A biomedical signal is basically any signal measured from a living organism. Commonly used biomedical signals include for example the electrocardiogram (ECG), blood pressure (BP), pulse wave signal using PPG, electroencephalogram (EEG) or event-related brain potentials, and time series data from functional magnetic resonance imaging (fMRI).
Biomedical signal monitoring is used in clinical practice for many purposes; for example to capture the occurrence and type of cardiac arrhythmias using Holter ECG monitoring, or to diagnose sleep disorders using polysomnography. The strength of using biomedical signal measurements in healthcare is that they give objective, evidence based quantitative information about physiology or neurophysiology, which can truly help in clinical diagnostics.
The measurement technology for biomedical signals has developed rapidly within the past decades, and nowadays there exist many easy-to-use, affordable and mobile measurement devices for recording these signals. Preventive healthcare, personal monitoring and quantified-self are current trends where biomedical signal monitoring and analyses have a key role. For example, they can be used to objectively evaluate physical fitness, training effect and recovery time, and occupational health (stress and recovery).
About heart rate variability analysis
Heart rate variability (HRV) analysis is generally used for evaluating autonomic nervous system (ANS) functioning in cardiovascular research and in different human wellbeing related applications. HRV is known to be affected, e.g. by stress, certain cardiac diseases and pathological states.
HRV is about variations between successive inter-beat-intervals (IBIs) or RR intervals (time intervals between successive ECG R-waves). IBI varies due to ANS regulation of the sinoatrial (SA) node of the heart. ANS is divided into sympathetic and parasympathetic branches and their influences on heart rate (HR) and HRV are quite well understood. Sympathetic activity increases HR and decreases HRV, whereas parasympathetic activity decreases HR and increases HRV. The control of the autonomic output involves several interconnected areas of central nervous system, which form the so-called central autonomic network. In addition to this central control, arterial baroreceptor reflex as well as respiration are known to induce quick changes in heart rate.
The most conspicuous periodic component of HRV is the respiratory sinus arrhythmia (RSA) which is considered to range from 0.15 to 0.4 Hz. This high frequency (HF) component is mediated almost solely by the parasympathetic nervous activity. The RSA component originates due to changes in vagus nerve stimulation during breathing cycles, causing HR to increase during inhalation and decrease during exhalation. Thus, in order to make reliable interpretations of HRV, respiratory frequency should be known. Another apparent component of HRV is the low frequency (LF) component ranging from 0.04 to 0.15 Hz. The LF component is generally thought of being both of sympathetic and parasympathetic origin, but there are studies demonstrating that the normalized value of the LF component could be used to assess sympathetic efferent activity. The fluctuations below 0.04 Hz, on the other hand, have not been studied as much as the higher frequencies. These very low frequency (VLF) components are characteristic for HRV signals and have been related to, e.g., humoral factors such as the thermoregulatory processes and renin-angiotensin system. Naturally also circadian rhythm and daily activities among many other factors can have major effect on the VLF component.
HRV is a commonly used tool when trying to assess the functioning of cardiac autonomic regulation. It has been used in multitude of studies, related to cardiovascular research and different human wellbeing applications, as an indirect tool to evaluate the functioning and balance of the ANS.
One of the main clinical scenarios where HRV has been found valuable include the risk stratification of sudden cardiac death after acute myocardial infarction. In addition, decreased HRV is generally accepted to provide an early warning sign of diabetic cardiovascular autonomic neuropathy, the most significant decrease in HRV being found within the first 5-10 years of diabetes. Besides these two main clinical scenarios, HRV has been studied with relation to several cardiovascular diseases, renal failure, physical exercise, occupational and psychosocial stress, gender, age, drugs, alcohol, smoking and sleep.