Stroke Clinical Trial
Official title:
Novel Methods for Arrhythmia Detection: Chest Strap ECG and Wrist Band Photoplethysmography Compared to Holter-device for Atrial Fibrillation Detection
Approximately 20-25% of strokes are of cardioembolic origin, atrial fibrillation (AF) being a
significant cause of cardioembolic strokes. AF is often symptomless and intermittent, making
its detection a clinical challenge. Currently the golden standard for diagnosis of AF is by
12-lead electrocardiogram (ECG) or any other ECG-strip.
The aim of the study is to assess the potential of chest strap as an ECG monitor, especially
in arrhythmia detection by cardiologist and algorithm.
Study design was a prospective case-control multicenter study at three sites in Finland.
Study material was collected in internal medicine emergency departments, cardiology wards and
cardiology examination units of participating hospitals, Kuopio University Hospital, Helsinki
University Central Hospital, Meilahti and North Karelia Central Hospital, Joensuu. The study
design was approved by University of Eastern Finland ethics committee (237/2017).
Study participants received a written information sheet about the study and were provided
with an opportunity to ask questions concerning the study. A written informed consent was
signed by the participants, including a permission to use patient's medical records.
Screening of study participants was made in participating hospitals from admitted patients in
May - September 2017. The inclusion criteria for study group patients was atrial fibrillation
confirmed by a doctor-interpreted 12-lead ECG, taken for medical reasons. Exclusion criteria
were: body mass index (BMI) over 33; implanted pacemaker device; 12-lead ECG findings of left
bundle branch block (LBBB) or right bundle branch block (RBBB); medical condition requiring
immediate treatment that would be delayed by the study measurements; serious infectious
disease. Control group consisted of patients with normal sinus rhythm in 12-lead ECG.
Demographics of study patients, including age, gender, previous medical history (as reported
by patient or from patient medical records), length, weight and BMI, was recorded.
First, a 12-lead ECG was taken over a period of 10 seconds for rhythm confirmation, after
which the ECG electrodes were removed. In the next step, altogether 5 wet electrodes were
attached to patient to record ECG with Faros 360 Holter device (Mega Elektroniikka, Kuopio,
Finland; device 1) to be used as golden standard for rhythm monitoring. Simultaneously a
heart rate monitoring chest strap (Suunto Movesense, Suunto, Vantaa, Finland; device 2) and
wrist band photoplethysmography (PPG) (Empatica E4, Empatica inc., Cambridge, United States)
was applied. A total of 5 min recording was made.
The data from heart rate chest strap was sent via Bluetooth connection to a mobile phone,
from which it was transferred via a cable to study computer; the data from Faros Holter
device was recorded to device´s internal memory card and transferred to analyzing software.
PPG data were transferred to MATLAB® software version R2017b for pre-processing and analysis.
The data collected was anonymized and ECG data from chest strap and Holter device was
analyzed using MATLAB software.
The quality of the ECG-strip was defined as good (no or only minor artefacts), average
(artefacts but QRS and/or P-wave identifiable) or poor (major artefacts, no identifiable QRS
and/or P-wave) by the cardiologist. The rhythm from the ECG-strips was divided to three
categories: sinus rhythm (SR), atrial fibrillation (AF) or other/inconclusive. The
cardiologists also assessed the possibility to detect P-waves from the ECG-strips with sinus
rhythm (yes/no).
The study population consisted of total 220 patients. According to the initial 12-lead ECG,
total 110 patients with atrial fibrillation were collected, and control group consisted of
110 patients with normal sinus rhythm. The initial 12-lead ECG was only used to recruitment
process of patients; later the division to sinus rhythm, atrial fibrillation or other rhythm
used in the final analysis was made according to the cardiologist-interpreted Holter ECG.
Two commonly used AF detection algorithms were used in this work. Algorithms were used to
demonstrate possibilities of automatic screening of AF using chest strap ECG devices with
automated analysis.
Holter ECG serving as golden standard a total of 218 patients were included and 2 were
excluded in the analysis. 2 of 220 3-lead Holter ECGs could be classified neither as sinus
rhythm nor atrial fibrillation. One of them converted from atrial flutter to sinus rhythm
during analysis and the quality of other ECG was insufficient for rhythm analysis. These two
Holter ECGs and the corresponding chest strap ECGs were excluded from final analysis.
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