WO2014101913A1 - Method and device for quantifying a respiratory sinus arrhythmia and use of said type of method or said type of device - Google Patents
Method and device for quantifying a respiratory sinus arrhythmia and use of said type of method or said type of device Download PDFInfo
- Publication number
- WO2014101913A1 WO2014101913A1 PCT/DE2013/000820 DE2013000820W WO2014101913A1 WO 2014101913 A1 WO2014101913 A1 WO 2014101913A1 DE 2013000820 W DE2013000820 W DE 2013000820W WO 2014101913 A1 WO2014101913 A1 WO 2014101913A1
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- WO
- WIPO (PCT)
- Prior art keywords
- heart rate
- sinus arrhythmia
- respiratory sinus
- subcurves
- curves
- Prior art date
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Classifications
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- 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
- A61B5/486—Bio-feedback
-
- 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
- A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
-
- 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
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
- A61B5/165—Evaluating the state of mind, e.g. depression, anxiety
Definitions
- the invention relates to a method and a device for quantifying a respiratory sinus arrhythmia and to the use of such a method or device.
- Heart rate variability is the term used to describe heart rate fluctuations from heartbeat to heartbeat.
- the HRV can be quantified by suitable mathematical methods, e.g.
- the heart rate variability is an expression of the continuous adjustment of the heart rate to changing requirements in the human organism and therefore allows conclusions on the neurovegetative regulatory ability of humans, in particular the function of the parasympathetic nervous system with its main nerve (vagus nerve) attributed a particular importance (Clin Sei (Lond.) 2012 Apr; 122 (7): 323-8 You may need the vagus nerve to understand pathophysiology and treat diseases; De Couck M, Mravec B, Gidron Y).
- This property of the parasympathetic nervous system is used to differentiate between the activity of the sympathetic and the parasympathetic nervous system by subjecting the heart rate profile to spectral analysis, eg by means of a Fast Fourier Transformation (FFT) (see FIG. 1b).
- FFT Fast Fourier Transformation
- FIG. 2a shows a typical heart rate curve in humans
- FIG. 2b shows the associated spectral analysis.
- the area of the spectral analysis designated as "HF” (high frequency), designates a control range of the heart rate, which is exclusively due to the influence of the parasympathetic nervous system (0.15 Hz to 0.4 Hz) .
- the "JLF” low frequency
- the area identified comprises a frequency range in which the sympathetic and parasympathetic nerves overlap (0.04 to 0.15 Hz).
- the frequency range referred to as "VLF” involves very slow acting influences such as thermoregulation Because of the required long recording time, the "VLF” range does not matter in the short term HRV analysis and may be neglected in the further consideration.
- Another way to determine the parasympathetic activity is to quantify respiratory sinus arrhythmia.
- respiratory sinus arrhythmia the synchronization of the rhythms of respiration, blood pressure and heart rate leads to an approximately sinusoidal oscillation of the heart rate, which has a characteristic pattern in spectral analysis and is characterized by a large peak above the respiratory rate (FIG. 1b).
- the peak of the respiratory sinus arrhythmia is almost always in the LF (low frequency) range of the spectral analysis, but is still an expression of parasympathetic activity and not to be confused with sympathetic activity by the absence of a characteristic peak and a broad distribution of frequencies occurring in the LF range is characterized (see Figure 2b).
- DE 10 2006 039 957 A1 describes a spectral-analytical method for determining the respiratory sinus arrhythmia, which is based on a ratio of the integral component of two frequency ranges similar to the LF / HF quotient.
- EP 1 156 851 B1 or DE 600 32 581 T2 describes a spectral-analytical method for determining the respiratory sinus arrhythmia, in which the frequency of the peak is determined by means of a peak detection and subsequently an integral which comprises the peak, is set in relation to two integrals, each comprising an area below and above the peak frequency.
- a practical implementation of the methods mentioned in the two patents are, for example, devices for carrying out the so-called HRV biofeedback process.
- the respiratory sinus arrhythmia of the user is measured in real time and visualized by different colored LEDs.
- biofeedback effect the user can now specifically train his respiratory sinus arrhythmia and thus the influence of the health-promoting parasympathetic nervous system.
- DE 10 2008 030 956 AI shows an embodiment of such a device.
