Influences of Sensor Placement Site and Subject Posture on Measurement of Respiratory Frequency Using Triaxial Accelerometers
Respiration frequency (RF) could be derived from the respiratory signals recorded by accelerometers which detect chest wall movements. The optimum direction of acceleration for accurate RF measurement is still uncertain. We aim to investigate the effect of measure site, posture, and direction of acc...
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Published in | Frontiers in physiology Vol. 11; p. 823 |
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Abstract | Respiration frequency (RF) could be derived from the respiratory signals recorded by accelerometers which detect chest wall movements. The optimum direction of acceleration for accurate RF measurement is still uncertain. We aim to investigate the effect of measure site, posture, and direction of acceleration on the accuracy of accelerometer-based RF estimation.
In supine and seated postures respectively, respiratory signals were measured from 34 healthy subjects in 70 s by triaxial accelerometers located at four sites on the body wall (over the clavicle, laterally on the chest wall, over the pectoral part of the anterior chest wall, on the abdomen in the midline at the umbilicus), with the reference respiratory signal simultaneously recorded by a strain gauge chest belt. RFs were extracted from the accelerometer and reference respiratory signals using wavelet transformation. To investigate the effect of measure site, posture, and direction of acceleration on the accuracy of accelerometer-based RF estimation, repeated measures multivariate analysis of variance, linear regression, Bland-Altman analysis, and Scheirer-Ray-Hare test were performed between reference and accelerometer-based RFs.
There was no significant difference in accelerometer-based RF estimation between seated and supine postures, among four accelerometer sites, or between seated or supine postures (
> 0.05 for all). The error of accelerometer-based RF estimation was less than 0.03 Hz (two breaths per minute) at any site or posture, but was significantly smaller in supine posture than in seated posture (
< 0.05), with narrower limits of agreement in Bland-Altman analysis and higher accuracy in linear regression (
> 0.61 vs.
< 0.51).
Respiration frequency can be accurately measured from the acceleration of any direction using triaxial accelerometers placed at the clavicular, pectoral and lateral sites on the chest as well the mid abdominal site. More accurate RF estimation could be achieved in supine posture compared with seated posture. |
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AbstractList | Respiration frequency (RF) could be derived from the respiratory signals recorded by accelerometers which detect chest wall movements. The optimum direction of acceleration for accurate RF measurement is still uncertain. We aim to investigate the effect of measure site, posture, and direction of acceleration on the accuracy of accelerometer-based RF estimation.
In supine and seated postures respectively, respiratory signals were measured from 34 healthy subjects in 70 s by triaxial accelerometers located at four sites on the body wall (over the clavicle, laterally on the chest wall, over the pectoral part of the anterior chest wall, on the abdomen in the midline at the umbilicus), with the reference respiratory signal simultaneously recorded by a strain gauge chest belt. RFs were extracted from the accelerometer and reference respiratory signals using wavelet transformation. To investigate the effect of measure site, posture, and direction of acceleration on the accuracy of accelerometer-based RF estimation, repeated measures multivariate analysis of variance, linear regression, Bland-Altman analysis, and Scheirer-Ray-Hare test were performed between reference and accelerometer-based RFs.
There was no significant difference in accelerometer-based RF estimation between seated and supine postures, among four accelerometer sites, or between seated or supine postures (
> 0.05 for all). The error of accelerometer-based RF estimation was less than 0.03 Hz (two breaths per minute) at any site or posture, but was significantly smaller in supine posture than in seated posture (
< 0.05), with narrower limits of agreement in Bland-Altman analysis and higher accuracy in linear regression (
> 0.61 vs.
< 0.51).
