False negative rates are ranging between 0.003 and 0.017. Nevertheless, QRS detection performed well across all used devices with positive predictive values between 0.985 and 1.000. Over all experimental phases, insufficient quality expressed by morphSQ values below 10% was only found in 1.22% of the recorded beats using eMotion Faros 360°whereas the rate was 8.67% with Hexoskin Hx1. Evaluation metrics includes the positive predictive value, false negative rates, and F1 scores for beat detection performance.Īll used devices achieved sufficient signal quality in non-movement conditions. A modification of the Smith-Waterman algorithm has been used to assess the RR interval quality and to classify incorrect beat annotations. The QRS detection performance was evaluated with eplimited on synchronized data by comparison to ground truth annotations. Signal quality was assessed by a new local morphological quality parameter morphSQ which is defined as a weighted peak noise-to-signal ratio on percentage scale. Used test conditions included: measurements during rest, treadmill walking/running, and a cognitive 2-back task. The recording quality is expressed by the ability to accurately detect the QRS complex, the amount of noise in the data, and the quality of RR intervals.įive ECG devices (eMotion Faros 360°, Hexoskin Hx1, NeXus-10 MKII, Polar RS800 Multi and SOMNOtouch NIBP) were attached and simultaneously tested in 13 participants. The objectives of this study is the cross-model comparison of data quality at different realistic use cases (cognitive and physical tasks). ![]() Numerous wearables are used in a research context to record cardiac activity although their validity and usability has not been fully investigated.
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