- the determination of the respiratory sinus arrhythmia by means of the spectral analysis of the prior art is due to the required mathematical methods such as a Fourier analysis, as disclosed for example in US 2007/0208266 AI, an FFT analysis, as in particular, for example EP 1 156 851 B1, WO 2008/028912 A2 of US Pat. No. 6,358,201, US Pat. No. 7,163,512 Bl, US Pat. No. 7,462,151 B2, US Pat. No. 8,066,637 B2 or US Pat US 8,123,696 B2 is disclosed, or a wavelet analysis before a high computing power, as it is quite common in the PC field today.
- US 2006/0074333 AI discloses complex computational steps to infer from biometric parameters that are measured to the state of the nervous system. In the realization of simple battery powered
- the standard deviation can be used as a statement for a variance of the corresponding signal with relatively little computation effort in the time domain (Proceedings of the 17th IEEE Symposium on Computer-Based Medical Systems (CBMS'04) 2004, pages 1 to 4; Raghavan V, Vikas Lath, Ashish Patil Sreejit Pillai), which in itself is not very meaningful.
- the noise is greatly reduced. This is also called coherence between heart rate and respiration. For this reason, the magnitude of the noise, in addition to the amplitude of the respiratory sinus arrhythmia, provides valuable information about parasympathetic activity. Due to the resonance characteristics of the physiological reflex arcs, the respiratory sinus arrhythmia is more pronounced in slow breathing with a maximum at about 0.1 Hz. The higher the respiratory rate, the lower its amplitude becomes. The determination of respiratory sinus arrhythmia is therefore usually performed at slower breathing. For this reason, it is usually sufficient to use the frequency components which occur above the respiratory frequency as the noise component. It is now possible to produce such a signal-to-noise ratio without spectral analysis in a simple manner:
- a respiratory sinus arrhythmia corresponds to the occurrence of a sinusoidal oscillation of a specific frequency in the heart rate curve, the frequency of the sinusoidal oscillation coinciding with the respiratory rate.
- the amplitude of the sinusoidal oscillation corresponds to the area swept by the sinusoidal curve, see FIG. 3.
- the respiratory sinus arrhythmia can be set by the use of a digital bandpass or lowpass filter Separate from the interfering frequency components ( Figure 4b) and determine the area under the curve.
- a digital high-pass filter on the heart rate curve for example, the noise component can now also be separated and likewise the area under the curve can be determined (FIG. 4c).
- the respiratory sinus arrhythmia can then be quantified as the ratio of the areas of the filtered curves: with passband as the area under the bandpass-filtered heart rate curve, where the frequency range that passes through the filter as undamped as possible should include the physiological range of the respiratory sinus arrhythmia.
- Possible frequency ranges would be, for example, the LF range known from the prior art 0.04 to 0.15 Hz.
- a frequency range could be selected which includes a physiological respiratory rate, eg between 5 and 10 breaths per minute, which corresponds to a frequency range of 0.083 to 0.166 Hz.
- a signal-to-noise ratio can be achieved which quantifies the magnitude of the respiratory sinus arrhythmia with sufficient accuracy. Due to the simple realization of digital but also analogue filters by means of fewer additions and multiplications, a complex spectral analysis can now be dispensed with, as a result of which smaller, more energy-efficient microprocessors can be used in devices for the determination of respiratory sinus arrhythmia.
- the heart rate curve is preferably recorded as a heartbeat rate over time or as a number of heartbeats per unit of time over time.
- a method for quantifying the respiratory sinus arrhythmia can be characterized in that a heart rate curve is separated by at least two filters in two different heart rate subcurves, wherein at least one of these heart rate sub-curves affects the frequency band of the respiratory sinus arrhythmia - or at least partially cuts or completely and by analyzing the two heart rate subcultures the respiratory sinus arrhythmia is quantified.
- a filter arrangement can be implemented on the one hand even by analog electronic modules and on the other hand by the simplest software engineering measures and allows a quick analysis of the heart rate curve.
- a range between 0.06 heart and 0.166 heart which corresponds to approximately 4 to 10 breaths per minute, is preferably selected or narrowed - the latter at the risk of breathing frequencies of individuals, such as athletes , no longer applicable.
- a device for quantifying the respiratory sinus arrhythmia is advantageous, which is characterized by measuring means for measuring a heart rate curve, by at least two filters for separating the heart rate curve into two different heart rate subcurves, by at least one analyzer for analyzing juxtaposition of the two heart rate subcurves and by at least one output device for Output of the result of the analyzer distinguished.
