Noninvasive Characterization of Vascular Tone by Model-Based System Identification in Healthy and Heart Failure Patients

Hypertensive heart disease: risk factors, complications and mechanisms

Hypertensive heart disease constitutes functional and structural dysfunction and pathogenesis occurring primarily in the left ventricle, the left atrium and the coronary arteries due to chronic uncontrolled hypertension. Hypertensive heart disease is underreported and the mechanisms underlying its correlates and complications are not well elaborated. In this review, we summarize the current understanding of hypertensive heart disease, we discuss in detail the mechanisms associated with development and complications of hypertensive heart disease especially left ventricular hypertrophy, atrial fibrillation, heart failure and coronary artery disease. We also briefly highlight the role of dietary salt, immunity and genetic predisposition in hypertensive heart disease pathogenesis.

Cuff-less and continuous blood pressure measurement based on pulse transit time from carotid and toe photoplethysmograms

Blood pressure (BP) is a vital health parameter that varies throughout the day. As a single reading of high BP may not indicate hypertension, continuous monitoring of BP is usually recommended by medical doctors to confirm the diagnosis of hypertension. In the last few decades, researchers have investigated cuff-less and continuous BP measurements based on pulse transit time (PTT). The main purpose of this research is to develop an autoregressive (ARX) system identification (SI)-based PTT calculation model using two PPG signals acquired from carotid and toe. The signals were recorded from 65 subjects with an age range between 20 and 60 years. The results of the study have been validated in two stages. The first validation comprised the estimated BP from PTT using SI compared to the measured BP using the cuff-based method for all subjects. The results of the estimated BP using the proposed method compared to the measured BP obtained using the standard BP cuff measurement method are highly correlated to both systolic blood pressure (R² = 0.8132) and diastolic blood pressure (R² = 0.8357). The second validation consisted of comparing PTT values using system identification to the results of the PTT derived from the ECG-PPG method. The results showed that both methods are highly correlated (R² = 0.7808), and there is no significant difference between them (p < 0.05) with a slightly better PTT estimation related to DBP in the proposed method. Our results have proven that the PTT obtained from the carotid PPG and toe PPG using the system identification approach yielded SBP and DBP estimations that are consistent with the values of the conventional BP cuff method. The newly proposed method has the advantage of being cuff-less and able to provide continuous BP measurements.

Characterization of the vascular system using overnight wearable-based pulse arrival time and ambulatory blood pressure: A pilot study

Pulse arrival time (PAT) has been broadly investigated for its potential for cuffless blood pressure (BP) estimation and ease of measurement by wearable devices. It is also of great significance to explore whether PAT conveys complementary information to BP for vascular health assessment. In this paper, the differences between the 24-h ambulatory BP and wearable-based PAT were compared among 12 young normotensives and 15 elderly hypertensives in terms of the mean and coefficients of variation (CoVs). The correlations of the nocturnal normalized PAT (n-PAT) and BP with two arterial stiffness-related parameters (i.e., the intrinsic elastic modulus E₀ and the vascular modulation factor α) estimated by a proposed model-based method were also compared. The results showed that the inter-subject variances of the nocturnal average n-PAT were significantly different between the hypertensives and the normotensives (P < 0.001), and the intra-subject CoVs of the nocturnal n-PAT were also significantly different between the two groups (P < 0.05). However, these findings were not shown in the nocturnal BP. The correlation coefficient between the nocturnal average n-PAT and ln(E₀) is larger than that with the nocturnal BP, i.e., 0.91 vs. 0.56. Furthermore, the result also revealed that all the hypertensives receiving antihypertensive medications did not achieve the optimal control of the nocturnal BP while presented diverse arterial stiffness indicated by the nocturnal average n-PAT and ln(E₀). It is concluded that wearable-based PAT contains complementary information about the vascular system to the ambulatory BP, which may be useful for designing effective antihypertensive treatments.

Big data for health

This paper provides an overview of recent developments in big data in the context of biomedical and health informatics. It outlines the key characteristics of big data and how medical and health informatics, translational bioinformatics, sensor informatics, and imaging informatics will benefit from an integrated approach of piecing together different aspects of personalized information from a diverse range of data sources, both structured and unstructured, covering genomics, proteomics, metabolomics, as well as imaging, clinical diagnosis, and long-term continuous physiological sensing of an individual. It is expected that recent advances in big data will expand our knowledge for testing new hypotheses about disease management from diagnosis to prevention to personalized treatment. The rise of big data, however, also raises challenges in terms of privacy, security, data ownership, data stewardship, and governance. This paper discusses some of the existing activities and future opportunities related to big data for health, outlining some of the key underlying issues that need to be tackled.