Atrial Fibrillation Detection Using a Novel Cardiac Ambulatory Monitor Based on Photo‐Plethysmography at the Wrist
Background Long‐term continuous cardiac monitoring would aid in the early diagnosis and management of atrial fibrillation (AF). This study examined the accuracy of a novel approach for AF detection using photo‐plethysmography signals measured from a wrist‐based wearable device. Methods and Results E...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-08-01
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| Series: | Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease |
| Subjects: | |
| Online Access: | https://www.ahajournals.org/doi/10.1161/JAHA.118.009351 |
| _version_ | 1818398610785566720 |
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| author | Alberto G. Bonomi Fons Schipper Linda M. Eerikäinen Jenny Margarito Ralph van Dinther Guido Muesch Helma M. de Morree Ronald M. Aarts Saeed Babaeizadeh David D. McManus Lukas R.C. Dekker |
| author_facet | Alberto G. Bonomi Fons Schipper Linda M. Eerikäinen Jenny Margarito Ralph van Dinther Guido Muesch Helma M. de Morree Ronald M. Aarts Saeed Babaeizadeh David D. McManus Lukas R.C. Dekker |
| author_sort | Alberto G. Bonomi |
| collection | DOAJ |
| description | Background Long‐term continuous cardiac monitoring would aid in the early diagnosis and management of atrial fibrillation (AF). This study examined the accuracy of a novel approach for AF detection using photo‐plethysmography signals measured from a wrist‐based wearable device. Methods and Results ECG and contemporaneous pulse data were collected from 2 cohorts of AF patients: AF patients (n=20) undergoing electrical cardioversion (ECV) and AF patients (n=40) that were prescribed for 24 hours ECG Holter in outpatient settings (HOL). Photo‐plethysmography and acceleration data were collected at the wrist and processed to determine the inter‐pulse interval and discard inter‐pulse intervals in presence of motion artifacts. A Markov model was deployed to assess the probability of AF given irregular pattern in inter‐pulse interval sequences. The AF detection algorithm was evaluated against clinical rhythm annotations of AF based on ECG interpretation. Photo‐plethysmography recordings from apparently healthy volunteers (n=120) were used to establish the false positive AF detection rate of the algorithm. A total of 42 and 855 hours (AF: 21 and 323 hours) of photo‐plethysmography data were recorded in the ECV and HOL cohorts, respectively. AF was detected with >96% accuracy (ECV, sensitivity=97%; HOL, sensitivity=93%; both with specificity=100%). Because of motion artifacts, the algorithm did not provide AF classification for 44±16% of the monitoring period in the HOL group. In healthy controls, the algorithm demonstrated a <0.2% false positive AF detection rate. Conclusions A novel AF detection algorithm using pulse data from a wrist‐wearable device can accurately discriminate rhythm irregularities caused by AF from normal rhythm. |
| first_indexed | 2024-12-14T07:07:32Z |
| format | Article |
| id | doaj.art-50dadd5d80a148869609dbf55b73ad7a |
| institution | Directory Open Access Journal |
| issn | 2047-9980 |
| language | English |
| last_indexed | 2024-12-14T07:07:32Z |
| publishDate | 2018-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease |
