EP0869734A4 - - Google Patents
Info
- Publication number
- EP0869734A4 EP0869734A4 EP95934981A EP95934981A EP0869734A4 EP 0869734 A4 EP0869734 A4 EP 0869734A4 EP 95934981 A EP95934981 A EP 95934981A EP 95934981 A EP95934981 A EP 95934981A EP 0869734 A4 EP0869734 A4 EP 0869734A4
- Authority
- EP
- European Patent Office
- Prior art keywords
- window
- frequency
- selecting
- selector
- transform
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/0245—Detecting, measuring or recording pulse rate or heart rate by using sensing means generating electric signals, i.e. ECG signals
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02405—Determining heart rate variability
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
- A61B5/4029—Detecting, measuring or recording for evaluating the nervous system for evaluating the peripheral nervous systems
- A61B5/4035—Evaluating the autonomic nervous system
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4884—Other medical applications inducing physiological or psychological stress, e.g. applications for stress testing
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7253—Details of waveform analysis characterised by using transforms
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
- A61B5/372—Analysis of electroencephalograms
- A61B5/374—Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7253—Details of waveform analysis characterised by using transforms
- A61B5/7257—Details of waveform analysis characterised by using transforms using Fourier transforms
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7253—Details of waveform analysis characterised by using transforms
- A61B5/726—Details of waveform analysis characterised by using transforms using Wavelet transforms
Definitions
- the present invention relates to apparatus and method for time dependent power spectrum analysis of physiological signals in general and in particular to time dependent power spectrum analysis of cardio- respiratory physiological signals modulated by the Autonomic Nervous
- ANS Autonomic Nervous System
- physiological signals include cardio-respiratory signals including, respiration, ECG, heart rate (HR), blood pressure (BP), blood flow, vascular resistance, cardiac volume, cardiac cross section, cardiac contractility, peripheral resistance, and the like.
- Other physiological signals which are not modulated by the ANS include EEG signals, EMG signal, ECoG signals, and the like.
- perturbations and/or transient changes which affect the functioning of the ANS affect the physiological signals and vice versa.
- Common perturbations used in the analysis of autonomic control include changing of posture, tilt, pharmaceutical interventions, deep breaths, vagal maneuvers, hand grip, and others.
- the power spectrum of physiological signals in humans modulated by the ANS can be divided into two frequency ranges: the Low Frequency (LF) range below 0J 5 Hz and the High Frequency (HF) range above 0J 5 Hz displaying a peak at about 0.2 Hz for adults and a peak at about 0.4 Hz for children.
- the HF range is mediated by the fast reacting parasympathetic nervous system while the LF range is mediated by both the parasympathetic nervous system and the slower reacting sympathetic nervous system.
- Time frequency distributions include the Short Time Fourier Transform (STFT), distributions belonging to the Cohen's class such as the Wigner-Ville Distribution (WVD), Exponential Distribution (ED), and the like.
- STFT Short Time Fourier Transform
- WVD Wigner-Ville Distribution
- ED Exponential Distribution
- Time dependent models are based on Auto Regressive (AR) or Auto Regressive Moving Average (ARMA) modeling.
- AR Auto Regressive
- ARMA Auto Regressive Moving Average
- the present invention is for an apparatus and method for time dependent power spectrum analysis of physiological signals in general and of cardio-respiratory physiological signals modulated by the Autonomic Nervous System (ANS) in particular.
- ANS Autonomic Nervous System
- an apparatus for time dependent power spectrum analysis of a physiological signal modulated by the autonomic nervous system comprising: (a) a sensor for picking up a physiological signal modulated by the autonomic nervous system; (b) frequency selection apparatus for selecting at least one frequency inherent to the signal; (c) a selective windowed time- frequency analysis processor for determining the power spectrum of the physiological signal within a window along the signal for the at least one frequency; and (d) output apparatus for providing information associated with the functioning of the autonomic nervous system as provided by the power spectrum of the physiological signal.
- the senor is selected from one of the following: an ECG recorder, a respiratory monitor, a blood pressure transducer, a Doppler flow meter, a tachometer, a finger plethysmograph, a skin resistance galvanometer or any other cardiovascular monitoring equipment.
- the window has an aperture selected from one of the following: a rectangular aperture, a Hamming aperture, a Hanning aperture, a Blackman aperture, a Gaussian window, a Lorentzian window, a sine window, any power of a sine window and any power of a cosine window, or any derivative of these windows.
- the apparatus further comprising frequency selection apparatus for determining the frequency resolution of the apparatus.
- the apparatus further comprising timing selection apparatus for determining the time resolution of the apparatus.
