Patent Application
20050143668
This application claims the priority benefit of Taiwan application serial no. 92136982, filed on Dec. 26, 2003.
1. Field of Invention
The present invention relates to an automatic diagnosing method and an device thereof. More particularly, the present invention relates to an automatic diagnosing method for the autonomic nervous system and a device thereof, wherein a physiological signal is collected for an undisturbed period and a diagnosis description statement is outputted after the signal is analyzed.
2. Description of Related Art
The current technological advancements can provide various means for detecting and diagnosing the function of each organ in the body. However, the previous developments only focus on the accuracy of signal detection. Therefore, many invasive tools and techniques were used. For example, cardiac catheterization requires the insertion of a catheter through the artery to the heart. The procedure is not only dangerous, but also is very painful for the patient.
A non-invasive tool and technique, on the other hand, use painless and harmless approaches to detect and diagnosis the functions of the organs in the body. Since the technique and the tool are noninvasive, the accuracy of the physiological signals is usually not acceptable. Therefore, in the past, the accuracy and the practice of the noninvasive approaches are not desirable.
In recent years, Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (Heart Rate Variability: Standards of Measurement, Physiological Interpretation and Clinical Use; Circulation 93:1043-1065; 1996) and Malliani, et. al. (Cardiovascular Neural Regulation Explored in the Frequency Domain, Circulation 84:482-492; 1991) discover that besides being affected by the breathing frequency, the heart rate variability (HRV) also reflects the activity of the autonomic nervous system (ANS). An adult at rest, the heartbeat is about 60-90 beats per minute. The heart rate variability refers to the beat-to-beat alterations in the heart rate. It is a measure of the beat-to-beat, regular or irregular variations with each breath under a precordial state. Since the variation is too small, the traditional analytic methods can not provide an accurate analysis. Not only until the recent years, signal detection and treatment technique are greatly improved. Researchers have discovered that, based on frequency analysis, HRV can be characterized into two main components: the high frequency (HF) component and the low frequency (LF) component, and the low frequency component is further divided into a low frequency component and a very low frequency component. The high frequency component is synchronous with respiration and occurs every 3 seconds, whereas the exact origin of the low frequency component is not known. Investigators suspect that the low frequency component is related to vessel activity or baroreflex, and occurs every 10 seconds. Currently, physiologist and cardiologists agree that the high frequency component or the total power reflects the activity of the parasympathetic nervous system and the low frequency component is jointly contributed by both vagal and sympathetic nerves, while the ratio LF/HF is considered to mirror the activity of the sympathetic nervous system.
Besides serving as a functional indicator of the autonomic nervous system, HRV can provide meaningful reflection of many physiological conditions. For example, a recent study by Framingham further indicates that when the HRV of an elderly is lowered by one standard deviation, his/her chance of dying is about 1.7 times higher than a normal individual.
In the current non-invasive diagnosing techniques, the various parameters obtained after analysis are provided to the physician. Normally, the physician will inform the patient the result after further analyzing the parameters. However, these parameters are not meaningful to an ordinary individual who is not a medical practitioner. Therefore, the current research is focused on designing an automatic diagnosing device, wherein after the parameters are obtained and analyzed, a comprehensible description statement of the diagnosis is provided.
Accordingly, the present invention provides an automatic diagnosing method for the autonomic nervous system (ANS), wherein a non-invasive approach is used to provide a preliminary diagnosis and recommendation on the function of the ANS. As a result, the user can obtain information regarding the activity of the autonomic nervous system and the related care.
The present invention provides an automatic diagnosing method for the autonomic nervous system, wherein an examination report and suggestion are provided for an ordinary user after the user is subjected to an easy and non-invasive examination on the activity and function of the ANS.
The present invention provides an automatic diagnosing method for the autonomic nervous system, wherein the method includes after detecting a heart beat signal of the subject, the heart beat signal is converted from the time domain to a frequency domain to obtain a plurality of the heart rate variability (HRV) parameters. A natural logarithm calculation is performed on these HRV parameters. Artificial intelligence is used to calculate and to optimize these parameters with a plurality of the corresponding reference values in the database, and a plurality of standard deviations is output. A diagnosis description statement that matches the basic information of the subject and these standard deviations is attained from a look-up table. Subsequently, an examination report, which includes the HRV parameters, the description statement of the diagnosis, the basic information and the standard deviations, is output.
In accordance to an embodiment of the present invention, the HRV parameters include the R-R intervals (peak intervals), the high frequency (HF) component, the low frequency (LF) component, and the ratio of low frequency to high frequency (LF/HF).
In accordance to the embodiment of the present invention, the above diagnosis description statement includes the standards of physiological condition, the physiological predisposition of the subject, the function of the autonomic nervous system, the age curve, the heart rate and suggestions.
In accordance to the embodiment of the present invention, the above examination report further includes the HRV parameters of the very low frequency component, the power spectrum density (PSD) and the total power.
The present invention further provides an automatic diagnosing device for the autonomic nervous system, wherein the diagnosis is achieved with a noninvasive approach. The automatic diagnosing device includes a sensing device, a computing device and an output device. The above sensing device includes a plurality of electrodes and a plurality of signal receiving leads. The electrodes are adhered to, for example, the skin surface of the subject's arm, to detect and output the heart beat signals. The computing device includes a database, wherein after receiving the heart beat signals, the signals are amplified, filtered, digitized and transformed to obtain a plurality of HRV parameters. Further, after the HRV parameters are calculated, compared and analyzed, these parameters are matched with a corresponding diagnosis description statement in the lookup table in the database. The aforementioned output device serves to receive and output an examination report, which incorporates the diagnosis description statement and the HRV parameters.
In accordance to the embodiment of the present invention, the above transformation includes fast Fourier transform.
In accordance to the embodiment of the present invention, the output device includes at least, for example, a monitor, a printer, a compact disk writer, and/or an internet system.
In accordance to the embodiment of the present invention, the above computing device includes at least an amplifier, a filter, and an analog/digital converter.
In accordance to an embodiment of the present invention, the above computing device includes a computer with a digital signal processing capability, which is used for frequency domain analysis, time domain analysis and nonlinear analysis.
In accordance to the present invention, a noninvasive automatic diagnosing device is used. The subject can be examined under a comfortable and safe environment. Further, the user can fully comprehend his/her own physiological condition even without an explanation from a medical practitioner. Moreover, the present invention can provide a preliminary diagnosis for the patient. In addition, a medical practitioner can provide a diagnosis and a treatment, which is directed to a specific part of the patient according to the examination report to rapidly and accurately eliminate the patient's illness.
It is to be understood that both the foregoing general description and the following detailed description are exemplary, and are intended to provide further explanation of the invention as claimed.
The accompanying drawings are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.
The automatic diagnosing method and device thereof of the present invention is based on the “physical diagnosis technique”. The “physical diagnosis technique” refers to a method, in which instruments are used to collect blood pressure, heart rate, etc., types of physiological signals to perform medical diagnosis.
Referring to
In this embodiment of the present invention, the sensing device 110 comprises a plurality of electrodes 102, 104, 106 and a plurality of signal receiving leads 108. These electrodes 102, 104, 106 are adhered to a subject, for example, to the skin surface of an arm of the subject, to detect and output the heart beat signal. A person skilled in the art can easily realize that these signal receiving leads 108 are connected to the stud electrodes, wherein one electrode is adhered to the front end of the left hand, another electrode is adhered to the back end of the left hand, while another electrode is adhered to front end of the right hand (using the standard Lead I placement), for example.
The computing device 120 includes a database (not shown), wherein this database stores a multiple of organized diagnosis description statements and an inquiry lookup table. The computing device 120 collects the heart beat signal through the signal collection leads 108. The computing device also amplifies, filters, digitizes and converts the heart beat signals to a plurality of heart rate variability (HRV) parameters. A person skilled in the art readily realizes that a computing device 120 can include, but not limited to, a plurality of high pass filters, an amplifier, a low pass filter, a voltage-current converter, a comparing circuit, an optical isolator, an analog-digital converter and a RS232 input/output port, etc.
