Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device
Wearable physiological monitors are becoming increasingly commonplace in the consumer domain, but in literature there exists no substantive studies of their performance when measuring the physiology of ambulatory patients. In this Letter, the authors investigate the reliability of the heart-rate (HR...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
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Institution of Engineering and Technology
2017
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| _version_ | 1826267277928955904 |
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| author | Morelli, D Bartoloni, L Colombo, M Plans, D Clifton, D |
| author_facet | Morelli, D Bartoloni, L Colombo, M Plans, D Clifton, D |
| author_sort | Morelli, D |
| collection | OXFORD |
| description | Wearable physiological monitors are becoming increasingly commonplace in the consumer domain, but in literature there exists no substantive studies of their performance when measuring the physiology of ambulatory patients. In this Letter, the authors investigate the reliability of the heart-rate (HR) sensor in an exemplar 'wearable' wrist-worn monitoring system (the Microsoft Band 2); their experiments quantify the propagation of error from (i) the photoplethysmogram (PPG) acquired by pulse oximetry, to (ii) estimation of HR, and (iii) subsequent calculation of HR variability (HRV) features. Their experiments confirm that motion artefacts account for the majority of this error, and show that the unreliable portions of HR data can be removed, using the accelerometer sensor from the wearable device. The experiments further show that acquired signals contain noise with substantial energy in the high-frequency band, and that this contributes to subsequent variability in standard HRV features often used in clinical practice. The authors finally show that the conventional use of long-duration windows of data is not needed to perform accurate estimation of time-domain HRV features. |
| first_indexed | 2024-03-06T20:51:43Z |
| format | Journal article |
| id | oxford-uuid:37cdef1b-26db-465e-92f8-a93f72ebaa11 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T20:51:43Z |
| publishDate | 2017 |
| publisher | Institution of Engineering and Technology |
| record_format | dspace |
| spelling | oxford-uuid:37cdef1b-26db-465e-92f8-a93f72ebaa112022-03-26T13:46:16ZProfiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring deviceJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:37cdef1b-26db-465e-92f8-a93f72ebaa11EnglishSymplectic Elements at OxfordInstitution of Engineering and Technology2017Morelli, DBartoloni, LColombo, MPlans, DClifton, DWearable physiological monitors are becoming increasingly commonplace in the consumer domain, but in literature there exists no substantive studies of their performance when measuring the physiology of ambulatory patients. In this Letter, the authors investigate the reliability of the heart-rate (HR) sensor in an exemplar 'wearable' wrist-worn monitoring system (the Microsoft Band 2); their experiments quantify the propagation of error from (i) the photoplethysmogram (PPG) acquired by pulse oximetry, to (ii) estimation of HR, and (iii) subsequent calculation of HR variability (HRV) features. Their experiments confirm that motion artefacts account for the majority of this error, and show that the unreliable portions of HR data can be removed, using the accelerometer sensor from the wearable device. The experiments further show that acquired signals contain noise with substantial energy in the high-frequency band, and that this contributes to subsequent variability in standard HRV features often used in clinical practice. The authors finally show that the conventional use of long-duration windows of data is not needed to perform accurate estimation of time-domain HRV features. |
| spellingShingle | Morelli, D Bartoloni, L Colombo, M Plans, D Clifton, D Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device |
| title | Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device |
| title_full | Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device |
| title_fullStr | Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device |
| title_full_unstemmed | Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device |
| title_short | Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device |
| title_sort | profiling the propagation of error from ppg to hrv features in a wearable physiological monitoring device |
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