- the apparatus further comprising a physiological signal selector for selecting the type of physiological signal picked up the sensor.
- the apparatus further comprising a type of perturbation selector for selecting the type of perturbation to be applied to a subject under investigation.
- the apparatus further comprising frequency selection apparatus for determining the range of frequency outputted on the output apparatus.
- the apparatus further comprising timing selection apparatus for determining the onset and termination of the time-dependent power spectrum of the physiological signal outputted on the output apparatus.
- the apparatus further comprising a detrending filter deployed between the sensor and the selective windowed time-frequency analysis processor.
- the selective windowed time-frequency analysis processor is a Wavelet processor.
- the apparatus further comprising a prototype function selector for selecting a prototype function applied by the Wavelet processor.
- the apparatus further comprising a scale parameters selector for selecting scale parameters applied by the Wavelet processor.
- the apparatus further comprising a shift parameters selector for selecting shift parameters applied by the Wavelet processor.
- the selective windowed time-frequency analysis processor is a selective discrete spectral transform algorithm processor.
- the apparatus further comprising a spectral transform selector for selecting a transform selected from one of the following: the Fourier transform, the Haar transform, the Hartley transform, the sine transform, the cosine transform, and the Hadamard transform.
- the apparatus further comprising a window duration selector for selecting the duration of the window.
- the apparatus further comprising a window aperture selector for selecting the aperture of the window.
- the apparatus further comprising a number of points selector for selecting the number of data points within the window.
- the apparatus further comprising a decimation technique selector for selecting the decimation technique applied by the selective discrete spectral transform analysis processor.
- a method of time dependent power spectrum analysis of a physiological signal modulated by the autonomic nervous system comprising the steps of: (a) picking up a physiological signal modulated by the autonomic nervous system; (b) selecting at least one frequency inherent to the signal; (c) determining the power spectrum of the physiological signal within a window along the signal for the at least one frequency; and (d) providing information associated with the functioning of the autonomic nervous system as provided by the power spectrum of the physiological signal.
- an apparatus for time dependent power spectrum analysis of a physiological signal comprising: (a) a sensor for picking up a physiological signal; (b) a frequency selector for selecting at least one frequency inherent to the signal; (c) window generating apparatus for generating a window along the signal, the duration of the window being substantially inversely related to the at least one frequency; (d) decimation apparatus for providing data points within the window; (e) spectral transform apparatus for determining the power spectrum of the signal within the window for the at least one frequency; and (f) output apparatus for providing information associated with time dependent power spectrum of the signal.
- the senor is selected from one of the following: an ECG recorder, a respiratory monitor, a finger plethysmograph, a Doppler flow meter, a tachometer, a blood pressure transducer, a skin resistance galvanometer, an EEG monitor and an EMG monitor.
- the window having an aperture selected from one of the following: a rectangular aperture, a Hamming aperture, a Hanning aperture, a Blackman aperture, a Gaussian window, a Lorentzian window, a sine window, any power of a sine window and any power of a cosine window or any derivative of these windows.
- the apparatus further comprising frequency selection apparatus for determining the frequency resolution of the apparatus.
- the apparatus further comprising timing selection apparatus for determining the time resolution of the apparatus.
- the apparatus further comprising a physiological signal selector for selecting the type of physiological signal picked up the signal.
- the apparatus further comprising a type of perturbation selector for selecting the type of perturbation to be applied to a subject under investigation.
- the apparatus further comprising frequency selection apparatus for determining the range of frequency outputted on the output apparatus.
- the apparatus further comprising timing selection apparatus for determining the onset and termination of the time dependent power spectrum of the physiological signal outputted on the output apparatus.
- the apparatus further comprising a detrending filter deployed between the sensor and the selective windowed time-frequency analysis processor.
- the apparatus further comprising a spectral transform selector for selecting a transform selected from one of the following: the Fourier transform, the Haar transform, the Hartley transform, the sine transform, the cosine transform, and the Hadamard transform.
- the apparatus further comprising a window duration selector for selecting the duration of the window.
- the apparatus further comprising a window aperture selector for selecting the aperture of the window.
- the apparatus further comprising a number of points selector for selecting the number of data points within the window.
- the apparatus further comprising a decimation technique selector for selecting the decimation technique applied by the selective discrete spectral transform analysis processor.
- a method of time dependent power spectrum analysis of a physiological signal comprising the steps of: (a) picking up a physiological signal; (b) selecting at least one frequency inherent to the signal; (c) generating a window along the signal, the duration of the window being substantially inversely related to the at least one frequency; (d) providing data points within the window; (e) determining the power spectrum of the signal within the window for the at least one frequency; and (f) providing information associated with time dependent power spectrum of the signal.
- FIG. 1 is a block diagram of a preferred embodiment of an apparatus, constructed and operative according to the teachings of the present invention, employing a selective windowed time-frequency analysis processor for time dependent power spectrum analysis of physiological signals;
- FIG. 2 is a representative trace of the heart rate detected from an ECG signal picked up by an ECG recorder of a subject who undergoes a perturbation in the form of a change in posture from a supine position to a standing position;
- FIG. 3 is a block diagram of the selective windowed time-frequency analysis processor of Figure 1 realized as a wavelet processor;
- FIG. 4 is a block diagram of the selective windowed time-frequency analysis processor of Figure 1 realized as a selective discrete spectral transform processor;
- FIGS. 5a-5c are oscilloscope type time dependent graphs of the LF power, the HF power and the LF/HF ratio of the heart rate fluctuations of Figure 2, respectively;
- FIG. 6 is a 2D time dependent power spectrum contour map of the 3D time dependent power spectrum graph shown in Figure 1.
- the present invention is of an apparatus and method for time dependent power spectrum analysis of physiological signals in general and of cardio-respiratory physiological signals modulated by the Autonomic Nervous System (ANS) in particular.
- ANS Autonomic Nervous System
- Figure 1 shows an apparatus, generally designated 100, constructed and operative according to the teachings of the present invention, for analyzing the time dependent power spectrum of physiological signals in general and cardio-respiratory physiological signals modulated by the autonomic nervous system (ANS) in particular.
- ANS autonomic nervous system
- apparatus 100 performs time dependent power spectrum analysis of a stationary or a non-stationary, mono-component or multi-component physiological signal picked-up by a sensor 102 adapted for detecting the physiological signal.
- the physiological signals include cardio-respiratory signals including, respiration, ECG, heart rate (HR), blood pressure (BP), blood flow, vascular resistance, cardiac volume, cardiac cross section, cardiac contractility, peripheral resistance, and the like.
- Other physiological signals which are not modulated by the ANS include EEG signals, EMG signal, ECoG signals, and the like.
- sensor 102 can be an ECG recorder, a respiratory monitor, a blood pressure transducer, a Doppler flow meter, a tachometer, a finger plethysmograph, a skin resistance galvanometer, a skin resistance galvanometer, cadiovascular monitoring equipment, and the like.
- a change in posture (CP) induces an increase in the heart rate of the subject.
- the increase in heart rate is caused by changes in the modulation of the heart rate by both branches of the autonomic nervous system. First, by an attenuation in the modulation exerted by the fast reacting parasympathetic nervous system. And second, by the strengthening in the modulation of the heart rate exerted by the slower reacting sympathetic nervous system.
- apparatus 100 includes a selective windowed time-frequency analysis (S WTFA) processor, generally designated 104, for providing the time-dependent power spectrum analysis of the physiological signal picked up by sensor 102.
- S WTFA selective windowed time-frequency analysis
- SWTFA processor 104 can be realized by several implementations including, but not limited to, a Wavelet processor 106 as described in greater detail hereinbelow with reference to Figure 3, a Selective Discrete Spectral Transform Analysis processor 108 as described in greater detail hereinbelow with reference to Figure 4, and the like. In both cases, SWTFA processor 104 includes a window generator
- SWTFA processor 104 for generating a series of windows along the signal within which the power spectrum of the frequencies under investigation is to be analyzed.
- SWTFA processor 104 includes a power spectrum determination apparatus 112 for determining the power spectrum for a particular frequency within each window provided by window generator 110.
- the aperture of the windows can be, but are not limited to, a rectangular aperture, a Hamming aperture, a Blackman aperture, a Gaussian window, a Lorentzian window, a sine window, any power of a sine window, any power of a cosine window, any derivative of these windows, and the like.
- SWTFA processor 104 it is a particular feature of SWTFA processor 104 that the duration of the windows is generally inversely proportional to the frequency under investigation. Hence, low frequencies are investigated using long time windows while high frequencies are investigated using short time windows. It is a further feature of SWTFA processor 104 that a physiological signal can be analyzed at a wide range of both frequency resolutions and time resolutions. Typically, SWTFA processor 104 is capable of a frequency resolution in the order of 0.001 Hz at the low frequency end of the spectrum for, say, a duration of 30 minutes or even lower for a longer time duration. Furthermore, SWTFA processor 104 is capable of a time resolution which can reach 1 second for frequencies of around 2 Hz. The time and frequency resolutions reach intermediate values around the center of the time-frequency plane.
- apparatus 100 includes an operator interface 116 enabling an operator to select the type of physiological signal to be analyzed, the type of perturbation, and other operating parameters as will be described hereinbelow.
- operator interface 116 includes a physiological signal selector 118 for selecting the type of physiological signal to be analyzed and a type of perturbation selector 120 for selecting the type of perturbation to be applied to a subject under investigation.
- the frequencies or ranges of frequencies under investigation are preferably selected by a user using frequency selection apparatus 122.
- one or more frequencies can be selected for investigation from a range from about 0 Hz and about 20 Hz for the analysis of the autonomic nervous systems of a wide range of mammals.
- the frequencies under investigation are determined by assigning values to a first frequency register 124, a last frequency register 126 and a frequency interval register 128 such that SWTFA processor 104 processes a sequence of frequencies starting at the first frequency stored in first frequency register 124 and increasing in steps determined by frequency interval register 128 up to the last frequency stored in last frequency register 126.
- frequency selection apparatus 122 preferably includes one or more frequency range selectors 130 and 132 for determining the display of their corresponding power spectrum. Typically, frequency range selectors 130 and 132 are used for selecting displays of LF power and HF power.
- Operator interface 116 also includes timing selection apparatus 134 which includes a timer 136 for determining the time resolution of the analysis of the physiological signal and several pairs of START and STOP timers as described hereinbelow. It should be noted that timer 136 determines the degree of overlapping between consecutive windows.
- a first pair of timers 138 is preferably dedicated to controlling the onset and termination of the display of the LF power spectrum of the autonomic control modulating the physiological signal.
- a second pair of timers 140 is preferably dedicated to controlling the onset and termination of the display of the HF power spectrum of the autonomic control moderating the physiological signal.
- Other timers 142 can be assigned by the operator to determine time intervals during which other parameters can be displayed or calculated.
- SWTFA processor 104 is typically connected to sensor 102 via an amplifier 142, an anti aliasing filter 144, and an A/D converter 148.
- Other devices may be required to provide suitable data to SWTFA processor 104 depending on the type of signal being picked up by sensor 102. For example, in the case of sensor 102 picking up heartbeats, then an R wave detector is required to provide suitable data to SWTFA processor 104.
- the additional devices required to be provide suitable data to SWTFA processor 104 can be connected through selection of the type of physiological sensor to be picked up by sensor 102 using physiological signal selector 118.
- apparatus 100 preferably includes a detrending filter 150 deployed between A/D converter 146 and SWTFA processor 104 such that sudden changes of amplitude in the physiological signal after the perturbation do not affect the natural high frequency components of the physiological signal.
- the parameters of detrending filter 150 can be determined by the settings of physiological signal selector 118 and type of perturbation selector 120. Alternatively, the parameters of detrending filter 150 can be set by the operator using detrending filter control 152.
- Apparatus 100 further includes a display driver 154 for providing output on an output apparatus realized as a display monitor 156 and a normalization apparatus 158 for normalizing the output on display monitor 156.
- Output apparatus can also include a printer.
- the displays can include 3D graphic displays, 2D contour map displays, time dependent oscilloscope type displays, and the like depending on the type of information required by an operator.
- display driver 154 can display a 3D time dependent power spectrum graph 160 where the x-axis 162 of graph 160 depicts frequency in Hz, the y-axis 164 of graph 160 depicts time in seconds and the z-axis 166 of graph 160 depicts the power spectrum in units associated with the type of physiological signal being picked up by sensor 102.
- z-axis 166 can have units of beats per minute 2 Hz "1 (BPM 2 Hz '1 ) when the physiological signal measured is heart beat, mmHg 2 Hz ' when the physiological signal measured is blood pressure, (mlsec 1 ) 2 Hz ' when the physiological signal measured is blood flow, and the like.
- apparatus 100 includes a metrics processor 168 for providing one or more metrics depending on the type of information required by an operator. Metrics processor 168 typically receives input from a number of sources including, but not limited to, physiological signal selector 118, type of perturbation selector 120, frequency selection apparatus 122, timing selection apparatus 134, and the like.
- metrics processor 168 can provide the baseline LF power before perturbation, the LF power during or after perturbation, maximal and/or minimal activity during perturbation and the ratio therebetween.
- metrics processor 168 can provide the baseline HF power before perturbation, the HF power during or after perturbation, maximal and/or minimal activity during perturbation and the ratio therebetween.
- metrics processor 168 can provide the LF/HF ratio before perturbation to the LF/HF ratio after perturbation.
- the block diagram depicts the preferred embodiment of SWTFA processor 104 realized as Wavelet processor 106 including window generator 106 additionally designated 170 and power spectrum determination apparatus 112 additionally designated 172.