Respiration frequency can be accurately measured from the acceleration of any direction using triaxial accelerometers placed at the clavicular, pectoral and lateral sites on the chest as well the mid abdominal site. More accurate RF estimation could be achieved in supine posture compared with seated posture. Respiration frequency (RF) could be derived from the respiratory signals recorded by accelerometers which detect chest wall movements. The optimum direction of acceleration for accurate RF measurement is still uncertain. We aim to investigate the effect of measure site, posture, and direction of acceleration on the accuracy of accelerometer-based RF estimation.INTRODUCTIONRespiration frequency (RF) could be derived from the respiratory signals recorded by accelerometers which detect chest wall movements. The optimum direction of acceleration for accurate RF measurement is still uncertain. We aim to investigate the effect of measure site, posture, and direction of acceleration on the accuracy of accelerometer-based RF estimation.In supine and seated postures respectively, respiratory signals were measured from 34 healthy subjects in 70 s by triaxial accelerometers located at four sites on the body wall (over the clavicle, laterally on the chest wall, over the pectoral part of the anterior chest wall, on the abdomen in the midline at the umbilicus), with the reference respiratory signal simultaneously recorded by a strain gauge chest belt. RFs were extracted from the accelerometer and reference respiratory signals using wavelet transformation. To investigate the effect of measure site, posture, and direction of acceleration on the accuracy of accelerometer-based RF estimation, repeated measures multivariate analysis of variance, linear regression, Bland-Altman analysis, and Scheirer-Ray-Hare test were performed between reference and accelerometer-based RFs.METHODSIn supine and seated postures respectively, respiratory signals were measured from 34 healthy subjects in 70 s by triaxial accelerometers located at four sites on the body wall (over the clavicle, laterally on the chest wall, over the pectoral part of the anterior chest wall, on the abdomen in the midline at the umbilicus), with the reference respiratory signal simultaneously recorded by a strain gauge chest belt. RFs were extracted from the accelerometer and reference respiratory signals using wavelet transformation. To investigate the effect of measure site, posture, and direction of acceleration on the accuracy of accelerometer-based RF estimation, repeated measures multivariate analysis of variance, linear regression, Bland-Altman analysis, and Scheirer-Ray-Hare test were performed between reference and accelerometer-based RFs.There was no significant difference in accelerometer-based RF estimation between seated and supine postures, among four accelerometer sites, or between seated or supine postures (p > 0.05 for all). The error of accelerometer-based RF estimation was less than 0.03 Hz (two breaths per minute) at any site or posture, but was significantly smaller in supine posture than in seated posture (p < 0.05), with narrower limits of agreement in Bland-Altman analysis and higher accuracy in linear regression (R 2 > 0.61 vs. R 2 < 0.51).RESULTSThere was no significant difference in accelerometer-based RF estimation between seated and supine postures, among four accelerometer sites, or between seated or supine postures (p > 0.05 for all). The error of accelerometer-based RF estimation was less than 0.03 Hz (two breaths per minute) at any site or posture, but was significantly smaller in supine posture than in seated posture (p < 0.05), with narrower limits of agreement in Bland-Altman analysis and higher accuracy in linear regression (R 2 > 0.61 vs. R 2 < 0.51).Respiration frequency can be accurately measured from the acceleration of any direction using triaxial accelerometers placed at the clavicular, pectoral and lateral sites on the chest as well the mid abdominal site. More accurate RF estimation could be achieved in supine posture compared with seated posture.CONCLUSIONRespiration frequency can be accurately measured from the acceleration of any direction using triaxial accelerometers placed at the clavicular, pectoral and lateral sites on the chest as well the mid abdominal site. More accurate RF estimation could be achieved in supine posture compared with seated posture. IntroductionRespiration frequency (RF) could be derived from the respiratory signals recorded by accelerometers which detect chest wall movements. The optimum direction of acceleration for accurate RF measurement is still uncertain. We aim to investigate the effect of measure site, posture, and direction of acceleration on the accuracy of accelerometer-based RF estimation.MethodsIn supine and seated postures respectively, respiratory signals were measured from 34 healthy subjects in 70 s by triaxial accelerometers located at four sites on the body wall (over the clavicle, laterally on the chest wall, over the pectoral part of the anterior chest wall, on the abdomen in the midline at the umbilicus), with the reference respiratory signal simultaneously recorded by a strain gauge chest belt. RFs were extracted from the accelerometer and reference respiratory signals using wavelet transformation. To investigate the effect of measure site, posture, and direction of acceleration on the