Transfer function analysis of vagal control of heart rate during synchronized vagal stimulation

1995 ◽  
Vol 269 (6) ◽  
pp. H1931-H1940 ◽  
Author(s):  
A. Mokrane ◽  
A. R. LeBlanc ◽  
R. Nadeau
Keyword(s):  
Heart Rate ◽  
Transfer Functions ◽  
Vagal Stimulation ◽  
Sinus Node ◽  
Time Interval ◽  
Pass Filter ◽  
Dynamic Component ◽  
Low Pass Filter ◽  
Transfer Function Analysis ◽  
Low Pass

Synchronized electrical stimulation was used to study the heart rate (HR) response to fluctuations in parasympathetic input to the sinus node in anesthetized dogs. This was obtained by varying the time interval (interpulse interval) between stimulatory vagal pulses. Spectral methods were used to estimate transfer functions between the excitatory signal and the resulting HR response for different intensities of vagal stimulation. The intensity of vagal stimulation was proportional to the number of pulses delivered in each cardiac cycle. From the estimated transfer functions, and based on a mathematical model of the time course of ACh concentration at the sinus node, filter models were derived by using a system identification approach. HR response was characterized by a combination of two different filter behaviors: a low-pass filter behavior of mean cut-off frequency of 0.065 Hz and an all-pass filter behavior. The magnitude of the low-pass filter gain decreased with increasing intensity of vagal stimulation. The magnitude of the all-pass filter gain increased and then decreased with increasing intensity of vagal stimulation. The all-pass filter characteristics of HR response during synchronized stimulation of the vagus nerves are specific to this mode of stimulation, because they were not observed in nonsynchronized modes of vagal stimulation. We can conclude that, during synchronized vagal stimulation, the HR response exhibits both a slow dynamic component and a fast component related to beat-to-beat variations.

Bidirectional augmentation of heart rate regulation by autonomic nervous system in rabbits

1996 ◽  
Vol 271 (1) ◽  
pp. H288-H295 ◽  
Author(s):  
T. Kawada ◽  
Y. Ikeda ◽  
M. Sugimachi ◽  
T. Shishido ◽  
O. Kawaguchi ◽  
...  
Keyword(s):  
Heart Rate ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Transfer Function ◽  
Vagal Stimulation ◽  
Dynamic Interaction ◽  
Sympathetic Stimulation ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass

Although the characteristics of the static interaction between the sympathetic and parasympathetic nervous systems in regulating heart rate (HR) have been well established, how the dynamic interaction modulates the HR response remains unknown. We therefore investigated dynamic interaction by estimating the transfer function from nerve stimulation to HR using a band-limited Gaussian white-noise technique. The transfer function relating dynamic sympathetic stimulation to HR had characteristics of a second-order low-pass filter. Simultaneous tonic vagal stimulation at 5 and 10 Hz increased gain of the transfer function by 55.0 +/- 40.1 and 80.7 +/- 50.5%, respectively (P < 0.05). The transfer function from dynamic vagal stimulation to HR had characteristics of a first-order low-pass filter. Simultaneous tonic sympathetic stimulation at 5 and 10 Hz increased the gain by 18.2 +/- 17.9 and 24.1 +/- 18.0%, respectively (P < 0.05). Thus interaction augmented dynamic gain bidirectionally, even though it affected mean HR antagonistically. By virtue of this interaction, the autonomic nervous system appears to extend its dynamic range of operation.

Disturbance Elimination of Buck-Converter with Resonant LPF via ILQ Servo-System

2014 ◽  
Vol 492 ◽  
pp. 493-498
Author(s):  
Shuhei Shiina ◽  
Sidshchadhaa Aumted ◽  
Hiroshi Takami
Keyword(s):  
Transfer Functions ◽  
Design Method ◽  
Servo System ◽  
State Equation ◽  
Buck Converter ◽  
Linear Quadratic ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
The Stability

The proposed optimal control on the basis of both current and voltage of the buck-converter is designed to be based on Inverse Linear Quadratic (ILQ) design method with the resonant low pass filter, which eliminates the disturbance by appended disturbance compensator. The designed scheme is composed of the state equation, an optimal ILQ solution, the ILQ servo-system with the disturbance elimination, the optimal basic gain, the optimal condition, the transfer functions and the disturbance compensator. Our results show the proposed strategy is the stability and robust control and has been made to improve ILQ control for the disturbance elimination of the output response, which guarantees the optimal gains on the basis of polynomial pole assignment.

