Optical heart rate monitoring (OHR) with reflective wrist photoplethysmography is a technique mainly used in the wellness application domain for monitoring heart rate levels during exercise. In the absence of motion, OHR technique is also able to estimate individual beat-to-beat intervals relatively well and can therefore also be used, for example, in monitoring of cardiac arrhythmias, stress, or sleep quality through heart rate variability (HRV) analysis. HRV analysis has also potential in monitoring the recovery of patients, e.g. after a medical intervention. However, in order to detect subtle changes, the calculated HRV parameters should be sufficiently accurate and very few studies exist that asses the accuracy of OHR derived HRV in non-healthy subjects. In this paper, we present a method to estimate beat-to-beat-intervals (BBIs) from reflective wrist PPG signal and evaluated the accuracy of the proposed method in estimating BBIs in a cross-sectional study with 29 hospitalized patients (mean age 70.6 years) in 24-h recordings performed after peripheral vascular surgery or endovascular interventions. Finally, we evaluate the accuracy of more than 30 commonly used HRV parameters and find that the accuracy of certain metrics, for example SDNN and triangular index, shown in the literature to be associated with the deterioration of the status of the patients during recovery from surgical intervention, could be adequate for patient monitoring. On the other hand, the parameters more affected by the high-frequency content of the HRV and especially the LF/HF-ratio should be used with caution.
The application of ballistocardiography (BCG) for unobtrusive monitor of (beat-to-beat) heart rate in sleeping subjects has seen increased attention in recent years. While most studies are performed on healthy volunteers, some studies have included subjects with sleep-related problems. Even so, little attention has been payed to patients suffering from cardiovascular diseases. In addition, most studies are either limited to short laboratory measurements or overnight recordings of sleeping subjects.In this work, we present preliminary results on beatto-beat interval estimation of long-term (> 21 h) BCG recordings in a hospital environment. Measurements were obtained from five subjects after peripheral vascular surgery or endovascular interventions and compared to Holter recordings. The commercially available sensor Emfit QS as well an augmented version of the CLIE interval estimation algorithm were used. Using the proposed approach, an average relative beat-to-beat interval error of 3.8 % at a coverage of 61.5 % was achieved. Error and coverage were found to vary from subject to subject as well as time of day. On average, findings are comparable though inferior to results reported on insomniac subjects in a sleep laboratory environment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.