accuracy of accelerometer-based RF estimation, repeated measures multivariate analysis of variance, linear regression, Bland-Altman analysis, and Scheirer-Ray-Hare test were performed between reference and accelerometer-based RFs.ResultsThere was no significant difference in accelerometer-based RF estimation between seated and supine postures, among four accelerometer sites, or between seated or supine postures (p > 0.05 for all). The error of accelerometer-based RF estimation was less than 0.03 Hz (two breaths per minute) at any site or posture, but was significantly smaller in supine posture than in seated posture (p < 0.05), with narrower limits of agreement in Bland-Altman analysis and higher accuracy in linear regression (R2 > 0.61 vs. R2 < 0.51).ConclusionRespiration frequency can be accurately measured from the acceleration of any direction using triaxial accelerometers placed at the clavicular, pectoral and lateral sites on the chest as well the mid abdominal site. More accurate RF estimation could be achieved in supine posture compared with seated posture. |
Author | Hughes, Stephen Liu, Haipeng Zheng, Dingchang |
AuthorAffiliation | 2 Faculty Research Centre for Intelligent Healthcare, Coventry University , Coventry , United Kingdom 1 Medical Devices Research Group, Anglia Ruskin University , Chelmsford , United Kingdom |
AuthorAffiliation_xml | – name: 1 Medical Devices Research Group, Anglia Ruskin University , Chelmsford , United Kingdom – name: 2 Faculty Research Centre for Intelligent Healthcare, Coventry University , Coventry , United Kingdom |
Author_xml | – sequence: 1 givenname: Stephen surname: Hughes fullname: Hughes, Stephen – sequence: 2 givenname: Haipeng surname: Liu fullname: Liu, Haipeng – sequence: 3 givenname: Dingchang surname: Zheng fullname: Zheng, Dingchang |
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CitedBy_id | crossref_primary_10_3390_s22249953 crossref_primary_10_3390_s24134139 crossref_primary_10_3390_s24062018 crossref_primary_10_1016_j_heliyon_2024_e33295 crossref_primary_10_3389_fphys_2021_738939 crossref_primary_10_3390_info14050297 crossref_primary_10_3390_app12084093 crossref_primary_10_1007_s11356_022_20055_x crossref_primary_10_3390_biomechanics4010005 crossref_primary_10_3390_s23094246 crossref_primary_10_1097_MD_0000000000038818 |
Cites_doi | 10.1093/bja/aer153 10.1088/1361-6579/ab299e 10.1136/bmjqs-2017-006671 10.1067/mem.2002.122017 10.3389/fphys.2019.00732 10.1109/EMBC.2015.7319366 10.1016/j.dib.2019.104912 10.5694/j.1326-5377.2008.tb01825.x 10.1113/ep088180 10.4108/icst.mobihealth.2014.257219 10.1145/3345615.3361130 10.1109/jbhi.2018.2867727 10.3390/app10020480 10.1088/0967-3334/34/8/N51 10.1016/j.resp.2010.01.001 10.1109/IEMBS.2011.6091301 10.1016/s0300-9572(02)00100-4 10.1111/aas.12784 10.1249/mss.0000000000001222 10.1016/j.bspc.2019.101779 10.1109/MeMeA.2017.7985870 10.1109/BSN.2010.50 |
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Copyright | Copyright © 2020 Hughes, Liu and Zheng. Copyright © 2020 Hughes, Liu and Zheng. 2020 Hughes, Liu and Zheng |
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Keywords | respiration frequency (RF) chest wall respiration rate sensor placement posture accelerometer |
Language | English |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Massimo–Pagani, University of Milan, Italy Reviewed by: Guanghao Sun, The University of Electro-Communications, Japan; Nizam Uddin Ahamed, University of Pittsburgh, United States ORCID: Haipeng Liu, orcid.org/0000-0002-4212-2503 This article was submitted to Computational Physiology and Medicine, a section of the journal Frontiers in Physiology |
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References | (B20) 2018 Lin (B16) 2020; 57 Costa (B5) 2014 Granholm (B9) 2016; 60 Cretikos (B6) 2008; 188 Preejith (B19) 2017 Schneller (B22) 2017; 49 Badawy (B3) 2017; 26 Liu (B17) 2019; 40 Vehkaoja (B25) 2015 Röddiger (B21) 2019 Lee (B15) 2010; 170 Aguilera-Castells (B1) 2020; 28 Bates (B4) 2010 Hodgetts (B12) 2002; 54 Siqueira (B23) 2019; 23 Sun (B24) 2015 Kwon (B14) 2011 Edmonds (B8) 2002; 39 Hartmann (B10) 2019; 10 Hernandez (B11) 2014 Pitts (B18) 2013; 34 Al-Halhouli (B2) 2020; 10 Drummond (B7) 2011; 107 Jacunski (B13) 2020; 105 |
References_xml | – volume: 107 start-page: 462 year: 2011 ident: B7 article-title: Validation of a new non-invasive automatic monitor of respiratory rate for postoperative subjects. publication-title: Br. J. Anaesth. doi: 10.1093/bja/aer153 – volume: 40 year: 2019 ident: B17 article-title: Recent development of respiratory rate measurement technologies. publication-title: Physiol. Meas. doi: 10.1088/1361-6579/ab299e – volume: 26 start-page: 832 year: 2017 ident: B3 article-title: Is everyone really breathing 20 times a minute? Assessing epidemiology and variation in recorded respiratory rate in hospitalised adults. publication-title: BMJ Q. Saf. doi: 10.1136/bmjqs-2017-006671 – year: 2014 ident: B5 article-title: A simple movement classification system for smartphones with accelerometer publication-title: New Perspectives in Information Systems and Technologies – volume: 39 start-page: 233 year: 2002 ident: B8 article-title: The reliability of vital sign measurements. publication-title: Ann. Emerg. Med. doi: 10.1067/mem.2002.122017 – volume: 10 year: 2019 ident: B10 article-title: Toward accurate extraction of respiratory frequency from the photoplethysmogram: effect of measurement site. publication-title: Front. Phys. doi: 10.3389/fphys.2019.00732 – year: 2015 ident: B25 article-title: Effects of sensor type and sensor location on signal quality in bed mounted ballistocardiographic heart rate and respiration monitoring publication-title: . doi: 10.1109/EMBC.2015.7319366 – volume: 28 year: 2020 ident: B1 article-title: Correlational data concerning body centre of mass acceleration, muscle activity, and forces exerted during a suspended lunge under different stability conditions in high-standard track and field athletes. publication-title: Data Brief. doi: 10.1016/j.dib.2019.104912 – year: 2018 ident: B20 publication-title: R: A Language and Environment for Statistical Computing. – volume: 188 start-page: 657 year: 2008 ident: B6 article-title: Respiratory rate: the neglected vital sign. publication-title: Med. J. Aust. doi: 10.5694/j.1326-5377.2008.tb01825.x – volume: 105 start-page: 842 year: 2020 ident: B13 article-title: The effects of hypoxia and fatigue on skeletal muscle electromechanical delay. publication-title: Exp. Physiol. doi: 10.1113/ep088180 – year: 2014 ident: B11 article-title: BioGlass: physiological parameter estimation using a head-mounted wearable device publication-title: Proceedings of the 2014 4th International Conference on Wireless Mobile Communication and Healthcare - Transforming Healthcare Through Innovations in Mobile and Wireless Technologies (MOBIHEALTH). doi: 10.4108/icst.mobihealth.2014.257219 – start-page: 48 year: 2019 ident: B21 article-title: Towards Respiration Rate Monitoring Using an In-Ear Headphone Inertial Measurement Unit publication-title: Proceedings of the 1st International Workshop on Earable Computing doi: 10.1145/3345615.3361130 – volume: 23 start-page: 1507 year: 2019 ident: B23 article-title: Respiratory waveform estimation from multiple accelerometers: an optimal sensor number and placement analysis. publication-title: IEEE J. Biomed. Health Inform. doi: 10.1109/jbhi.2018.2867727 – volume: 10 year: 2020 ident: B2 article-title: Clinical evaluation of stretchable and wearable inkjet-printed strain gauge sensor for respiratory rate monitoring at different body postures. publication-title: Appl. Sci. doi: 10.3390/app10020480 – volume: 34 start-page: N51 year: 2013 ident: B18 article-title: A respiratory monitoring device based on clavicular motion. publication-title: Physiol. Meas. doi: 10.1088/0967-3334/34/8/N51 – volume: 170 start-page: 236 year: 2010 ident: B15 article-title: Changes in sitting posture induce multiplanar changes in chest wall shape and motion with breathing. publication-title: Respir. Physiol. Neurobiol. doi: 10.1016/j.resp.2010.01.001 – year: 2015 ident: B24 article-title: Rapid and stable measurement of respiratory rate from Doppler radar signals using time domain autocorrelation model publication-title: Proceedings of the 2015 37th Annual Int Conf of the IEEE Engineering in Medicine and Biology Society – year: 2011 ident: B14 article-title: Validation of heart rate extraction through an iPhone accelerometer publication-title: Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society doi: 10.1109/IEMBS.2011.6091301 – volume: 54 start-page: 125 year: 2002 ident: B12 article-title: The identification of risk factors for cardiac arrest and formulation of activation criteria to alert a medical emergency team. publication-title: Resuscitation doi: 10.1016/s0300-9572(02)00100-4 – volume: 60 start-page: 1444 year: 2016 ident: B9 article-title: Respiratory rates measured by a standardised clinical approach, ward staff, and a wireless device. publication-title: Acta Anaesthesiol. Scand. doi: 10.1111/aas.12784 – volume: 49 start-page: 1261 year: 2017 ident: B22 article-title: Measuring children’s physical activity: compliance using skin-taped accelerometers. publication-title: Med. Sci. Sports Exerc. doi: 10.1249/mss.0000000000001222 – volume: 57 year: 2020 ident: B16 article-title: Estimation of heart rate and respiratory rate from the seismocardiogram under resting state. publication-title: Biomed. Signal Process. Control doi: 10.1016/j.bspc.2019.101779 – year: 2017 ident: B19 article-title: Accelerometer based system for continuous respiratory rate monitoring publication-title: Proceedings of the 2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) IEEE doi: 10.1109/MeMeA.2017.7985870 – year: 2010 ident: B4 article-title: Respiratory rate and flow waveform estimation from tri-axial accelerometer data publication-title: Proceedings of the 2010 International Conference on Body Sensor Networks. doi: 10.1109/BSN.2010.50 |
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Snippet | Respiration frequency (RF) could be derived from the respiratory signals recorded by accelerometers which detect chest wall movements. The optimum direction of... IntroductionRespiration frequency (RF) could be derived from the respiratory signals recorded by accelerometers which detect chest wall movements. The optimum... |
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SubjectTerms | accelerometer chest wall Physiology posture respiration frequency (RF) respiration rate sensor placement |
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Title | Influences of Sensor Placement Site and Subject Posture on Measurement of Respiratory Frequency Using Triaxial Accelerometers |
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