Sara Wong

Does the level of chronic physical activity alter heart rate variability in healthy older women

In the present study, we investigated the effects of three levels of chronic physical activity on HRV (heart rate variability) in healthy older women. ECG recordings were taken in three (low-, moderate- and high-) activity groups in supine position with free and with controlled breathing, and during orthostatic stress. Temporal and spectral HRV indices were obtained from the ECG signal processing. The main results showed that, in supine position with free and controlled breathing, the HF (high-frequency) spectral component (P<0.01) and the rMSSD (square root of the mean squared differences) between two adjacent RR intervals (P<0.05 and P<0.01 respectively) were elevated in the high-activity group compared with the low-activity group. No significant difference was observed between groups during the orthostatic test. Within groups, in the supine position, the change from free to controlled breathing produced a decrease in the LF (low-frequency) spectral component in all three groups (P<0.01). The change from supine to standing position produced a decrease in RR in all three groups (P<0.05 in low- and moderate-activity groups, and P<0.01 in high-activity group); the rMSSD and the HF spectral component decreased only in the high-activity group (P<0.01). In conclusion, this study performed on older women showed that parasympathetic indices of resting HRV were significantly elevated in a high physical activity group compared with in a low physical activity group. Furthermore, parasympathetic indices of HRV decreased during an orthostatic test only in the high-activity group. The influence of chronic moderate physical activity on HRV in older women was small in the present study.

The effects of exercise training on myocardial adrenergic and muscarinic receptors

We investigated the effects of exercise training on heart rate variability (HRV) and myocardial adrenergic and muscarinic receptors in rats. Exercise training induced a decrease in body mass while ventricular size remained unchanged, a development we considered as a relative cardiac hypertrophy. In addition, there was a reduction in the density of myocardial β1-adrenergic receptors. These structural changes were associated with functional adaptations, as illustrated by the increased response of the sinus node to sympathetic blockade.

Reliability of heart rate variability in healthy older women at rest and during orthostatic testing

Background and aims: In the older population, the reliability of heart rate variability (HRV) has only been evaluated in a few studies, in the supine position, and covering a broad sample of age and patients of both sexes. To document the relevance of using HRV analysis in healthy older women, the aim of this study was to evaluate the reliability of HRV indexes during three classical tests. Methods: 33 healthy women (66.9±0.7 years old) performed two test sessions. Each session consisted of an ECG recorded in the supine position, first with free breathing (Test 1), then with controlled breathing (Test 2), and in the upright position (Test 3). Time and frequency HRV indexes were obtained by processing the ECG signals. Reliability was assessed between sessions using Student’s paired t-test, intraclass correlation coefficient (ICC) and coefficient of variation (CV). Results: There were no differences between the sessions. ICC showed good reliability for all HRV indexes. CV was low for absolute HRV indexes, except in Test 3 for parasympathetic indexes with modest CV. The CV of HRV ratio indexes were modest to high in all three tests. Conclusions: Time and absolute frequency HRV indexes are reliable when testing healthy older women. Our results support the use of such indexes in gerontology research, to assess the effects of clinical or pharmacological interventions on the autonomic nervous system.

A New On-Line Electrocardiographic Records Database and Computer Routines for Data Analysis

Gathering experimental data to test computer methods developed during a research is a hard work. Nowadays, some databases have been stored online that can be freely downloaded, however there is not a wide range of databases yet and not all pathologies are covered. Researchers with low resources are in need of more data they can consult for free. To cope with this we present an on-line portal containing a compilation of ECG databases recorded over the last two decades for research purposes. The first version of this portal contains four databases of ECG records: ischemic cardiopathy (72 patients, 3-lead ECG each), ischemic preconditioning (20 patients, 3-lead ECG each), diabetes (51 patients, 8-lead ECG each) and metabolic syndrome (25 subjects, 12-lead ECG each). In addition, one computer program and three routines are provided in order to correctly read the signals, and two digital filters along with two ECG waves detectors are provided for further processing. This portal will be constantly growing, other ECG databases and signal processing software will be uploaded. With this project, we give the scientific community a resource to avoid hours of data collection and to develop free software.

Stress ECG and Laboratory Database for the Assessment of Diabetic Cardiovascular Autonomic Neuropathy

Development of a diabetic patient database in order to study cardiovascular autonomic neuropathy (CAN) using as a primary source, stress ECG is presented. The selected platform (ecgML) allows user-friendly environment to analyze and interpret graphs, signals and data. It also allows the ability to perform annotations and reports done by users from different fields. In order to feed the database, the input data is codify using MatLab. The database is composed by two populations: 1) Type 2 Diabetes mellitus group and 2) a control group with no medical history of cardiovascular disease. At the present, there are 62 records available from these two groups. The database also contains laboratory parameters, concurrent medical diagnoses reports verified by cardiologists and other clinicians, automatic annotations for each beat and trend series from parameters extracted from the ECG signals such as RR intervals and ST segment measurements. All this information will become very useful for CAN investigations.

