Diagnostic performance of a wearing dynamic ECG recorder for atrial fibrillation screening: the HUAMI heart study.

BACKGROUND: Atrial fibrillation (AF) is the most prevalent cardiac dysrhythmia with high morbidity and mortality rate. Evidence shows that in every three patients with AF, one is asymptomatic. The asymptomatic and paroxysmal nature of AF is the reason for unsatisfactory and delayed detection using traditional instruments. Research indicates that wearing a dynamic electrocardiogram (ECG) recorder can guide accurate and safe analysis, interpretation, and distinction of AF from normal sinus rhythm. This is also achievable in an upright position and after exercises, assisted by an artificial intelligence (AI) algorithm. METHODS: This study enrolled 114 participants from the outpatient registry of our institution from June 24, 2020 to July 24, 2020. Participants were tested with a wearable dynamic ECG recorder and 12-lead ECG in a supine, an upright position and after exercises for 60 s. RESULTS: Of the 114 subjects enrolled in the study, 61 had normal sinus rhythm and 53 had AF. The number of cases that could not be determined by the wristband of dynamic ECG recorder was two, one and one respectively. Case results that were not clinically objective were defined as false-negative or false-positive. Results for diagnostic accuracy, sensitivity, and specificity tested by wearable dynamic ECG recorders in a supine position were 94.74% (95% CI% 88.76-97.80%), 88.68% (95% CI 77.06-95.07%), and 100% (95% CI 92.91-100%), respectively. Meanwhile, the diagnostic accuracy, sensitivity and specificity in an upright position were 97.37% (95% CI 92.21-99.44%), 94.34% (95% CI 84.03-98.65%), and 100% (95% CI 92.91-100%), respectively. Similar results as those of the upright position were obtained after exercise. CONCLUSION: The widely accessible wearable dynamic ECG recorder integrated with an AI algorithm can efficiently detect AF in different postures and after exercises. As such, this tool holds great promise as a useful and user-friendly screening method for timely AF diagnosis in at-risk individuals.

Home use of a compact, 12­lead ECG recording system for newborns.

BACKGROUND: An easy-to-operate ECG recorder should be useful for newborn screening for heart conditions, by health care workers - or parents. We developed a one-piece electrode strip and a compact, 12­lead ECG recorder for newborns. METHOD: We enrolled 2582 newborns in a trial to assess abilities of parents to record a 12­lead ECG on their infants (2-4 weeks-old). Newborns were randomized to recordings by parents (1290) or our staff (1292 controls). Educational backgrounds of parents varied, including 64% with no more than a high school diploma. RESULTS: For newborns randomized to parent recorded ECGs, 94% of parents completed a 10-minute recording. However, 42.6% asked for verbal help, and 12.7% needed physical help. ECG quality was the same for recordings by parents versus staff. CONCLUSIONS: By use of a one-piece electrode strip and a compact recorder, 87% of parents recorded diagnostic quality ECGs on their newborn infants, with minimal assistance.

[Development of Automatic Diagnosis and Evaluation System for ECG Recorder].

ECG Recorder's automatic diagnosis function is uneven, it brings a lot of inconvenience to clinicians in the diagnosis and treatment. We developed the automatic diagnosis and evaluation system for ECG recorder based on data platform in General Hospital of PLA, in order to evaluate the automatic diagnosis function of ECG recorder and improve the level of automatic diagnosis, and through a large number of data evaluation results, to provides the standard basis of ECG recorder's automatic diagnosis.

72 hour Holter monitoring, 7 day Holter monitoring, and 30 day intermittent patient-activated heart rhythm recording in detecting arrhythmias in cryptogenic stroke patients free from arrhythmia in a screening 24 h Holter.

INTRODUCTION: According to recent studies, silent atrial fibrillation (AF) is a common cause of cryptogenic ischemic stroke (CIS). 12-lead electrocardiogram (ECG) and 24 h Holter are not efficient to reveal an occult arrhythmic cause of stroke. OBJECTIVES: The aim of the study was to evaluate 72 h Holter, 7 day Holter monitoring, and intermittent single-lead ECG recording in patients with CIS to identify cases with the arrhythmic cause of stroke in patients with CIS in whom 24 h ECG Holter was free from arrhythmia. METHODS: 72 patients (aged 60 ± 9 years, 44 males) with CIS and no arrhythmic findings in 24 h Holter were enrolled. All patients had 7 day Holter monitoring and received handheld ECG recorder (CheckMe, Viatom) for ambulatory 30 ± 3 days ECG recording. AF, supraventricular tachycardia (SVT runs of ≥5 QRS), and other arrhythmias were assessed in the first 72 h of Holter recording, in 7 day-recording, and in handheld ECG strips. RESULTS: 72 h-recording revealed AF in four cases (5.6%) and SVT in 18 (25%) cases. 7 day Holter confirmed AF in seven patients (10%) and SVT in 27 patients (37.5%). There was no difference in regards to CHADS2VASc score between patients with SVT and non-arrhythmic group (3.6 ± 1.1 vs 3.4 ± 1.6; p = NS). Symptoms did not correlate with findings. Patient-activated handheld ECG recorders were used with good compliance. The mean number of recordings was 49 ± 30. Except for PACs, there was only one case of AF documented in 3,531 strips. CONCLUSIONS: 7 day Holter performs better than 72 h and reveals supraventricular arrhythmias in every third and AF in 10% of CIS patients who were free from arrhythmia in 24 h ECG monitoring. 30 day intermittent ECG monitor does not yield diagnostic value in CIS.

Automatic Real-Time Embedded QRS Complex Detection for a Novel Patch-Type Electrocardiogram Recorder.

Cardiovascular diseases are projected to remain the single leading cause of death globally. Timely diagnosis and treatment of these diseases are crucial to prevent death and dangerous complications. One of the important tools in early diagnosis of arrhythmias is analysis of electrocardiograms (ECGs) obtained from ambulatory long-term recordings. The design of novel patch-type ECG recorders has increased the accessibility of these long-term recordings. In many applications, it is furthermore an advantage for these devices that the recorded ECGs can be analyzed automatically in real time. The purpose of this study was therefore to design a novel algorithm for automatic heart beat detection, and embed the algorithm in the CE marked ePatch heart monitor. The algorithm is based on a novel cascade of computationally efficient filters, optimized adaptive thresholding, and a refined search back mechanism. The design and optimization of the algorithm was performed on two different databases: The MIT-BIH arrhythmia database ([Formula: see text]%, [Formula: see text]) and a private ePatch training database ([Formula: see text]%, [Formula: see text]%). The offline validation was conducted on the European ST-T database ([Formula: see text]%, [Formula: see text]%). Finally, a double-blinded validation of the embedded algorithm was conducted on a private ePatch validation database ([Formula: see text]%, [Formula: see text]%). The algorithm was thus validated with high clinical performance on more than 300 ECG records from 189 different subjects with a high number of different abnormal beat morphologies. This demonstrates the strengths of the algorithm, and the potential for this embedded algorithm to improve the possibilities of early diagnosis and treatment of cardiovascular diseases.