Pregled bibliografske jedinice broj: 1058093
A Data-Fusion Algorithm for Respiration Rate Extraction Based on UWB Transversal Propagation Method
A Data-Fusion Algorithm for Respiration Rate Extraction Based on UWB Transversal Propagation Method // 2020 IEEE International Instrumentation and Measurement Technology Conference Proceedings / Rapuano, Sergio ; Van Moer, Wendy ; Vasic, Darko (ur.) (ur.).
Piscataway (NJ): Institute of Electrical and Electronics Engineers (IEEE), 2020. str. 1-5 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
A Data-Fusion Algorithm for Respiration Rate
Extraction Based on UWB Transversal Propagation
Method
Autori
Čuljak, Ivana ; Mihaldinec, Hrvoje ; Džapo, Hrvoje ; Cifrek, Mario
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
2020 IEEE International Instrumentation and Measurement Technology Conference Proceedings
/ Rapuano, Sergio ; Van Moer, Wendy ; Vasic, Darko (ur.) - Piscataway (NJ) : Institute of Electrical and Electronics Engineers (IEEE), 2020, 1-5
Skup
2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC 2020)
Mjesto i datum
Dubrovnik, Hrvatska, 25.05.2020. - 28.05.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
UWB ; transversal propagation method ; data fusion
Sažetak
This paper presents a data-fusion algorithm for respiration rate (RR) extraction by employing the ultra-wideband (UWB) transversal propagation measurement method. In the experimental scenario the UWB transmitter and receiver units were placed on the front and back sides of the thoracic wall. The measurement principle is based on the fact that periodic movements of lung affect the communication channel properties that can be measured. We measured the energy attenuation variations on the receiver side caused by tissue movements from which we extracted the information about the respiration rate. For testing purpose a custom developed UWB platform suitable for on-body placement was used, with an integrated inertial motion unit (IMU) sensor. UWB and IMU signals were combined by means of a data fusion algorithm. Data fusion algorithms based on Extended Kalman filtering (EKF) and Naïve Bayes inference show better estimation performance than a estimation from individual signal sources. The obtained error rate of RR estimation by means of the proposed data fusion method is lower than 0.2 respiration per minute (rpm) in comparison to the reference respiration system. Our results show that the proposed method of UWB and IMU sensor fusion is a promising candidate for reliable RR monitoring by compact wearable units under relatively non- stationary body movement conditions.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb