMN [MICROELEC SI - IEMN]
Larras, Benoit [Auteur]

JUNIA [JUNIA]
Microélectronique Silicium - IEMN [MICROELEC SI - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Frappe, Antoine [Auteur]

Microélectronique Silicium - IEMN [MICROELEC SI - IEMN]
JUNIA [JUNIA]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Cardiff, Barry [Auteur]
University College Dublin [Dublin] [UCD]
Annus, Paul [Auteur]
Tallinn University of Technology [TalTech]
Land, Raul [Auteur]
Tallinn University of Technology [TalTech]
Märtens, Olev [Auteur]
Tallinn University of Technology [TalTech]
Journal title :
Sensors
Special Issue Use of Smart Wearable Sensors and AI Methods in Providing P4 Medicine
Special Issue Use of Smart Wearable Sensors and AI Methods in Providing P4 Medicine
Pages :
7111
Publisher :
MDPI
Publication date :
2023-08
ISSN :
1424-8220
English keyword(s) :
cardiovascular system
convolutional neural networks
electrical bioimpedance
deep learning
photoplethysmography
non-invasive measurements
pulse wave
sensor fusion
small data machine learning
wearable devices
convolutional neural networks
electrical bioimpedance
deep learning
photoplethysmography
non-invasive measurements
pulse wave
sensor fusion
small data machine learning
wearable devices
HAL domain(s) :
Physique [physics]
Sciences de l'ingénieur [physics]
Sciences de l'ingénieur [physics]
English abstract : [en]
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 ...
Show more >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.Show less >
Show more >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.Show less >
Language :
Anglais
Popular science :
Non
Source :
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