- SWTFA processor 104 realized as Wavelet processor 106 including window generator 106 additionally designated 170 and power spectrum determination apparatus 112 additionally designated 172.
- the aperture, duration and the time resolution between consecutive windows provided by window generator 170 are defined by three parameters: a prototype function h(t), a scale parameter "a” and a shift parameter "b" according to the Wavelet transform:
- the prototype function is stretched such that the prototype Wavelet acts as a low frequency function while, for a small scale parameter value, the prototype function is contracted such that the Wavelet function acts a high frequency function.
- the Wavelet function dilates or contracts in time, causing the corresponding contraction or dilation in the frequency domain.
- the Wavelet transform provides a flexible time-frequency resolution and analyzes higher frequencies with better time resolution but poorer frequency resolution than lower frequencies.
- apparatus 100 is configured such that the settings of physiological signal selector 118 and type of perturbation selector 120 determine the selections of prototype function h(t), effective scale parameters "a” and effective shift parameters "b", thereby obviating the need for direct operator intervention.
- apparatus 100 can include a prototype function selector 174 for selection of the prototype function h(t), a scale parameters selector 176 for selection of the scale parameter "a” and a shift parameters selector 178 for selection of shift parameter "b”, thereby enabling operator intervention in the regulation of Wavelet processor 106 according to the type of physiological signal to be analyzed, the type of perturbation, and the like.
- the aperture of the windows can be, but are not limited to, a rectangular aperture, a Hamming aperture, a Blackman aperture, a Gaussian window, a Lorentzian window, a sine window, any power of a sine window, any power of a cosine window, any derivative of these windows, and the like.
- SWTFA processor 104 realized as Selective Discrete Spectral Transform Algorithm processor (SDA) 108 including window generator 106 additionally designated 180 and power spectrum determination apparatus 112.
- power spectrum determination apparatus 112 includes decimation apparatus 182 for providing a constant number of data points from the windows, a spectral transform apparatus 184 for providing the power spectrum of the frequency within the windows based on the data points and a window correction apparatus 186 for correcting the power spectrum due to distortions rendered by window generator 180.
- SDA apparatus 108 can employ any one of a number of known transforms for determining the power spectrum of a time dependent physiological signal.
- Such transforms include the Fourier transform, the Haar transform, the Hartley transform, the sine transform, the cosine transform, the Hadamard transform, and the like.
- the selection of the spectral transform realized by SDA apparatus 180 is preferably operator controlled by means of a spectral transform selector 188.
- the duration of windows is preferably inversely related to the frequency under investigation. Depending on the type of signal, the duration of windows typically lies from about 2 periods and about 10 periods of the frequency under investigation.
- the duration is preferably user selected by means of a window duration selector 190.
- the duration of the window can be automatically set according to the SNR or similar metric of the physiological signal.
- the windows can have different apertures including, but not limited to, a rectangular aperture, a Hamming aperture, a Harming aperture, a Blackman aperture, a Gaussian window, a Lorentzian window, a sine window, any power of a sine window, any power of a cosine window, any derivative of these windows, and the like.
- the aperture of the window is preferably user selected by means of a window aperture selector 192.
- window correction apparatus 186 is required to correct the obtained power spectra by dividing by the corresponding sine function. For other windows and transforms, the correction required depends on the type of window and the mathematical rules of the transform.
- Decimation apparatus 182 preferably provides data points by employing a low pass filter and undersampling technique including, but not limited to, moving average. Typically, decimation apparatus 182 provides the same number of data points irrespective of the duration of the windows so as not to generate artifacts or normalization problems.
- the number of data points determined in a window is preferably operator selected by means of a number of data points selector 194.
- SDA apparatus 108 preferably includes a decimation technique selector 196 for selecting a technique for decimation of a window.
- SDA apparatus 108 can be configured such that settings of physiological signal selector 118 and type of perturbation selector 118 determines: the settings of spectral transform selector 188, window duration selector 190, window aperture 18 selector 192, number of data points selector 194 and decimation technique selector 196.
- an operator selects an appropriate sensor 102, in this case an ECG recorder, for detecting the heart rate of a subject.
- the operator employs the above-mentioned selectors in the following fashion.
- the operator employs physiological signal selector 118 for selecting the type of physiological signal to be analyzed and perturbation selector 120 for selecting the type of perturbation to be applied to a subject under investigation. These selections can cause connection of an R wave detector if required and the setting of SWTFA processor 104 as described hereinabove.
- the operator employs frequency selection apparatus 122 to determine the frequencies under investigation by assigning values to registers 124, 126 and 128.
