**4.2 SBP2000**

Although SP2000 is specific software for ECG, SBP2000 can record and analyze not only ECG but also intra ventricular pressure, blood pressure, blood flow and respiration. Operation is almost the same as SP2000.

#### **4.3 SHL-2W**

SHL-2W is prepared for advanced analysis of arrhythmias for ECG. This software analyzes arrhythmias such as premature ventricular contraction (PVC), premature atrial contraction (PAC), ventricular tachycardia (VT), ventricular fibrillation (VF), Pause, etc based on patterns of QRS complex from long term recording ECGs obtained by the telemetry and Holter ECG recorder. Fig. 5 shows an example of mouse ECG recorded using the telemetry system. Some arrhythmias such as PVC are observed in this ECG. High lightened part is also shown below as an expanded window.

Fig. 6 is Print Preview window. ECGs are able to print out as compress waves.

ECG: characteristic points of the P, Q, R, S, T waves as well as the time intervals between these different points by Edit screen as shown in Fig. 4. The program can operate in automatic detection of complexes directly from the ECG signal. This detection is based on

Although SP2000 is specific software for ECG, SBP2000 can record and analyze not only ECG but also intra ventricular pressure, blood pressure, blood flow and respiration.

SHL-2W is prepared for advanced analysis of arrhythmias for ECG. This software analyzes arrhythmias such as premature ventricular contraction (PVC), premature atrial contraction (PAC), ventricular tachycardia (VT), ventricular fibrillation (VF), Pause, etc based on patterns of QRS complex from long term recording ECGs obtained by the telemetry and Holter ECG recorder. Fig. 5 shows an example of mouse ECG recorded using the telemetry system. Some arrhythmias such as PVC are observed in this ECG. High lightened part is

Fig. 6 is Print Preview window. ECGs are able to print out as compress waves.

the presence of a R wave peak.

Fig. 4. Edit screen of a mouse ECGs.

Operation is almost the same as SP2000.

also shown below as an expanded window.

**4.2 SBP2000** 

**4.3 SHL-2W** 

Fig. 5. Long term ECGs of mouse represent with SHL-2W window.

Fig. 6. Print preview window of compress ECGs.

Recent Advances in Telemetry Monitoring and Analysis for Laboratory Animals 151

Power spectral analysis of HRV has been studied and applied in not only human beings but also many animal species. In this section, I describe HRV in itself and methods for analysis

Heart rate being regulated by autonomic nervous system and endocrine system, is known to be affected with changes in postures, with exercise, with changes in psychological states. But heart rate is also known to fluctuate around the mean heart rate even in a stable condition. For example, when we inhale heart rate rises and when we exhale heart rate drops. This fluctuation of heart rate is known as respiratory sinus arrhythmia, and it occurs because burst rate at the sino atrial node changes according to respiration cycle. This kind of rhythmic fluctuation of the heart rate under stable condition, brought about by naturally occurring physiological perturbations such as respiration, blood pressure, and thermoregulation, is recognized as HRV. Considering that the principle systems involved in regulating the heart rate are mainly the sympathetic and parasympathetic nervous system, it has been suggested that the analysis of HRV could lead to noninvasive assessment of the

Since HRV reflects cardiac autonomic outflow, attempts have been made to assess this outflow by analyzing HRV. Time domain analysis with the use of standard deviation of R-R interval has been proposed as measures of parasympathetic activity. But this is a nonspecific quantifier of HRV and we cannot analyze the factors which produce this variability. To solve this problem, frequency domain analysis with the use of power spectrum has proven useful to sort out the variability into components which the whole variability is consisted of. In this method, the variability is mathematically transformed into frequency components, and the power of each frequency is calculated. In this way, we can understand which frequency components make up the variability and how much influence they have on the

Example of a power spectrum of HRV in human is shown in Fig. 9. In human beings, three major components can be observed. One in the low frequency (LF) area of 0.04-0.15 Hz, one in the high frequency (HF) area of around 0.20 Hz and one below the LF. The LF power which is the components between 0.04-0.15 Hz in human, reflect the heart rate fluctuating at a cycle of about 10 seconds. This component is said to be the result of the Mayer wave of arterial pressure reflecting on the burst rate of the sino atrial node through baroreflex (Scher, 1977). Both the sympathetic and parasympathetic outflow are considered to regulate the LF components (Akselrod, et al., 1981; Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996). The HF power which is the components between 0.15-0.40 Hz in human, derives from respiratory sinus arrhythmia (Hirsch & Bishop, 1981). The frequency of the component is this area coincides with the frequency of respiration. This component is said to be the respiratory system ad afferent signals from receptors in the lung influencing the cardiovascular system. Only the parasympathetic outflow is considered to regulate the HF components (Akselrod, et al., 1981; Task Force of the European Society of Cardiology and the North American Society of

**5. Heart Rate Variability (HRV)** 

tonic autonomic regulation of the heart rate.

Pacing and Electrophysiology, 1996).

of HRV.

**5.1 What HRV is** 

**5.2 Analysis of HRV** 

whole.