The Design of Ideal Positioning Servo System

2015 ◽  
Vol 816 ◽  
pp. 132-139
Author(s):  
Ľubica Miková ◽  
Alexander Gmiterko ◽  
Michal Kelemen
Keyword(s):  
Frequency Characteristic ◽  
Pid Controller ◽  
Transfer Functions ◽  
Servo System ◽  
Second Order ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Degree Of Stability

The paper deals with the design of an ideal positioning servo system. To achieve this aim, we will derive transfer functions of the PID controller and the second-order low-pass filter while using typical fault frequencies for PID controller with a low pass filter. Consequently, an overall frequency characteristic of the open servo system will be depicted. This characteristic will be further used to determine the amplitude and phase safety, which determine the degree of stability system.

Band-Stop Filter Algorithm Research Based on Nano-Displacement Positioning System

2013 ◽  
Vol 380-384 ◽  
pp. 697-700 ◽  
Author(s):  
Yue Zhou ◽  
Xiao Xiao Yao ◽  
Jin Xiang Pian ◽  
Yan Qiang Su
Keyword(s):  
Transfer Functions ◽  
Experimental Simulation ◽  
Infinite Impulse Response ◽  
Positioning System ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Control Precision ◽  
Band Stop Filter ◽  
Low Pass ◽  
Inherent Frequency

This paper proposed the algorithms of infinite impulse response (IIR) band-stop filter and all-pass filter to eliminate the inherent frequency for piezoelectric ceramics and improve the control precision for nanodisplacement positioning system. The IIR algorithm was composed of five steps (such as the determination of normalized frequency, filter orders and transfer functions of analog low-pass filter, analog band-stop filter and digital band-stop filter). Based on the experimental simulation results on the nanodisplacement positioning platform, the butterworth band-stop filter algorithm can achieve the requested filtering effects within 10 orders .

scholarly journals On the Autonomous Gain and Phase Tailoring Transfer Functions of Symmetrically Distributed Piezoelectric Sensors

2004 ◽  
Vol 126 (4) ◽  
pp. 528-536 ◽  
Author(s):  
Yu-Hsiang Hsu ◽  
Chih-Kung Lee
Keyword(s):  
Strain Distribution ◽  
Transfer Functions ◽  
Design Concept ◽  
Piezoelectric Sensors ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Distributed Sensors ◽  
Distributed Sensor ◽  
Finite Plate ◽  
Low Pass

A new design concept for a distributed sensor, which was developed based on the principle that the strain distribution of an arbitrary finite plate structure can be expressed as the superposition of even and odd strain functions, is presented. The distributed sensors adopt a symmetric weighting electrode to match the symmetric distribution of the even parts of the strain in order to introduce a no-phase delay low-pass filter to tailor the sensor transfer function. Both the design concept and the experimental results are detailed herein.

Transfer function analysis of autonomic regulation. II. Respiratory sinus arrhythmia

1989 ◽  
Vol 256 (1) ◽  
pp. H153-H161 ◽  
Author(s):  
J. P. Saul ◽  
R. D. Berger ◽  
M. H. Chen ◽  
R. J. Cohen
Keyword(s):  
Heart Rate ◽  
Transfer Function ◽  
Respiratory Sinus Arrhythmia ◽  
Respiratory Activity ◽  
Autonomic Regulation ◽  
Upright Posture ◽  
Sinus Arrhythmia ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Transfer Function Analysis