- the other of the heart rate sub-curves does not include the respiratory sinus arrhythmia frequency band. In this way structurally very easy separation and thus good signal sharpness can be achieved.
- the areas A and B are determined under the two heart rate sub-curves and set in relation to each other, wherein the ratio G quantifies the respiratory sinus arrhythmia.
- a weighting for example via a factor c, d or an exponent p, q, may be possible.
- Such weighting may be readily experimentally chosen and, for example, tuned to output a binary signal G, such as "good” and "bad", as quantification, if the corresponding factors c, d and exponents p, q are chosen such that that a sufficiently significant transition is available at an output of a corresponding device.
- the heart rate curve can be separated by more than two filters into a corresponding number of different heart rate subcurves.
- the heart rate sub-curves which affect the frequency band of the respiratory sinus arrhythmia are first evaluated and the rating A summarized and the heart rate sub-curves which do not contain or affect the frequency band of the respiratory sinus arrhythmia are evaluated and the rating evaluated B summarized. Subsequently, the summaries for the quantification G of the respiratory sinus arrhythmia can be analyzed.
- the areas under the two heart rate subcurves are preferably determined and added to the summary, wherein in particular the combined heart rate subcurves can be set in relation to one another for analysis. This ratio can then be used to quantify G respiratory sinus arrhythmia.
- At least one of the scores is weighted prior to combining the respective heart rate subcurves.
- the significance of the output signal can be specifically adapted to the respective requirements.
- At least one of the summaries may be weighted prior to analysis. This can also be done via a factor or the like. Preferably, this is done via an exponent.
- the analysis device may have at least one integrator for determining the area under a heart rate sub-curve, whereby a corresponding area calculation can be carried out quickly and easily.
- an integrator is provided per heart rate sub-curve.
- a corresponding analysis device can have at least one amplifier for amplifying one of the two heart rate subcurves, wherein in the present context the term "amplification" includes a multiplication by a factor which can certainly also take place with a value below 1, which leads to a corresponding reduction Likewise, the amplifier may have an exponential or logarithmic or a multiplying characteristic curve, Preferably an amplifier is provided for each heart rate component curve.
- the analysis means may comprise at least one adder for adding heart rate subcurves modified by the analyzer, for example heart rate subcircuits modified by the enhancers or integrators.
- the analyzing means may have at least one divider for setting heart rate part curves modified by the analyzing means, whereby a corresponding analysis can be performed quickly and precisely.
- the analysis device can cumulatively or alternatively also comprise a multiplier, possibly a plurality of multipliers with different characteristic curves, in particular in order, for example, to weight individual or groups of high-frequency partial curves with a factor or exponent.
- one of the filters can also be a digital filter, so that the overall arrangement can also be implemented in digital form.
- the other components of the analysis device such as the integrators, amplifiers, multipliers or adders, are also configured correspondingly digital.
- the corresponding method or the device is particularly suitable for biofeedback by taking a measurement and evaluation in real time and displaying the result of the evaluation in real time.
- a corresponding display can be made for example by "good” or "bad” but also by a finer resolution.
- FIG. 1 shows an example of a respiratory sinus arrhythmia with the individual recorded data (a) and the resulting spectral analysis (b);
- FIG. 2 shows a ten-minute recording of the heart rate curve (a) and the associated spectral analysis (b);
- FIG. 3 shows an exemplary heart rate variability only with consideration of
- FIG. 4 shows an exemplary heart rate variability taking into account further
- Figure 5 shows an exemplary construction of the filter and analysis device.
- a heart rate curve (FIG. 1 a) via an input 1 via three filters 11, 12, 13 on the one hand frequencies below the respiratory sinus arrhythmia via the filter 11, which very low frequencies (very low frequencies VLF ) as well as above the respiratory sinus arrhythmia via the filter 13, which filters high frequencies (high frequencies HF), from the frequency band of respiratory sinus arrhythmia between 0.06 heart and 0.166 heart (low frequencies LF) passing through the filter 12 into one third branch to be filtered out, separated.
- Integrators 21, 22, 23 are used to integrate the areas under the respective variations, as shown by way of example in FIGS. 4b and 4c and then weighted via suitable amplifiers 31, 32, 33.
- the amplifiers 31, 33 are attenuating amplifiers with a factor below one, while the amplifier 32, which amplifies the respiratory sinus arrhythmia, sets an over unity factor to the integrated values.