After obtaining the HRV parameters, calculation, comparison and analysis are further performed on these parameters by the computing device. Thereafter, these parameters are matched with a corresponding diagnosis description statement in the lookup table in the database in the computing device 120.
In this embodiment, the output device 130 is coupled to the computing device 120. The output device 130 serves to receive and output the test report, which incorporates the diagnosis description statement and the heart rate variability parameters. A person skilled in the art can readily realize that the output device 130 can include a monitor, a printer to displace and print the test report, or a compact disk writer to write the test report on a compact disk. In another aspect of the invention, the examination is conducted, and the output device 130 is an internet system for sending the test report to a remote terminal, for example, the doctor's computer.
In one embodiment of the invention, the computing device 120 includes a computer with a digital signal processing (DSP) capability, which can perform frequency domain analysis, time domain analysis and nonlinear analysis.
In this embodiment of the invention, the operating principle of the automatic diagnosing device 100 used for automatically diagnosing the function of the autonomic nervous system is detailed in the following.
Referring to
In accordance to the automatic diagnosing method of the present invention, the basic information of the subject is first input followed by monitoring the heart beat signal (s202) of the subject. The basic information of the subject includes, but not limited to, name, age, sex, etc.
Thereafter, the heart beat signal is transformed to obtain a plurality heart rate variability (HRV) parameters (s204), wherein the step (s204) includes using fast Fourier transform to transform the heart beat signal from the time domain to the frequency domain (s206). Parameters, such as, the peak interval (the R-R interval) (s208), the low frequency (LF) component (s210), the high frequency (HF) component (s214) and the ratio of the low frequency to high frequency (s212), etc., are obtained.
The process flow showing the transformation of the heart rate signals to obtain the plurality of HRV parameters are detailed in
The heart beat signals (s304) are digitally converted by using an analog/digital converter in the computing device. Thereafter, the computing device detects each peak in the digitized heart beat signals (s306).
In this embodiment, statistical validation of each peak is performed (s308) after detecting each peak. The computing device continues to calculate the peak intervals between the peaks, and statistically validate each peak interval of these peaks (s310). In fact, the computing device calculates the peak-to-peak distance to obtain a plurality of peak intervals (s312). After obtaining these peak intervals, the computing device further perform a statistical validation on each peak interval (s314).
The computing device then performs calculations on these peak intervals to obtain the heart rate variability parameters in the frequency domain (s316), wherein interpolation and sampling (s318) are performed on these peak intervals to obtain the heart rate variability parameters in the frequency domain (s320).
Referring again to
Thereafter, using a plurality of reference values in the database in the computing device, calculation and optimization are further performed on the 1n LF (s220), the 1n (HF) (s222), and the 1n (LF/HF) (s224), and a plurality of standard deviations (s266) is output. In other words, artificial intelligence is used to calculate and to optimize the peak intervals, the 1n LF (s220), the 1n (HF) (s222), and the 1n (LF/HF) (s224) with the reference values in the database in the computing device to obtain respectively the standard deviations (s230) of the peak interval, the 1n LF, the 1n (HF), and the 1n (LF/HF).
In this embodiment of the present invention, after obtaining the standard deviations of the peak intervals, the 1n (LF), the 1n (HF), and the 1n (LF/HF), respectively, a corresponding diagnosis description statement (s232) is selected from the look-up table according to the basic information of the subject and these standard deviations.
In step s232, the process flow for selecting the corresponding diagnosis description statement from the look-up table based on the basic information of the subject and the standard deviations obtained above is summarized in
The various functional states include the three states of low, normal and a high. Therefore, there are 3*3*3*3*3=81 combinations for the functional states of the heart rate variability parameters.