An efficient new technique was developed to investigate heart rate control at all physiologically relevant frequencies by using respiratory activity as a frequency probe of the autonomic nervous response. The transfer function from respiratory activity to heart rate was determined during 6-min periods in which the respiratory rate was voluntarily controlled in a predetermined but erratic fashion. Changes in posture were used to manipulate autonomic balance. Respiratory sinus arrhythmia was determined to be a frequency-dependent phenomenon with the magnitude and phase characteristics of a low-pass filter. In agreement with previous work, at typical respiratory frequencies (greater than 0.15 Hz) increases in heart rate occurred simultaneously with the onset of inspiratory activity; however, at frequencies less than 0.15 Hz the phase relationship was quite different, such that increases in heart rate preceded inspiration. Between 0.15 and 0.45 Hz, the transfer magnitude was consistently lower while the subjects were in the upright posture than when in the supine posture, but below 0.15 Hz, it was equal in both postures. A model for respiratory modulation of heart rate, based on the atrial rate response characteristics determined in the companion paper [Am. J. Physiol. 256 (Heart Circ. Physiol. 25): H142-H152, 1989], suggests that the magnitude and phase characteristics of the subjects in the supine and upright postures differ because of relatively increased sympathetic outflow in the upright posture. A precise and efficient characterization of respiratory sinus arrhythmia can yield considerable insight into the autonomic regulation of the heart.

Transfer function analysis of autonomic regulation. I. Canine atrial rate response

1989 ◽  
Vol 256 (1) ◽  
pp. H142-H152 ◽  
Author(s):  
R. D. Berger ◽  
J. P. Saul ◽  
R. J. Cohen
Keyword(s):  
Transfer Function ◽  
Transfer Functions ◽  
Function Analysis ◽  
Cardiac Pacemaker ◽  
Corner Frequency ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Atrial Rate ◽  
Transfer Function Analysis ◽  
Functional Components

We present a useful technique for analyzing the various functional components that comprise the cardiovascular control network. Our approach entails the imposition of a signal with broad frequency content as an input excitation and the computation of a system transfer function using spectral estimation techniques. In this paper, we outline the analytical methods involved and demonstrate the utility of our approach in studying the dynamic behavior of the canine cardiac pacemaker. In particular, we applied frequency-modulated pulse trains to either the right vagus or the cardiac sympathetic nerve and computed transfer functions between nerve stimulation rate and the resulting atrial rate. We found that the sinoatrial node (and associated automatic tissue) responds as a low-pass filter to fluctuations in either sympathetic or parasympathetic tone. For sympathetic fluctuations, however, the filter has a much lower corner frequency than for vagal fluctuations and is coupled with a roughly 1.7-s pure delay. We further found that the filter characteristics, including the location of the corner frequency and rate of roll-off, depend significantly on the mean level of sympathetic or vagal tone imposed.

Neuronal uptake affects dynamic characteristics of heart rate response to sympathetic stimulation

1999 ◽  
Vol 277 (1) ◽  
pp. R140-R146 ◽  
Author(s):  
Tsutomu Nakahara ◽  
Toru Kawada ◽  
Masaru Sugimachi ◽  
Hiroshi Miyano ◽  
Takayuki Sato ◽  
...  
Keyword(s):  
Heart Rate ◽  
Transfer Function ◽  
Lag Time ◽  
Stimulation Frequency ◽  
Neuronal Uptake ◽  
Sympathetic Stimulation ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Dynamic Gain

Recently, studies in our laboratory involving the use of a Gaussian white noise technique demonstrated that the transfer function from sympathetic stimulation frequency to heart rate (HR) response showed dynamic characteristics of a second-order low-pass filter. However, determinants for the characteristics remain to be established. We examined the effect of an increase in mean sympathetic stimulation frequency and that of a blockade of the neuronal uptake mechanism on the transfer function in anesthetized rabbits. We found that increasing mean sympathetic stimulation frequency from 1 to 4 Hz significantly ( P < 0.01) decreased the dynamic gain of the transfer function without affecting other parameters, such as the natural frequency, lag time, or damping coefficient. In contrast, the administration of desipramine (0.3 mg/kg iv), a neuronal uptake blocking agent, significantly ( P < 0.01) decreased both the dynamic gain and the natural frequency and prolonged the lag time. These results suggest that the removal rate of norepinephrine at the neuroeffector junction, rather than the amount of available norepinephrine, plays an important role in determining the low-pass filter characteristics of the HR response to sympathetic stimulation.