- the values correspondingly reduced via the amplifiers 31, 33 are added up in an adder 41.
- further adders may be provided, in particular if a plurality of filters are also provided in the area of the respiratory sinus arrhythmia, the outputs of which are optionally integrated separately and weighted with different factors.
- the accumulated values from the adder 41, or the amplified values from the amplifier 32 are supplied to an exponential weighting in the multipliers 51, 52, in order subsequently to divide them in a divisor 61 according to the above-mentioned formula. From this follows then a corresponding output signal at an output 2, which represents a measure of the respiratory sinus arrhythmia.
Abstract
Description
Claims
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
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DE112013006246.1T DE112013006246A5 (en) | 2012-12-27 | 2013-12-27 | Method and device for quantifying the respiratory sinus arrhythmia and use of such a method or device |
Applications Claiming Priority (4)
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US201261746168P | 2012-12-27 | 2012-12-27 | |
DE102012025183.1 | 2012-12-27 | ||
DE102012025183.1A DE102012025183A1 (en) | 2012-12-27 | 2012-12-27 | Method and device for quantifying the respiratory sinus arrhythmia and use of such a method or device |
US61/746,168 | 2012-12-27 |
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WO2014101913A1 true WO2014101913A1 (en) | 2014-07-03 |
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PCT/DE2013/000820 WO2014101913A1 (en) | 2012-12-27 | 2013-12-27 | Method and device for quantifying a respiratory sinus arrhythmia and use of said type of method or said type of device |
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WO (1) | WO2014101913A1 (en) |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102015116044A1 (en) | 2015-09-23 | 2017-03-23 | Biosign Medical Ug (Haftungsbegrenzt) | Method and device for quantifying a respiratory sinus arrhythmia and use of such a method or device [ |
CN111698940A (en) * | 2018-01-26 | 2020-09-22 | 伯斯有限公司 | Measuring respiration with an in-the-ear accelerometer |
DE102021113372B3 (en) | 2021-05-21 | 2022-08-04 | Dr. Willmar Schwabe Gmbh & Co. Kg | Analysis method, analysis device and executable computer program for the medical-technical analysis of a heart rate curve measured on a body |
DE102022114277A1 (en) | 2022-06-07 | 2023-12-07 | BioSign Medical UG (haftungsbeschränkt) | Method, device and executable computer program for the individualized quantification of a respiratory sinus arrhythmia |
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2012
- 2012-12-27 DE DE102012025183.1A patent/DE102012025183A1/en not_active Ceased
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2013
- 2013-12-27 DE DE112013006246.1T patent/DE112013006246A5/en not_active Withdrawn
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Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102015116044A1 (en) | 2015-09-23 | 2017-03-23 | Biosign Medical Ug (Haftungsbegrenzt) | Method and device for quantifying a respiratory sinus arrhythmia and use of such a method or device [ |
WO2017050321A1 (en) | 2015-09-23 | 2017-03-30 | Biosign Medical Ug | Method and device for quantifying a respiratory sinus arrhythmia and use of said type of method or said type of device |
US10980489B2 (en) | 2015-09-23 | 2021-04-20 | Biosign Medical Ug | Method and device for quantifying a respiratory sinus arrhythmia and use of said type of method or said type of device |
CN111698940A (en) * | 2018-01-26 | 2020-09-22 | 伯斯有限公司 | Measuring respiration with an in-the-ear accelerometer |
CN111698940B (en) * | 2018-01-26 | 2022-12-06 | 伯斯有限公司 | Measuring respiration with an in-the-ear accelerometer |
DE102021113372B3 (en) | 2021-05-21 | 2022-08-04 | Dr. Willmar Schwabe Gmbh & Co. Kg | Analysis method, analysis device and executable computer program for the medical-technical analysis of a heart rate curve measured on a body |
WO2022242789A1 (en) | 2021-05-21 | 2022-11-24 | Dr. Willmar Schwabe Gmbh & Co. Kg | Analysis method, analysis device and executable computer program for the medical analysis of a heart rate trace measured on a body |
DE102022114277A1 (en) | 2022-06-07 | 2023-12-07 | BioSign Medical UG (haftungsbeschränkt) | Method, device and executable computer program for the individualized quantification of a respiratory sinus arrhythmia |
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DE102012025183A1 (en) | 2014-07-03 |
DE112013006246A5 (en) | 2015-10-08 |
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