Classifications

• • G—PHYSICS
  • G08—SIGNALLING
  • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
  • G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
  • G08B29/18—Prevention or correction of operating errors
  • G08B29/20—Calibration, including self-calibrating arrangements
  • G08B29/24—Self-calibration, e.g. compensating for environmental drift or ageing of components
  • G08B29/26—Self-calibration, e.g. compensating for environmental drift or ageing of components by updating and storing reference thresholds

Definitions

• the invention relates to a method for the detection of an alarm state or for the detection of drifts, jumps and / or outliers of measurement signal values received via measurement data acquisition means, an alarm state being triggered when a currently received measurement signal value or a value derived from measurement values predetermined limit value or predetermined interval limits is exceeded.
• Examples of the extremely numerous applications of the method according to the invention are, in particular in the field of medicine, perioperative monitoring, monitoring vital parameters in intensive care units, sleep monitoring, CTG (cardio-tocography), and in other areas fire and smoke warning systems, acoustic monitoring systems, such as B. Baby monitor called.
• Alarm systems in intensive care monitors which typically display and analyze cardiovascular parameters (ECG, blood pressure), oxygen saturation (SpO2), gas exchange and metabolic parameters as well as EEG and EMG online, are intended to draw the attention of the attending physician or nurse to potentially life-threatening conditions for the direct monitored patients.
• ECG cardiovascular parameters
• SpO2 oxygen saturation
• gas exchange gas exchange
• metabolic parameters as well as EEG and EMG online
• a high degree of adaptability in order to avoid that too many parameters have to be preset by hand and readjusted during the treatment, and thus distract from the actual monitoring task. In particular, it should be possible to recognize several alarm situations which follow one another at a certain time interval. 4. A high degree of meaningfulness of the adjustable parameters to ensure that the alarm system can also be operated easily and without errors.
• the high false alarm rate leads to desensitization of the surveillance personnel and frequent manual alarm deactivation.
• the known alarm systems are triggered when the size to be monitored exceeds the preset upper or lower limits. Such alarm systems are referred to as threshold alarm systems. In order to lower the false alarm rate, the upper limit must be chosen rather high and the lower limit rather low, which inevitably leads to longer time delays in alarm-worthy situations. In addition, such an all-or-nothing system does not comply with the ISO standard, which proposes a graduated alarm system with different warning divisions.
• the threshold alarm In the known threshold alarm system, an upper and a lower threshold are specified for a fluctuating signal, an alarm being triggered when the signal moves from the interval defined by the threshold values.
• the threshold alarm has the following disadvantages. He is unstable towards
• Runaway It is not adaptive, ie limits have to be set manually and, in particular in the case of a signal with a drift, e.g. B. caused by a time be permanently adjusted before changing the detector sensitivity. If the threshold alarm limits are set too far, there will be long delays before an alarm is detected. If the limits are too narrow, false alarms often occur. In practice, therefore, a so-called “border balancing act” or an option, such as "all alarms off for two minutes", is set. Furthermore, the threshold alarm system is not suitable in the event that a large number of signals must be monitored by an alarm system.
• a fire alarm system for determining and delivering an analog value corresponding to a change in a physical appearance of the ambient conditions.
• a sampling device for sampling an analog detection signal emitted from a determination section within a certain period of time
• a data processing device for forming an average value from the sampling data
• a storage device in which this sampling data can be stored and an alarm device which detects the presence of a fire after evaluation of the Indicates mean
• the data processing device is designed such that the scan data are written sequentially into the memory device, and a moving average is continuously formed from a certain number of the last stored scan data, the oldest scan data storage value in the sequence being replaced by the latest one .
• DE 31 27 324 A1 discloses a method and an arrangement for increasing the sensitivity and interference immunity in a hazard, in particular fire alarm system.
• the method used to trigger the alarm is adaptive and thus capable of learning. Therefore, the above methods are unable to adapt, for example, to a change in the sensitivity of the detector over time.
• DE 44 17 574 C2 relates to patient alarm detection using a target mode. In this process, an intentional change a physiological parameter of a patient dynamic
• the object of the present invention is therefore to avoid the disadvantages of the prior art and, in particular, to further develop a method of the type mentioned at the outset in such a way that an "alarm situation" is recognized more quickly and with a lower false alarm rate compared to the prior art.