scholarly journals Temporal Modulation Transfer Functions in Cat Primary Auditory Cortex: Separating Stimulus Effects From Neural Mechanisms

2002 ◽  
Vol 87 (1) ◽  
pp. 305-321 ◽  
Author(s):  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Cortical Neurons ◽  
Transfer Functions ◽  
Frequency Tuning ◽  
Primary Auditory Cortex ◽  
Modulation Transfer ◽  
Temporal Modulation ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass

We present here a comparison between the local field potentials (LFP) and multiunit (MU) responses, comprising 401 single units, in primary auditory cortex (AI) of 31 cats to periodic click trains, gamma-tone and time-reversed gamma-tone trains, AM noise, AM tones, and frequency-modulated (FM) tones. In a large number of cases, the response to all six stimuli was obtained for the same neurons. We investigate whether cortical neurons are likely to respond to all types of repetitive transients and modulated stimuli and whether a dependence on modulating waveform, or tone or noise carrier, exists. In 97% of the recordings, a temporal modulation transfer function (tMTF) for MU activity was obtained for gamma-tone trains, in 92% for periodic click trains, in 83% for time-reversed gamma-tone trains, in 82% for AM noise, in 71% for FM tones, and only in 53% for AM tones. In 31% of the cases, the units responded to all six stimuli in an envelope-following way. These particular units had significantly larger onset responses to each stimulus compared with all other units. The overall response distribution shows the preference of AI units for stimuli with short rise times such as clicks and gamma tones. It also shows a clear asymmetry in the ability to respond to AM noise and AM tones and points to a strong effect of the frequency content of the carrier on the subcortical processing of AM stimuli. Yet all temporal response properties were independent of characteristic frequency and frequency-tuning curve bandwidth. We show that the observed differences in the tMTFs for different stimuli are to a large extent produced by the different degree of phase locking of the neuronal firings to the envelope of the first stimulus in the train or first modulation period. A normalization procedure, based on these synchronization differences, unified the tMTFs for all stimuli except clicks and allowed the identification of a largely stimulus-invariant, low-pass temporal filter function that most likely reflects the properties of synaptic depression and facilitation. For nonclick stimuli, the low-pass filter has a cutoff frequency of ∼10 Hz and a slope of ∼6 dB/octave. For nonclick stimuli, there was a systematic difference between the vector strength for LFPs and MU activity that can likely be attributed to postactivation suppression mechanisms.

scholarly journals Preset time count rate meter using adaptive digital signal processing

2005 ◽  
Vol 20 (1) ◽  
pp. 64-73 ◽  
Author(s):  
Aleksandar Zigic
Keyword(s):  
Signal Processing ◽  
Count Rate ◽  
Time Interval ◽  
Adaptation Algorithm ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Preset Time ◽  
The Mean ◽  
Low Pass Filters

Two presented methods were developed to improve classical preset time count rate meters by using adapt able signal processing tools. An optimized detection algorithm that senses the change of mean count rate was implemented in both methods. Three low-pass filters of various structures with adaptable parameters to implement the control of the mean count rate error by suppressing the fluctuations in a controllable way, were considered and one of them implemented in both methods. An adaptation algorithm for preset time interval calculation executed after the low-pass filter was devised and implemented in the first method. This adaptation algorithm makes it possible to obtain shorter preset time intervals for higher stationary mean count rate. The adaptation algorithm for preset time interval calculation executed before the low-pass filter was devised and implemented in the second method. That adaptation algorithm enables sensing of a rapid change of the mean count rate before fluctuations suppression is carried out. Some parameters were fixed to their optimum values after appropriate optimization procedure. Low-pass filters have variable number of stationary coefficients depending on the specified error and the mean count rate. They implement control of the mean count rate error by suppressing fluctuations in a controllable way. The simulated and realized methods, using the developed algorithms, guarantee that the response time shall not exceed 2 s for the mean count rate higher than 2 s-1 and that controllable mean count rate error shall be within the range of ?4% to ?10%.

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