- SWTFA processor 104 is realized as Wavelet processor 106
- the operator can employ prototype function selector 174, scale parameters selector 176 and shift parameters selector 178 for setting the prototype function, the scale parameters and the shift parameters of Wavelet processor 106, respectively.
- SWTFA processor 104 is realized as SDA processor 108
- the operator employs spectral transform selector 188, window duration selector 190, window aperture selector 192, number of data points selector 194 and decimation technique selector 196 to determine the settings of SDA apparatus 108.
- Apparatus 100 analyzes the physiological signal in the following manner.
- Window generator 110 generates a window toward the onset of the pick-up of the physiological signal for the first frequency under investigation according to the selection of the operator.
- Power spectrum determination apparatus 112 determines the power spectrum of the frequency within the window and provides the output to both display driver 154 and metrics processor 168.
- SWTFA processor 104 analyzes the window for other frequencies under investigation according to the selection of the operator such that apparatus 100 provides a real time, time dependent, power spectrum analysis of the physiological signal. It should be noted as described hereinabove that the size of the windows varies as a function of the frequency under investigation.
- SWTFA processor 104 After determining the power spectrum within the window for each frequency under investigation, SWTFA processor 104 repeats the method for the second window deployed forward along the physiological signal according to the time resolution and frequency resolution set by the operator for the next frequency and so on. Alternatively, SWTFA processor 104 can process all the time signal for each frequency under investigation.
- window generator 180 generates a first window starting at the onset of the pick-up of the physiological signal for the first frequency under investigation according to the selection of the operator, decimation apparatus 182 decimates the data points in the window to provide the predetermined number of data points, spectrum transform apparatus 184 determines the power spectrum of the frequency during the first window and provides the output to window correction apparatus 186 for correction of the power spectrum.
- apparatus 100 provides the following displays and metrics after the time dependent power spectrum analysis of the physiological signal shown in Figure 2.
- display driver 154 can provide an oscilloscope type time dependent LF power graph 198 according to input received from timing selection apparatus 122 and frequency selection apparatus 134.
- time dependent LF power graph 198 is provided for the LF power integral over the range of from about 0.04 Hz to about 0J2 Hz.
- display driver 154 can provide an oscilloscope type time dependent HF power graph 200 according to input received from timing selection apparatus 122 and frequency selection apparatus 134.
- 5 time dependent HF power graph 200 is provided for the HF power spectrum integral over the range of from about 0.24 Hz to about 0.6 Hz.
- display driver 154 can provide an oscilloscope type graph 202 of the sympatho-vagal balance LF/HF as shown in Figure 5c.
- display driver 154 can display a 2D time dependent power spectrum contour map
- display driver 154 can provide 3D time dependent power spectrum graph 160 as shown in Figure 1. It should be noted that 2D time dependent
- 15 power spectrum contour map 204 is in fact a top view of 3D time dependent power spectrum graph 160.
- apparatus 100 provides information regarding the heart rate of the subject as induced by the functioning of the autonomic nervous system due to the change of posture
- HF power graph 200 depicts that a sudden attenuation in HF power at the time of perturbation corresponding to the fast response of the parasympathetic nervous system.
- LF power spectrum graph 198 depicts that there is a strengthening in the LF power after perturbation corresponding to the slower response of
- HF power spectrum graph 200 which reflects only the functioning of the parasympathetic nervous system, depicts that HF power is attenuated after the perturbation.
- LF/HF sympatho-vagal balance ratio graph 202 depicts that the contribution of LF power is greater after the perturbation confirming the known functioning
- apparatus 100 provides time dependent evaluation of the functioning of the ANS which will be useful in the clinical interpretation of a wide range of clinical conditions including, autonomic changes relative to fainting spells such as vasovagal syncope, tilt test, autonomic failure, autonomic imbalance, diabetic neuropathy, cardiac ischemic changes, effects of drugs interfering with autonomic or ischemic changes, angioplasty effects on autonomic control, early detection of hypertension.
- apparatus 100 can be used for all kinds of autonomic tests such as: hand grip, cold pressor test, vagal maneuvers such as Oculocardiac Reflex or Diving Response, valsalva maneuver and the like. It can also be appreciated that apparatus 100 can provide time dependent power spectrum analysis of a wide range of other physiological signals in a similar fashion.
