A Hidden Markov Model for Seismocardiography Wahlstrom, Johan; Skog, Isaac; Handel, Peter ...
IEEE transactions on biomedical engineering,
10/2017, Letnik:
64, Številka:
10
Journal Article
Recenzirano
We propose a hidden Markov model approach for processing seismocardiograms. The seismocardiogram morphology is learned using the expectation-maximization algorithm, and the state of the heart at a ...given time instant is estimated by the Viterbi algorithm. From the obtained Viterbi sequence, it is then straightforward to estimate instantaneous heart rate, heart rate variability measures, and cardiac time intervals (the latter requiring a small number of manual annotations). As is shown in the conducted experimental study, the presented algorithm outperforms the state-of-the-art in seismocardiogram-based heart rate and heart rate variability estimation. Moreover, the isovolumic contraction time and the left ventricular ejection time are estimated with mean absolute errors of about 5 ms and 9 ms, respectively. The proposed algorithm can be applied to any set of inertial sensors; does not require access to any additional sensor modalities; does not make any assumptions on the seismocardiogram morphology; and explicitly models sensor noise and beat-to-beat variations (both in amplitude and temporal scaling) in the seismocardiogram morphology. As such, it is well suited for low-cost implementations using off-the-shelf inertial sensors and targeting, e.g., at-home medical services.
Obstructive sleep apnea is a sleep-related breathing disorder that has a major impact on cardiovascular function. It has been associated with hypertension, coronary artery disease, cardiac ...arrhythmias, sudden cardiac death, and heart failure. This review focuses on the relationship between obstructive sleep apnea and heart failure with either reduced or preserved ejection fraction. We discuss the pathophysiology of obstructive sleep apnea, as well as its prevalence, treatment outcomes with continuous positive airway pressure, and prognosis in these 2 distinct types of heart failure. We also identify areas in which further work is needed to improve our understanding of this association in heart failure patients.
Heart rate (HR) variability has been extensively studied in patients surviving an acute myocardial infarction (AMI). The majority of studies have shown that patients with reduced or abnormal HR ...variability/turbulence have an increased risk of mortality within few years after an AMI. Various measures of HR dynamics, such as time-domain, spectral, and non-linear measures of HR variability, as well as HR turbulence, have been used in risk stratification of post-AMI patients. The prognostic power of various measures, except of those reflecting rapid R-R interval oscillations, has been almost identical, albeit some non-linear HR variability measures, such as short-term fractal scaling exponent, and HR turbulence, have provided somewhat better prognostic information than the others. Abnormal HR variability predicts both sudden and non-sudden cardiac death after AMI. Because of remodeling of the arrhythmia substrate after AMI, early measurement of HR variability to identify those at high risk should likely be repeated later in order to assess the risk of fatal arrhythmia events. Future randomized trials using HR variability/turbulence as one of the pre-defined inclusion criteria will show whether routine measurement of HR variability/turbulence will become a routine clinical tool for risk stratification of post-AMI patients.
Abstract Objectives This study sought to determine whether Holter-based parameters of heart rate variability (HRV) are independently associated with incident heart failure among older adults in the ...CHS (Cardiovascular Health Study) as evidenced by an improvement in the predictive power of the Health Aging and Body Composition Heart Failure (Health ABC) score. Background Abnormal HRV, a marker of autonomic dysfunction, has been associated with multiple adverse cardiovascular outcomes but not the development of congestive heart failure (CHF). Methods Asymptomatic CHS participants with interpretable 24-h baseline Holter recordings were included (n = 1,401). HRV measures and premature ventricular contraction (PVC) counts were compared between participants with (n = 260) and without (n = 1,141) incident CHF on follow-up. Significantly different parameters between groups were added to the components of the Health ABC score, a validated CHF prediction tool, using stepwise Cox regression. Results The final model included components of the Health ABC score, In PVC counts (adjusted hazard ratio aHR: 1.12; 95% confidence interval CI: 1.07 to 1.19; p < 0.001) and the following HRV measures: abnormal heart rate turbulence onset (aHR: 1.52; 95% CI: 1.11 to 2.08; p = 0.009), short-term fractal scaling exponent (aHR: 0.27; 95% CI: 0.14 to 0.53; p < 0.001), in very low frequency power (aHR: 1.28; 95% CI: 1.02 to 1.60; p = 0.037), and coefficient of variance of N-N intervals (aHR: 0.94; 95% CI: 0.90 to 0.99; p = 0.009). The C-statistic for the final model was significantly improved over the Health ABC model alone (0.77 vs. 0.73; p = 0.0002). Conclusions Abnormal HRV parameters were significantly and independently associated with incident CHF in asymptomatic, older adults. When combined with increased PVCs, HRV improved the predictive power of the Health ABC score.
Atrial fibrillation (AF) prediction models have unclear clinical utility given the absence of AF prevention therapies and the immutability of many risk factors. Premature atrial contractions (PACs) ...play a critical role in AF pathogenesis and may be modifiable.
To investigate whether PAC count improves model performance for AF risk.