| spelling | doaj.art-50dadd5d80a148869609dbf55b73ad7a2022-12-21T23:12:06ZengWileyJournal of the American Heart Association: Cardiovascular and Cerebrovascular Disease2047-99802018-08-0171510.1161/JAHA.118.009351Atrial Fibrillation Detection Using a Novel Cardiac Ambulatory Monitor Based on Photo‐Plethysmography at the WristAlberto G. Bonomi0Fons Schipper1Linda M. Eerikäinen2Jenny Margarito3Ralph van Dinther4Guido Muesch5Helma M. de Morree6Ronald M. Aarts7Saeed Babaeizadeh8David D. McManus9Lukas R.C. Dekker10Philips Research Eindhoven The NetherlandsPhilips Healthcare Andover MAPhilips Research Eindhoven The NetherlandsPhilips Research Eindhoven The NetherlandsPhilips Research Eindhoven The NetherlandsPhilips Research Eindhoven The NetherlandsPhilips Research Eindhoven The NetherlandsPhilips Research Eindhoven The NetherlandsPhilips Healthcare Andover MACardiology Division Department of Medicine University of Massachusetts Medical School Worcester MADepartment of Electrical Engineering Eindhoven University of Technology Eindhoven The NetherlandsBackground Long‐term continuous cardiac monitoring would aid in the early diagnosis and management of atrial fibrillation (AF). This study examined the accuracy of a novel approach for AF detection using photo‐plethysmography signals measured from a wrist‐based wearable device. Methods and Results ECG and contemporaneous pulse data were collected from 2 cohorts of AF patients: AF patients (n=20) undergoing electrical cardioversion (ECV) and AF patients (n=40) that were prescribed for 24 hours ECG Holter in outpatient settings (HOL). Photo‐plethysmography and acceleration data were collected at the wrist and processed to determine the inter‐pulse interval and discard inter‐pulse intervals in presence of motion artifacts. A Markov model was deployed to assess the probability of AF given irregular pattern in inter‐pulse interval sequences. The AF detection algorithm was evaluated against clinical rhythm annotations of AF based on ECG interpretation. Photo‐plethysmography recordings from apparently healthy volunteers (n=120) were used to establish the false positive AF detection rate of the algorithm. A total of 42 and 855 hours (AF: 21 and 323 hours) of photo‐plethysmography data were recorded in the ECV and HOL cohorts, respectively. AF was detected with >96% accuracy (ECV, sensitivity=97%; HOL, sensitivity=93%; both with specificity=100%). Because of motion artifacts, the algorithm did not provide AF classification for 44±16% of the monitoring period in the HOL group. In healthy controls, the algorithm demonstrated a <0.2% false positive AF detection rate. Conclusions A novel AF detection algorithm using pulse data from a wrist‐wearable device can accurately discriminate rhythm irregularities caused by AF from normal rhythm.https://www.ahajournals.org/doi/10.1161/JAHA.118.009351arrhythmia (heart rhythm disorders)cardioversionscreeningself‐management |
| spellingShingle | Alberto G. Bonomi Fons Schipper Linda M. Eerikäinen Jenny Margarito Ralph van Dinther Guido Muesch Helma M. de Morree Ronald M. Aarts Saeed Babaeizadeh David D. McManus Lukas R.C. Dekker Atrial Fibrillation Detection Using a Novel Cardiac Ambulatory Monitor Based on Photo‐Plethysmography at the Wrist Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease arrhythmia (heart rhythm disorders) cardioversion screening self‐management |
| title | Atrial Fibrillation Detection Using a Novel Cardiac Ambulatory Monitor Based on Photo‐Plethysmography at the Wrist |
| title_full | Atrial Fibrillation Detection Using a Novel Cardiac Ambulatory Monitor Based on Photo‐Plethysmography at the Wrist |
| title_fullStr | Atrial Fibrillation Detection Using a Novel Cardiac Ambulatory Monitor Based on Photo‐Plethysmography at the Wrist |
| title_full_unstemmed | Atrial Fibrillation Detection Using a Novel Cardiac Ambulatory Monitor Based on Photo‐Plethysmography at the Wrist |
| title_short | Atrial Fibrillation Detection Using a Novel Cardiac Ambulatory Monitor Based on Photo‐Plethysmography at the Wrist |
| title_sort | atrial fibrillation detection using a novel cardiac ambulatory monitor based on photo plethysmography at the wrist |
| topic | arrhythmia (heart rhythm disorders) cardioversion screening self‐management |
| url | https://www.ahajournals.org/doi/10.1161/JAHA.118.009351 |
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