Microprocessor system for the analysis of physiologic and financial datasets

Abstract

A system and method for organization and analysis of complex and dynamically interactive time series is disclosed. One example comprises a processor based system for relational analysis of physiologic signals for providing early recognition of catastrophic and pathologic events such as pathophysiologic divergence. The processor is programmed to identify pathophysiologic divergence of at least one of first and second physiologic parameters in relationship to the other and to output an indication of the divergence. An object-based method of iterative relational processing waveform fragments in the time domain is described wherein each more complex waveform object inherits the characteristics of the waveform objects from which it is derived. The first physiologic parameter can be the amplitude and frequency of the variation in chest wall impedance or nasal pressure and the second parameter can be a measure or indication of the arterial oxygen saturation.

Description

FIELD OF THE INVENTION [0001] This invention relates to an object based system for the organization, analysis, and recognition of complex timed processes and the analysis and integration of time series outputs of data sets and particularly physiologic data sets, and to the evaluation of the financial and physiologic datasets and the determination of relationships between them. BACKGROUND [0002] The analysis of time series data is widely used to characterize the behavior of a system. The following four general categories of approaches are commonly applied to achieve characterization of such a system and these provide a general background for the present invention. The approaches are illustrative both in their conceptualization, application, and limitations. [0003] The first such approach represents a form of mathematical reductionism of the complexity through the application of a cascade of rules based on an anticipated relationship between the time series output and a given set of s...

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Benefits of technology

[0047] Another example of the value of monitor based automatic divergence recognition, according to the present invention is provided by a patient who has experienced a very mild breach of the alarm threshold in association with significant physiologic divergence such as a patient whose baseline oxygen saturation is 95% in association with a given baseline amplitude and frequency of minute ventilation as identified by the impedance monitor. For this patient, the fall in oxygen saturation over a period of two hours from 95% to 89% might be perceived by the nurse or house officer as representing only a mild change which warrants the addition of simple oxygen treatment by nasal cannula but no further investigation. However, if this same change is associated with marked physiologic divergence wherein the patient has experienced significant increase in the amplitude and frequency of the chest impedance, the microprocessor identification of significant pathophysiologic divergence can give the nurse or house officer cause to consider further performance of a blood gas, chest x-ray or further investigation of this otherwise modest fall in the oxygen saturation parameter.

[0048] It is noted that excessive sedation is unlikely to produce physiologic divergence since sedation generally results in a fall in minute ventilation, which will be associated with a fall in oxygen saturation if the patient is not receiving nasal oxygen. The lack of pathophysiologic divergence in association with a significant fall in oxygen saturation can provide diagnostic clues to the house officer.

[0049] In a preferred embodiment, the processor system can automatically output an indication of pathophysiologic divergence relating to timed data sets derived from sensors which measure oxygen saturation, ventilation, heart rate, plethesmographic pulse, and/or blood pressure to provide automatic comparisons of linked parameters in real time, as will be discussed. The indication can be provided in a two or three-dimensional graphical format in which the corresponding parameters are presented summary graphical format such as a timed two-dimensional or three-dimensional animation. This allows the nurse or physician to immediately recognize pathophysiologic divergence.

[0050] According to another aspect of the invention the comparison of signals can be used to define a mathematical relationship range between two parameters and the degree of variance from that range. This approach has substantial advantages over the simple comparison of a given signal %kith itself along a time series to determine variability with respect to that signal (as is described in Griffin U.S. Pat. No. 6,216,032, the disclosure of which is incorporated by reference as is completely disclosed herein), which has been shown to correlate loosely with a diseased or aged physiologic system. The signal variability processing method of the prior art, which has been widely used with pulse rate, lacks specificity since variance in a given signal may have many causes. According to the present invention a plurality of signals are tracked to determine if the variability is present in all of the signals, to define the relationship between the signals with respect to that variability, and to determine if a particular signal (such as for example airflow) is the primary (first) signal to vary with other signals tracking the primary signal. For example, airway instability, sepsis, stroke, and congestive heart failure are all associated with a high degree of heart rate variability and this can be determined in relation to a baseline or by other known methods, however in the preferred embodiment the general variability of a plurality of signals is determined and these are matched to determine if a particular signal has a greater variability than the other signals, and more importantly the dynamic relationship between the signals is determined to identify the conformation of that variability. In this respect for example the pulse in sepsis in a neonate may show a high degree of variability, by confirming that this variability is associated with a general multi-parameter conformation as shown in FIGS. 2a and 2b(and will be discussed in more detail) rather than a conformation of rapidly expanding and contracting parameters, as is typical of airway instability. In this way the etiology of the pulse variability is much better identified. Variability is therefore defined in relation to; which parameters are changing, whether they are changing together in a particular category of conformation indicative of a specific disease process, and the extent to which they follow anticipated subordinate behavio...

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