Key result
An SCG-based AF-detection algorithm was able to distinguish atrial fibrillation from sinus rhythm with high accuracy.
Why the study?
Does an SCG-based AF-detection algorithm accurately detect atrial fibrillation in telemonitoring applications?
Observational (n=12)
Does an SCG-based AF-detection algorithm accurately detect atrial fibrillation in telemonitoring applications?
An SCG-based algorithm using a MEMS accelerometer can accurately detect atrial fibrillation, demonstrating potential utility for telemonitoring applications.
May support SCG telemonitoring exploration; leaves open prospective validation before clinical use.
The aim of the study was to assess the applicability of seismocardiogram (SCG) for the detection of atrial fibrillation (AF) in telemonitoring applications. SCG data used in this study consists of simultaneous SCG and ECG recordings of 12 patients during both AF and sinus rhythm (after cardioversion). An SCG-based AF-detection algorithm was developed and its performance tested with the acquired clinical data. The algorithm is able to distinguish AF positive samples from samples with sinus rhythm with high accuracy.
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Koivisto et al. (2015) conducted an observational in Atrial fibrillation (n=12). Seismocardiogram (SCG)-based AF-detection algorithm vs. ECG (gold standard) was evaluated on Detection of atrial fibrillation (distinguishing AF from sinus rhythm). An SCG-based AF-detection algorithm was able to distinguish atrial fibrillation from sinus rhythm with high accuracy.
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