Wrist Band Photoplethysmography Autocorrelation Analysis Enables Detection of Atrial Fibrillation Without Pulse Detection.

Atrial fibrillation is often asymptomatic and intermittent making its detection challenging. A photoplethysmography (PPG) provides a promising option for atrial fibrillation detection. However, the shapes of pulse waves vary in atrial fibrillation decreasing pulse and atrial fibrillation detection accuracy. This study evaluated ten robust photoplethysmography features for detection of atrial fibrillation. The study was a national multi-center clinical study in Finland and the data were combined from two broader research projects (NCT03721601, URL: https://clinicaltrials.gov/ct2/show/NCT03721601 and NCT03753139, URL: https://clinicaltrials.gov/ct2/show/NCT03753139). A photoplethysmography signal was recorded with a wrist band. Five pulse interval variability, four amplitude features and a novel autocorrelation-based morphology feature were calculated and evaluated independently as predictors of atrial fibrillation. A multivariate predictor model including only the most significant features was established. The models were 10-fold cross-validated. 359 patients were included in the study (atrial fibrillation n = 169, sinus rhythm n = 190). The autocorrelation univariate predictor model detected atrial fibrillation with the highest area under receiver operating characteristic curve (AUC) value of 0.982 (sensitivity 95.1%, specificity 93.7%). Autocorrelation was also the most significant individual feature (p < 0.00001) in the multivariate predictor model, detecting atrial fibrillation with AUC of 0.993 (sensitivity 96.4%, specificity 96.3%). Our results demonstrated that the autocorrelation independently detects atrial fibrillation reliably without the need of pulse detection. Combining pulse wave morphology-based features such as autocorrelation with information from pulse-interval variability it is possible to detect atrial fibrillation with high accuracy with a commercial wrist band. Photoplethysmography wrist bands accompanied with atrial fibrillation detection algorithms utilizing autocorrelation could provide a computationally very effective and reliable wearable monitoring method in screening of atrial fibrillation.

Continuous 24-h Photoplethysmogram Monitoring Enables Detection of Atrial Fibrillation.

Aim: Atrial fibrillation (AF) detection is challenging because it is often asymptomatic and paroxysmal. We evaluated continuous photoplethysmogram (PPG) for signal quality and detection of AF. Methods: PPGs were recorded using a wrist-band device in 173 patients (76 AF, 97 sinus rhythm, SR) for 24 h. Simultaneously recorded 3-lead ambulatory ECG served as control. The recordings were split into 10-, 20-, 30-, and 60-min time-frames. The sensitivity, specificity, and F1-score of AF detection were evaluated for each time-frame. AF alarms were generated to simulate continuous AF monitoring. Sensitivities, specificities, and positive predictive values (PPVs) of the alarms were evaluated. User experiences of PPG and ECG recordings were assessed. The study was registered in the Clinical Trials database (NCT03507335). Results: The quality of PPG signal was better during night-time than in daytime (67.3 ± 22.4% vs. 30.5 ± 19.4%, p < 0.001). The 30-min time-frame yielded the highest F1-score (0.9536), identifying AF correctly in 72/76 AF patients (sensitivity 94.7%), only 3/97 SR patients receiving a false AF diagnosis (specificity 96.9%). The sensitivity and PPV of the simulated AF alarms were 78.2 and 97.2% at night, and 49.3 and 97.0% during the daytime. 82% of patients were willing to use the device at home. Conclusion: PPG wrist-band provided reliable AF identification both during daytime and night-time. The PPG data's quality was better at night. The positive user experience suggests that wearable PPG devices could be feasible for continuous rhythm monitoring.

Heart rate reactivity associated to positive and negative food and non-food visual stimuli.

Using food as a stimuli is known to cause multiple psychophysiological reactions. Heart rate variability (HRV) is common tool for assessing physiological reactions in autonomic nervous system. However, the findings in HRV related to food stimuli have not been consistent. In this paper the quick changes in HRV related to positive and negative food and non-food visual stimuli are investigated. Electrocardiogram (ECG) was measured from 18 healthy females while being stimulated with the pictures. Subjects also filled Three-Factor Eating Questionnaire to determine their eating behavior. The inter-beat-interval time series and the HRV parameters were extracted from the ECG. The quick change in HRV parameters were studied by calculating the change from baseline value (10 s window before stimulus) to value after the onset of the stimulus (10 s window during stimulus). The paired t-test showed significant difference between positive and negative food pictures but not between positive and negative non-food pictures. All the HRV parameters decreased for positive food pictures while they stayed the same or increased a little for negative food pictures. The eating behavior characteristic cognitive restraint was negatively correlated with HRV parameters that describe decreasing of heart rate.

A Lunchtime Walk in Nature Enhances Restoration of Autonomic Control during Night-Time Sleep: Results from a Preliminary Study.

Walking within nature (Green Exercise) has been shown to immediately enhance mental well-being but less is known about the impact on physiology and longer lasting effects. Heart rate variability (HRV) gives an indication of autonomic control of the heart, in particular vagal activity, with reduced HRV identified as a risk factor for cardiovascular disease. Night-time HRV allows vagal activity to be assessed whilst minimizing confounding influences of physical and mental activity. The aim of this study was to investigate whether a lunchtime walk in nature increases night-time HRV. Participants (n = 13) attended on two occasions to walk a 1.8 km route through a built or a natural environment. Pace was similar between the two walks. HRV was measured during sleep using a RR interval sensor (eMotion sensor) and was assessed at 1-2 h after participants noted that they had fallen asleep. Markers for vagal activity were significantly greater after the walk in nature compared to the built walk. Lunchtime walks in nature-based environments may provide a greater restorative effect as shown by vagal activity than equivalent built walks. Nature walks may improve essential recovery during night-time sleep, potentially enhancing physiological health.

Complexity of heart rate variability in type 2 diabetes - effect of hyperglycemia.

Heart rate variability (HRV) is reduced in diabetes mellitus (DM) patients, suggesting dysfunction of cardiac autonomic regulation which has been associated with increased risk for pathological cardiac events. In this paper, we examined changes in HRV complexity in association to blood glucose level (BGL) and duration of diabetes. Resting HRV and BGL measurements of 32 healthy controls and 54 type 2 DM (T2DM) patients were analyzed. HRV complexity was assessed using Shannon entropy, sample entropy (SampEn), multiscale entropy (MSE), and multiscale Renyi entropy. HRV complexity increased with hyperglycemia indicated by increases in Shannon entropy and MSE and decreases in Renyi entropy for negative orders. Diabetes duration was strongly associated with Renyi entropy which increased for positive orders and decreased for negative orders as a function of disease duration. Shannon entropy, SampEn and MSE did not correlate with disease duration.