Returning to
Referring to
In one embodiment of the present invention, the automatic diagnosing method of the autonomic nervous system detects the R pulse of the electrocardiograph from the hands of the subject for example, by transmitting the signal from the electrodes to the collection leads and further to the amplifier in the computing device for amplifying the weak signals. The QRS complex pulse (as shown in
In the present embodiment, a subject will receive an examination report as shown in
As shown in
In this embodiment, the R-R interval is a distance between two R waves in an electrocardiograph (ECG), which is also defined as the peak interval in this invention. Under a normal condition, the R-R interval is about 600 to 1000 ms. After a frequency-domain analysis is performed using the fast Fourier transform (FFT), the resulting power spectrum is quantified by means of integration into standard frequency-domain parameters including low-frequency (LF 0.04-0.15 Hz) and high-frequency (HF 0.15-0.40 Hz), total power (TP) and ratio of low frequency to high frequency (LF/HF). The high frequency component or the total power reflects the activity of the parasympathetic nervous system, the low frequency component is jointly contributed by the vagal and the sympathetic nerves, while the ratio LF/HF is considered to mirror the activity of the sympathetic nervous system. LF % represents the function and activity of the sympathetic nervous system. The power spectral density (PSD) provides the basic information of how power distributes as a function of frequency, in which at least two band powers, including the low frequency power and the high frequency power, are estimated by integrating the power spectrum. Total power (TP) is defined as a total power of all measured spectrum, which is integrated over all measured spectrum from a power density spectrum. Variance (VAR) represents the statistical variation of each value of the R-R interval during the examination period. N represents noise, in which N has to be less than −1 ln (mv2) and is normally −3 ln (mv2). If N is greater than −1 ln (mv2), the noise generated in the site must be eliminated.
In this embodiment of the invention, the curve 602 indicates an average heart beat of an individual between the age of 40 to 80. Curve 604 is an age curve, wherein the higher the black dot, the younger the subject. Curve 606 is an average activity line of the sympathetic nervous system of an individual between the age of 40 to 80, wherein a higher block dot represents the individual tends to be worrisome, excited, nervous, etc. Curve 608 is an average activity line of the parasympathetic nervous system, wherein the higher the black dot represents the individual is athletic, and the subject's sleeping pattern or the digestive system is desirable.
In this embodiment of the invention, the indicator chart 610 indicates the physiological predisposition of the subject, which can be divided into two regions. If the indicator falls between the parasympathetic nervous system and the center point, the subject tends to be less nervous or worrisome, whereas as the indicator falls between the sympathetic system and the center point, the subject tends to be more nervous or worrisome.
In this embodiment, the physical state index chart 612 indicates the physiological condition of the subject, which can be categorized into over, good, fair and poor. The position of the indicator indicates the ANS condition as recited in the diagnosis description statement.
Diagram 614 illustrates the entire function activity of the autonomic nervous system, wherein the black portion represents the activity of the parasympathetic system, while the white portion represents the activity of the sympathetic system. The ratio of the black portion to the white portion is calculated based on the above HRV parameters. Referring to
In this embodiment of the present invention, this examination report can be used to evaluate the ANS function, to predict patent outcome in the intensive care unit, to verify a brain death situation, to monitor the depth of anesthesia or heart transplant rejection, or to evaluate the aging of nervous system, etc.
In accordance to the present invention, the automatic diagnosing method for the autonomic nervous system and the device thereof, a rapid diagnosis and essential guides for diagnosing an illness can be provided. Further, an ordinary individual can also self-diagnose when abnormality of the individual's health occurs to prevent a delay in the intervention of the illness.
It will be apparent to those skilled in the art that various modifications and variations can be made to the structure of the present invention without departing from the scope or spirit of the invention. In view of the foregoing, it is intended that the present invention cover modifications and variations of this invention provided they fall within the scope of the following claims and their equivalents.
| Number | Date | Country | Kind |
|---|---|---|---|
| 92136982 | Dec 2003 | TW | national |