• the object is achieved in that, in a first step, the mean value and the corresponding scatter of these measurement signal values are calculated from the mean value in a settable time window for temporally successive measurement signal values, that in a second step each further subsequent measurement signal value for obtaining a the respective evaluation variable is compared with the mean value and weighted with the scatter, and in a third step an outlier state is detected in the case of an evaluation variable exceeding an adjustable outlier parameter, while in an evaluation quantity exceeding an adjustable outlier parameter
• Evaluation variable an alarm state indicating the presence of a significant drift or jump in the measurement signal values is detected.
• the currently received measurement signal values are compared with the mean value and the scatter representing the fluctuation range, the evaluation variable determined thereby representing a measure of the presence of a significant drift.
• An advantage of the method according to the invention is that on-line detection of outliers is provided. It is also advantageous that the method according to the invention is adaptive, i. H. for example only physiological
• the evaluation variable is determined by forming the difference between the measurement signal value and the calculated mean value and then normalizing the difference.
• the evaluation variable is weighted by forming a division from the normalized difference between the measurement signal value and the mean value with the calculated scatter.
• an outlier state is detected when the normalized difference between the measurement signal value and the mean value, weighted with the calculated scattering, exceeds the set outlier parameter.
• an alarm state is detected if the normalized difference between the measured signal value and the mean value, weighted with the calculated scatter, exceeds the set alarm parameter.
• the corresponding measurement signal value is replaced by the current mean value calculated in the time-shifted window when an outlier condition occurs and the next following measurement signal value is processed.
• a different type of replacement can be carried out, which is particularly preferred for statistical reasons. It can for example, adding a noise or performing another imputation.
• the outlier value can in particular be replaced by an average plus an added random number, which originates from a probability distribution.
• a falsified or falsified measurement value can also simply be ignored for the further calculation.
• the mean value of the successive measurement signal values is formed from the summation of the individual measurement signal values, the number of the summation steps being determined by the width of the time window.
• the standard deviation is used as the scatter, the number of summation steps being determined by the width of the time window.
• time window is positioned by means of a time delay in order to be able to recognize even small gradients in the course of the measured variable over time, so that long-term drifts due to a correspondingly distant one , delayed moving window. Short-term drifts can also be detected with a correspondingly close, delayed moving window.
• the outlier parameter is set to a higher value than the alarm parameter.
• the width of the time window is preferably set to 10 successive measurement signal values and the outlier parameter is set to 6 and the alarm parameter to 3.
• the above-mentioned object is achieved in a device with a measured value detection device for receiving measured value signals and a measured value transmission device for converting and processing the received measured value signals, and one when a measured value is exceeded
• Alarm device which can be triggered by the limit value is solved in that, in order to detect the measurement signal values, in a time window which can be set according to width and time delay.
• a memory device is provided that in an initialization phase for temporally successive measurement signal values in the adjustable time window, calculation means are provided for calculating the mean values and the corresponding scatter, and that in a process phase a processor device is provided for obtaining an evaluation variable, with an adjustable alarm parameter exceeding evaluation size actuated the alarm device.
• outlier states and alarm states can thus be distinguished from one another in accordance with an evaluation variable thereby obtained, so that the false alarm rate can thus be significantly reduced compared to methods according to the prior art.
• 3a shows a highly schematic illustration of a drift
• 3b is a highly schematic representation of a jump
• 3c shows a highly schematic illustration of an outlier.
• the method according to the invention which is preferably implemented as a software program, is illustrated with its essential process steps in a flow diagram, designated as a whole by 10, in FIG. 1.
• a time window is provided in which an average value 2 and the associated scatter 3 of the measurement signal values around this average value are calculated over a length of i successive steps for the measurement signal values recorded in the time window.