Multiple factor analysis as a tool for studying the effect of physical training on the autonomic nervous system

Sports activity may modify cardio-vascular regulation through the Autonomic Nervous System, the results of the studies previously performed in athletes depend on the type of HRV analysis is subjected to, the populations studied and the physical training period The drawback of these studies comes from an analysis parameter by parameter whereas the problem is inherently multifactorial. A method based on multiple factorial analysis is proposed in this study. Multivariate analysis results confirmed the existence of differences in the ANS in athletes depending on the training period and the sport discipline. Multiple Factorial Analysis provides a very powerful tool allowing the confrontation of whole information, which is more rich than an examination parameter by parameter to assess autonomic nervous system.

Computerized analysis of ST vs. HR for assessing myocardial ischaemia in the stress ECG

Stress electrocardiography is very important in myocardial ischaemia diagnosis and gives insight into therapeutic and preventive procedures. In this work the application of trend analysis is evaluated based on a digital processing of temporal series. Among other indicators, the ST vs. HR relation was studied in a database collected for this particular study. Preliminary results show the feasibility of using this information for a more precise interpretation of stress electrocardiograms.

Adaptation of five indirect insulin sensitivity evaluation methods to three populations: metabolic syndrome, athletic and normal subjects.

Insulin sensitivity is determined using direct or indirect methods. Indirect methods are less invasive than direct methods, but have lower accuracy. The accuracy is set through the Spearmans rank correlation coefficient between the indirect method and a direct method. Since the set of parameters of each indirect method has been set empirically, different values of insulin sensitivity have been reported when they are applied on different populations. In this paper, five indirect methods (Avignon, HOMA-IR, QUICKI, Raynaud, and Matsuda) used to determine insulin sensitivity were adapted to three different populations: athletics, metabolic syndrome and normal subjects. The parameters of each method were varied in a range of values until the optimal value that gives the best correlation coefficient with a gold standard was obtained. Results show that the adaptation procedure led to an improved correlation coefficient. Additionally, the method of Matsuda was the most accurate, followed by the method of Avignon. We have confirmed that each indirect method needs a different set of parameters when it is applied to a specific population in order to obtain an accurate value of insulin sensitivity.

Anthropometric measurements for assessing insulin sensitivity on patients with metabolic syndrome, sedentaries and marathoners.

The diagnosis of low insulin sensitivity is commonly done through the HOMA-IR index, in which fasting insulin and glucose blood levels are evaluated. Insulin and blood glucose levels are used for insulin sensitivity assessment by surrogate methods (HOMA-IR, Matsuda, etc), but anthropometric measurements like body weight, height and waist circumference are not considered, even if these variables also are related to low insulin sensitivity and metabolic syndrome. In this study we evaluate the impact of anthropometric measurements on the HOMA-IR, Matsuda and Caumo indexes to estimate insulin sensitivity. Specifically, we compare insulin sensitivity indexes with and without the anthropometric measurements in their equations on three different groups: patients with metabolic syndrome, sedentaries and marathoners. Results show relationships between anthropometric variables and insulin sensitivity indexes. On the other hand, subjects are mapped differently for insulin sensitivity assessment when anthropometric variables are taken into account. In addition, subjects diagnosed with normal insulin sensitivity could be considered as having low insulin sensitivity when anthropometric variables are considered.

Extracting Stationary Segments from Non-Stationary Synthetic and Cardiac Signals

Physiological signals are commonly the result of complex interactions between systems and organs, these interactions lead to signals that exhibit a non-stationary behaviour. For cardiac signals, non-stationary heart rate variability (HRV) may produce misinterpretations. A previous work proposed to divide a non-stationary signal into stationary segments by looking for changes in the signal’s properties related to changes in the mean of the signal. In this paper, we extract stationary segments from non-stationary synthetic and cardiac signals. For synthetic signals with different signal-to-noise ratio levels, we detect the beginning and end of the stationary segments and the result is compared to the known values of the occurrence of these events. For cardiac signals, RR interval (cardiac cycle length) time series, obtained from electrocardiographic records during stress tests for two populations (diabetic patients with cardiovascular autonomic neuropathy and control subjects), were divided into stationary segments. Results on synthetic signals reveal that the non-stationary sequence is divided into more stationary segments than needed. Additionally, due to HRV reduction and exercise intolerance reported on diabetic cardiovascular autonomic neuropathy patients, non-stationary RR interval sequences from these subjects can be divided into longer stationary segments compared to the control group.