Literature DB >> 31195383

Recent development of respiratory rate measurement technologies.

Haipeng Liu1, John Allen, Dingchang Zheng, Fei Chen.   

Abstract

Respiratory rate (RR) is an important physiological parameter whose abnormality has been regarded as an important indicator of serious illness. In order to make RR monitoring simple to perform, reliable and accurate, many different methods have been proposed for such automatic monitoring. According to the theory of respiratory rate extraction, methods are categorized into three modalities: extracting RR from other physiological signals, RR measurement based on respiratory movements, and RR measurement based on airflow. The merits and limitations of each method are highlighted and discussed. In addition, current works are summarized to suggest key directions for the development of future RR monitoring methodologies.

Mesh:

Year:  2019        PMID: 31195383     DOI: 10.1088/1361-6579/ab299e

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  31 in total

1.  An easy and accurate respiratory rate monitor is necessary.

Authors:  Nicolas Marjanovic; Olivier Mimoz; Jérémy Guenezan
Journal:  J Clin Monit Comput       Date:  2019-07-24       Impact factor: 2.502

2.  Significance of considering respiratory movement in estimating sleep stage.

Authors:  Haipeng Liu; Yuhang Xu; Dingchang Zheng
Journal:  Biomed Eng Lett       Date:  2020-03-18

3.  Clinical evaluation of stretchable and wearable inkjet-printed strain gauge sensor for respiratory rate monitoring at different measurements locations.

Authors:  Ala'aldeen Al-Halhouli; Loiy Al-Ghussain; Saleem El Bouri; Haipeng Liu; Dingchang Zheng
Journal:  J Clin Monit Comput       Date:  2020-02-22       Impact factor: 2.502

Review 4.  Advancements in Methods and Camera-Based Sensors for the Quantification of Respiration.

Authors:  Haythem Rehouma; Rita Noumeir; Sandrine Essouri; Philippe Jouvet
Journal:  Sensors (Basel)       Date:  2020-12-17       Impact factor: 3.576

5.  Frequency-Modulated Continuous Wave Radar Respiratory Pattern Detection Technology Based on Multifeature.

Authors:  Qisong Wang; Zhening Dong; Dan Liu; Tianao Cao; Meiyan Zhang; Runqiao Liu; Xiaocong Zhong; Jinwei Sun
Journal:  J Healthc Eng       Date:  2021-08-09       Impact factor: 2.682

6.  Estimating Heart Rate and Respiratory Rate from a Single Lead Electrocardiogram Using Ensemble Empirical Mode Decomposition and Spectral Data Fusion.

Authors:  Iau-Quen Chung; Jen-Te Yu; Wei-Chi Hu
Journal:  Sensors (Basel)       Date:  2021-02-08       Impact factor: 3.576

7.  Future trends in measuring physiology in free-living animals.

Authors:  H J Williams; J Ryan Shipley; C Rutz; M Wikelski; M Wilkes; L A Hawkes
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2021-06-28       Impact factor: 6.671

8.  Respiration pattern recognition by wearable mask device.

Authors:  Vishal Varun Tipparaju; Di Wang; Jingjing Yu; Fang Chen; Francis Tsow; Erica Forzani; Nongjian Tao; Xiaojun Xian
Journal:  Biosens Bioelectron       Date:  2020-09-03       Impact factor: 10.618

9.  A real-time camera-based adaptive breathing monitoring system.

Authors:  Yu-Ching Lee; Abdan Syakura; Muhammad Adil Khalil; Ching-Ho Wu; Yi-Fang Ding; Ching-Wei Wang
Journal:  Med Biol Eng Comput       Date:  2021-06-08       Impact factor: 2.602

10.  Non-Contact Respiration Measurement Method Based on RGB Camera Using 1D Convolutional Neural Networks.

Authors:  Hyeon-Sang Hwang; Eui-Chul Lee
Journal:  Sensors (Basel)       Date:  2021-05-15       Impact factor: 3.576

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