• the mean value is not calculated from a series of the immediately preceding measured values, but that from a time window of latitude ⁇ in the past with the selectable time delay d.
• the lower summation limit for determining the mean value thus results from the subtraction nd- ⁇ , where n denotes the number of time steps carried out, d the time delay and ⁇ the window width.
• the upper summation limit results from the subtraction nd, so that the summation index i runs from nd- ⁇ to nd.
• the same summation limits apply to the determination of the scatter 3.
• an incrementation is carried out in a process step 4.
• the measurement signal value Y n acquired in a specific time step is compared with the mean value determined in the initialization phase by carrying out a difference formation and providing this difference formation with an amount normalization.
• the amount-standardized difference is weighted with the variance by including the variance as a divisor.
• the evaluation variable thereby obtained serves as a measure for the detection of outlier states occurring in this process step 4. If the evaluation variable obtained for the currently recorded measurement signal value is greater than a preset outlier parameter o (o> 0), the query in process step 4 reveals that an outlier state 6 is present. The outlier state can be ignored for the following calculation or replaced by a "reasonable" value. Imputation procedures are particularly suitable for this. In this case, the sequence program returns to increment instruction 4.
• query block 7 determines whether the evaluation variable obtained for the currently recorded measurement signal value is greater than a preset alarm parameter a. If the result is positive, an alarm state 8 is present.
• a return to the initialization phase is carried out, while if the result is negative, a return is made to the increment instruction.
• the outlier parameter is assigned a higher value than the alarm parameter.
• the abscissa axis serves as the time axis ⁇ C p, while the ordinate axis represents the amplitude of the measurement signal.
• 3a shows a highly schematic illustration of a drift.
• 3b shows a highly schematic representation of a jump.
• 3c shows a highly schematic representation of an outlier. The time dependence of a measured signal is shown.
• the internal parameters of the algorithm are the window width ⁇ ( ⁇ > 0), the delay d (d> 0), the initialization length i (i> ⁇ + d), the outlier parameter o (o> 0) and the alarm parameter a (a> 0).
• the newly measured value is compared with an average value estimated from the previous measured values together with the associated scatter (the empirical standard deviation) - in this respect, the algorithm is a natural generalization of the normal threshold alarm, in which the mean value and the spread are known be assumed. However, the mean value is not calculated from a series of the immediately preceding measured values, but from a time window of width ⁇ in the past, with the selectable time delay d.
• the type of calculation circumvents the problem that the measured values used to estimate the mean value and the spread have already started to drift and thus contribute to a considerable bias, which can go so far that a sufficiently slow drift is not recognized at all. Rather, the freely selectable delay d gives the option of choosing the critical angle of the slope that is just about to be recognized. Naturally, the smaller the slope, the larger d must be chosen.
• Each newly measured value is compared with the current mean value estimated according to the method according to the invention as follows: the measured value is more than the product of the selectable outlier factor and the scatter of the estimated mean value removed, it is classified as an outlier and replaced for further calculations by the current mean value (plus a random number with an expected value of zero and scatter according to the estimated scatter).
• the measured value is more than the product of (selectable) alarm factor a and scatter from the estimated mean, it is output that there is a significant drift, depending on the direction of the deviation, a drift upwards or below. In all other cases, no message is issued. Then the next time step is processed. You can choose whether you want to reinitialize after an alarm is issued, possibly with a further selectable time delay, or whether you want to continue calculating without a new initialization.
• the window width ⁇ influences the fluctuations of the estimated mean - the fluctuations decrease proportionally to the root of ⁇ .
• outlier parameter o 6
• the alarm parameter a 3.
• the calculated information outliers yes / no, alarm for drift up / down, or no significant drift can either be output directly on the screen or acoustically via agreed sound sequences, or at the entrance to an intelligent alarm system.

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• Engineering & Computer Science (AREA)
• Computer Security & Cryptography (AREA)
• Physics & Mathematics (AREA)
• General Physics & Mathematics (AREA)
• Alarm Systems (AREA)
• Measuring And Recording Apparatus For Diagnosis (AREA)

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• 1999
  • 1999-06-22 US US09/720,580 patent/US6556957B1/en not_active Expired - Lifetime
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  • 1999-06-22 EP EP99939929A patent/EP1097439B1/fr not_active Expired - Lifetime
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