Literature DB >> 17271674

Monitoring respiratory rate based on tracheal sounds. First experiences.

G Sierra1, V Telfort, B Popov, L G Durand, R Agarwal, V Lanzo.   

Abstract

The objective was to develop a non-invasive method for continuously monitoring respiratory rate (RR) based on tracheal sounds. 25 volunteers and 36 patients with chronic pulmonary diseases were enrolled in a clinical study. Tracheal sounds were acquired using a contact piezoelectric sensor placed on the examinee's throat and analyzed using a combined investigation of the sound envelope and frequency content. RR estimates were compared to reference measurements taken from a pneumotachometer coupled to a face mask worn by the examinee. RR was also manually counted by a respiratory technician. Two types of breathing (mouth and nose) and three different positions were studied (fowler, semi-fowler and supine). RR estimated in volunteers had a success rate (SR) of 96%, a correlation coefficient (r) of 0.99 and a standard error of the estimate (SEE) of 0.56. The RR estimated in patients was comparable or slightly better (SR = 85%, r = 0.93 and SEE = 1.49) than those obtained by manual count (SR = 82%, r = 0.91, SEE = 1.58), which is the method widely used in clinical settings. No significant difference in the capacity to estimate RR was found related to posture and breathing type, making this method useful for continuous monitoring.

Entities:  

Year:  2004        PMID: 17271674     DOI: 10.1109/IEMBS.2004.1403156

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  An acoustical respiratory phase segmentation algorithm using genetic approach.

Authors:  F Jin; F Sattar; D Y T Goh
Journal:  Med Biol Eng Comput       Date:  2009-07-29       Impact factor: 2.602

2.  A multi-channel acoustics monitor for perioperative respiratory monitoring: preliminary data.

Authors:  Kamal Jafarian; Majid Amineslami; Kamran Hassani; Mahdi Navidbakhsh; Mohammad Niakan Lahiji; D John Doyle
Journal:  J Clin Monit Comput       Date:  2015-04-14       Impact factor: 2.502

3.  A Novel Sleep Respiratory Rate Detection Method for Obstructive Sleep Apnea Based on Characteristic Moment Waveform.

Authors:  Yu Fang; Zhongwei Jiang; Haibin Wang
Journal:  J Healthc Eng       Date:  2018-01-10       Impact factor: 2.682

4.  Respiratory Motion and Airflow Estimation During Sleep Using Tracheal Movement and Sound.

Authors:  Nasim Montazeri Ghahjaverestan; Wei Fan; Cristiano Aguiar; Jackson Yu; T Douglas Bradley
Journal:  Nat Sci Sleep       Date:  2022-07-01
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.