Key result
An algorithm for a-wave detection in the second derivative plethysmogram was proposed and tested on 27 records to calculate statistical heart rate variability measures.
Why the study?
Does an algorithm for a-wave detection in the second derivative plethysmogram (SDPTG) allow for heart rate variability measurement?
Does an algorithm for a-wave detection in the second derivative plethysmogram (SDPTG) allow for heart rate variability measurement?
Answers are grounded in this paper and cite their sources.
An algorithm for a-wave detection in the second derivative plethysmogram can be used to calculate statistical heart rate variability measures.
Heart-rate monitoring is a basic measure for cardiovascular functionality assessment. The electrocardiogram (ECG) and Holter monitoring devices are accurate, but their use in the field is limited. Photoplethysmography is an optical technique that has been developed for experimental use in vascular disease. Because of its non-invasive, safe, and easy-to-use properties, it is considered a promising tool that may replace some of the current traditional cardiovascular diagnostic tools. A useful algorithm for a-wave detection in the second derivative plethysmogram (SDPTG) is introduced for heart–rate monitoring. The performance of the proposed method was tested on 27 records measured at rest and after exercise. Statistical HRV measures can be calculated using the a-a interval of the SDPTG.
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Elgendi et al. (2010) studied this question. Algorithm for a-wave detection in the second derivative plethysmogram (SDPTG) was evaluated on a-wave detection for heart-rate monitoring. An algorithm for a-wave detection in the second derivative plethysmogram was proposed and tested on 27 records to calculate statistical heart rate variability measures.
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