novel methods for arrhythmia detection: preliminary study

Conditions: Stroke; Atrial Fibrillation

Summary: 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.

Eligibility criteria:
inclusion criteria: * atrial fibrillation in 12-lead ecg exclusion criteria: * 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

Keywords: atrial fibrillation stroke atrial fibrillation screening heart rate monitoring