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Veterinary Medicine (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Physiology (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Cardiology (AREA)
- Public Health (AREA)
- Physics & Mathematics (AREA)
- Neurology (AREA)
- Psychiatry (AREA)
- Signal Processing (AREA)
- Child & Adolescent Psychology (AREA)
- Developmental Disabilities (AREA)
- Hospice & Palliative Care (AREA)
- Neurosurgery (AREA)
- Psychology (AREA)
- Social Psychology (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
Description
Claims
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
IL11097394 | 1994-09-14 | ||
IL11097394A IL110973A (en) | 1994-09-14 | 1994-09-14 | Apparatus and method for time dependent power spectrum analysis of physiological signals |
PCT/US1995/011686 WO1996008992A2 (en) | 1994-09-14 | 1995-09-13 | Apparatus and method for time dependent power spectrum analysis of physiological signals |
Publications (2)
Publication Number | Publication Date |
---|---|
EP0869734A2 EP0869734A2 (en) | 1998-10-14 |
EP0869734A4 true EP0869734A4 (en) | 1998-10-14 |
Family
ID=11066554
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP95934981A Withdrawn EP0869734A2 (en) | 1994-09-14 | 1995-09-13 | Apparatus and method for time dependent power spectrum analysis of physiological signals |
Country Status (5)
Country | Link |
---|---|
EP (1) | EP0869734A2 (en) |
JP (1) | JPH11511036A (en) |
AU (1) | AU3717495A (en) |
IL (1) | IL110973A (en) |
WO (1) | WO1996008992A2 (en) |
Families Citing this family (21)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
GB9624280D0 (en) | 1996-11-22 | 1997-01-08 | Univ Glasgow | Apparatus and method for measuring cardiac vagal tone |
AUPO616697A0 (en) * | 1997-04-11 | 1997-05-08 | Heartlink Pty Ltd | Method for diagnosing psychiatric disorders |
US5830148A (en) * | 1997-06-03 | 1998-11-03 | Colin Corporation | System and method for evaluating the autonomic nervous system of a living subject |
US6358201B1 (en) * | 1999-03-02 | 2002-03-19 | Doc L. Childre | Method and apparatus for facilitating physiological coherence and autonomic balance |
AU4422800A (en) * | 1999-05-01 | 2001-11-07 | Court Of Napier University, The | Method of analysis of medical signals |
US6393316B1 (en) * | 1999-05-12 | 2002-05-21 | Medtronic, Inc. | Method and apparatus for detection and treatment of cardiac arrhythmias |
JP3783491B2 (en) * | 1999-10-21 | 2006-06-07 | 花王株式会社 | Skin condition evaluation method and apparatus |
EP1399056B1 (en) * | 2001-06-22 | 2009-03-04 | Nellcor Puritan Bennett Ireland | Wavelet-based analysis of pulse oximetry signals |
GB0131024D0 (en) * | 2001-12-28 | 2002-02-13 | Cardiodigital Ltd | Analysis of acoustic medical signals |
KR100580618B1 (en) | 2002-01-23 | 2006-05-16 | 삼성전자주식회사 | Apparatus and method for recognizing user emotional status using short-time monitoring of physiological signals |
US8295567B2 (en) * | 2008-06-30 | 2012-10-23 | Nellcor Puritan Bennett Ireland | Systems and methods for ridge selection in scalograms of signals |
CA2771856A1 (en) | 2009-09-24 | 2011-03-31 | Nellcor Puritan Bennett Llc | Determination of a physiological parameter |
US8923945B2 (en) | 2009-09-24 | 2014-12-30 | Covidien Lp | Determination of a physiological parameter |
JP5467268B2 (en) * | 2010-03-18 | 2014-04-09 | 学校法人早稲田大学 | Involuntary movement suppression system, movement recognition apparatus, and movement recognition apparatus program |
US8870783B2 (en) | 2011-11-30 | 2014-10-28 | Covidien Lp | Pulse rate determination using Gaussian kernel smoothing of multiple inter-fiducial pulse periods |
JP6045100B2 (en) * | 2012-10-17 | 2016-12-14 | オメガウェーブ株式会社 | Blood flow measurement device |
JP6316063B2 (en) * | 2014-03-31 | 2018-04-25 | 学校法人慶應義塾 | Information processing apparatus, information processing system, information processing method, and program |
CN108135548A (en) | 2015-06-15 | 2018-06-08 | Medibio有限公司 | For monitoring the method and system of pressure state |
CN108366763A (en) | 2015-06-15 | 2018-08-03 | Medibio有限公司 | Method and system for assessing the state of mind |
KR102436729B1 (en) * | 2015-07-27 | 2022-08-26 | 삼성전자주식회사 | Bio-signal processing appartus and bio-signal processing method |
JP6779518B2 (en) * | 2016-09-30 | 2020-11-04 | 学校法人慶應義塾 | Biosignal detection system, biosignal detection method |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4777960A (en) * | 1986-08-18 | 1988-10-18 | Massachusetts Institute Of Technology | Method and apparatus for the assessment of autonomic response by broad-band excitation |