Prospective cohort study.
4 U.S. communities.
A random subset of 1260 adults without prevalent AF enrolled in the Cardiovascular Health Study between 1989 and 1990.
The PAC count was quantified by 24-hour electrocardiography. Participants were followed for the diagnosis of incident AF or death. The Framingham AF risk algorithm was used as the comparator prediction model.
In adjusted analyses, doubling the hourly PAC count was associated with a significant increase in AF risk (hazard ratio, 1.17 95% CI, 1.13 to 1.22; P < 0.001) and overall mortality (hazard ratio, 1.06 CI, 1.03 to 1.09; P < 0.001). Compared with the Framingham model, PAC count alone resulted in similar AF risk discrimination at 5 and 10 years of follow-up and superior risk discrimination at 15 years. The addition of PAC count to the Framingham model resulted in significant 10-year AF risk discrimination improvement (c-statistic, 0.65 vs. 0.72; P < 0.001), net reclassification improvement (23.2% CI, 12.8% to 33.6%; P < 0.001), and integrated discrimination improvement (5.6% CI, 4.2% to 7.0%; P < 0.001). The specificity for predicting AF at 15 years exceeded 90% for PAC counts more than 32 beats/h.
This study does not establish a causal link between PACs and AF.
The addition of PAC count to a validated AF risk algorithm provides superior AF risk discrimination and significantly improves risk reclassification. Further study is needed to determine whether PAC modification can prospectively reduce AF risk.
American Heart Association, Joseph Drown Foundation, and National Institutes of Health.
Electrocardiographic RR intervals fluctuate cyclically, modulated by ventilation, baroreflexes, and other genetic and environmental factors that are mediated through the autonomic nervous system. ...Short term electrocardiographic recordings (5 to 15 minutes), made under controlled conditions, e.g., lying supine or standing or tilted upright can elucidate physiologic, pharmacologic, or pathologic changes in autonomic nervous system function. Long‐term, usually 24‐hour recordings, can be used to assess autonomic nervous responses during normal daily activities in health, disease, and in response to therapeutic interventions, e.g., exercise or drugs. RR interval variability is useful for assessing risk of cardiovascular death or arrhythmic events, especially when combined with other tests, e.g., left ventricular ejection fraction or ventricular arrhythmias.
The autonomic nervous system (ANS) innervates pancreatic endocrine cells, muscle, and liver, all of which participate in glucose metabolism. We tested whether measures of cardiovascular ANS function ...are independently associated with incident diabetes and annual change in fasting glucose (FG) levels as well as with insulin secretion and insulin sensitivity in older adults without diabetes.
Heart rate (HR) and measures of HR variability (HRV) were derived from 24-h electrocardiographic monitoring. Blood pressure, seated and standing, was measured. Cox proportional hazards models and linear mixed models were used to analyze the associations between HRV, HR, and orthostatic hypotension (SBP >20 mmHg decline) and incident diabetes or longitudinal FG change.
The mean annual unadjusted FG change was 1 mg/dL. Higher detrended fluctuation analyses (DFA) values, averaged over 4-11 (DFA1) or 12-20 beats (DFA2)-reflecting greater versus less organization of beat-to-beat intervals-were associated with less FG increase over time (per 1-SD increment: DFA1: -0.49 mg/dL/year -0.96, -0.03; DFA2: -0.55 mg/dL/year -1.02, -0.09). In mutually adjusted analyses, higher SD of the N-N interval (SDNN) was associated with less FG increase over time (per 1-SD increment: SDNN: -0.62 mg/dL/year -1.22, -0.03). Higher values of DFA1, DFA2, and SDNN were each associated with greater insulin secretion and insulin sensitivity but not with incident diabetes. We observed no association of HR or orthostatic hypotension with diabetes or FG change.
Specific measures of cardiac autonomic function are prospectively related to FG level changes and insulin secretion and action.
Direct and indirect links between brain regions and cardiac function have been reported. We performed a systematic literature review to summarize current knowledge regarding the associations of heart ...rate variability (HRV) and brain region morphology, activity and connectivity involved in autonomic control at rest in healthy subjects. Both positive and negative correlations of cortical thickness and gray matter volumes of brain structures with HRV were observed. The strongest were found for a cluster located within the cingulate cortex. A decline in HRV, as well as cortical thickness with increasing age, especially in the orbitofrontal cortex were noted. When associations of region-specific brain activity with HRV were examined, HRV correlated most strongly with activity in the insula, cingulate cortex, frontal and prefrontal cortices, hippocampus, thalamus, striatum and amygdala. Furthermore, significant correlations, largely positive, between HRV and brain region connectivity (in the amygdala, cingulate cortex and prefrontal cortex) were observed. Notably, right-sided neural structures may be preferentially involved in heart rate and HRV control. However, the evidence for left hemispheric control of cardiac vagal function has also been reported. Our findings provide support for the premise that the brain and the heart are interconnected by both structural and functional networks and indicate complex multi-level interactions. Further studies of brain-heart associations promise to yield insights into their relationship to health and disease.
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