US4979110A (en) * | 1988-09-22 | 1990-12-18 | Massachusetts Institute Of Technology | Characterizing the statistical properties of a biological signal |
US5046504A (en) * | 1989-02-01 | 1991-09-10 | Corazonix Corporation | Method and apparatus for analyzing and interpreting electrocardiograms using spectro-temporal mapping |
-
1994
- 1994-09-14 IL IL11097394A patent/IL110973A/en not_active IP Right Cessation
-
1995
- 1995-09-13 JP JP8510976A patent/JPH11511036A/en not_active Withdrawn
- 1995-09-13 EP EP95934981A patent/EP0869734A2/en not_active Withdrawn
- 1995-09-13 AU AU37174/95A patent/AU3717495A/en not_active Abandoned
- 1995-09-13 WO PCT/US1995/011686 patent/WO1996008992A2/en not_active Application Discontinuation
Non-Patent Citations (1)
Title |
---|
No further relevant documents disclosed * |
Also Published As
Publication number | Publication date |
---|---|
IL110973A0 (en) | 1994-11-28 |
AU3717495A (en) | 1996-04-09 |
IL110973A (en) | 2001-12-23 |
JPH11511036A (en) | 1999-09-28 |
EP0869734A2 (en) | 1998-10-14 |
WO1996008992A3 (en) | 1996-06-13 |
WO1996008992A2 (en) | 1996-03-28 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US5797840A (en) | Apparatus and method for time dependent power spectrum analysis of physiological signals | |
EP0869734A4 (en) | ||
US7079888B2 (en) | Method and apparatus for monitoring the autonomic nervous system using non-stationary spectral analysis of heart rate and respiratory activity | |
Aysin et al. | Effect of respiration in heart rate variability (HRV) analysis | |
Mulder | Measurement and analysis methods of heart rate and respiration for use in applied environments | |
US5419338A (en) | Autonomic nervous system testing by bi-variate spectral analysis of heart period and QT interval variability | |
Baselli et al. | Heart rate variability signal processing: a quantitative approach as an aid to diagnosis in cardiovascular pathologies | |
Ruha et al. | A real-time microprocessor QRS detector system with a 1-ms timing accuracy for the measurement of ambulatory HRV | |
US8668649B2 (en) | System for cardiac status determination | |
EP1273265B1 (en) | Monitoring a condition of a patient under anaesthesia or sedation | |
US20030093002A1 (en) | Function indicator for autonomic nervous system based on phonocardiogram | |
US20080214902A1 (en) | Apparatus and Method for Objectively Determining Human Response to Media | |
US6269263B1 (en) | Method for estimating heart rate variability and apparatus for embodying estimation | |
JPH0257933B2 (en) | ||
US20150374285A1 (en) | Method and apparatus for measuring anesthetic depth | |
US8352020B2 (en) | Method for processing a series of cardiac rhythm signals (RR) and the use thereof for analysing a cardiac rhythm variability, in particular for assessing a patient's pain or stress | |
US20180263567A1 (en) | Method and device for quantifying a respiratory sinus arrhythmia and use of said type of method or said type of device | |
US10349896B2 (en) | Epsilon-tube filter for blunt noise removal | |
JPH07231880A (en) | Stress evaluation method and device therefor | |
CN106539580B (en) | Continuous monitoring method for dynamic change of autonomic nervous system | |
WO2017069870A1 (en) | Method for assessment of cerebrovascular regulation | |
JPH07313494A (en) | Stress measuring system | |
JP3250474B2 (en) | Mental stress judgment device | |
Pinhas et al. | Bicoherence analysis of new cardiovascular spectral components observed in heart-transplant patients: statistical approach for bicoherence thresholding | |
JPH10165380A (en) | Fatigue judging method, fatigue judging device, and rationalization system of work by use of this device |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PUAI | Public reference made under article 153(3) epc to a published international application that has entered the european phase |
Free format text: ORIGINAL CODE: 0009012 |
|
17P | Request for examination filed |
Effective date: 19970306 |
|
A4 | Supplementary search report drawn up and despatched |
Effective date: 19980505 |
|
AK | Designated contracting states |
Kind code of ref document: A4 Designated state(s): DE FR GB Kind code of ref document: A2 Designated state(s): DE FR GB |
|
17Q | First examination report despatched |
Effective date: 20020527 |
|
GRAH | Despatch of communication of intention to grant a patent |
Free format text: ORIGINAL CODE: EPIDOS IGRA |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: THE APPLICATION IS DEEMED TO BE WITHDRAWN |
|
18D | Application deemed to be withdrawn |
Effective date: 20030611 |