Computer system and method for diagnostic data display

A method for operating a computer system to generate and display multidimensional data. A set of multidimensional data points and a selected deviation range is received at a processor. The processor processes each data point to determine its value about the selected deviation range. Display data representative of data point indicia of the determined data point values at circumferentially spaced locations and with respect to an origin in a coordinate system is generated and stored by the processor. The data point indicia for the multidimensional data points are at circumferentially spaced locations, and a radial distance of the indicia with respect to the origin represents the determined data point values. A visual display of the display data can be produced on a printer or monitor.

FIELD OF THE INVENTION

The invention is a computer system and method for generating and displaying medical and other data.

BACKGROUND

Activities such as research in medical and other fields can result in the generation or collection of sets of multidimensional data. Complex data of this type is often processed and displayed in visual form for review and analysis. There remains, however, a continuing need for improved systems and methods for processing and displaying multidimensional data. For example, there is a need for systems and methods that can enhance the visualization of information from the data. In particular, there is a need for systems and methods that enhance a user's ability to gain insight and understanding from the data to facilitate the accurate and efficient interpretation of the data (e.g., for diagnostic decisions).

SUMMARY

Embodiments of the invention include a method for operating a computer system to generate display data representative of a display of multidimensional data. In embodiments, a set of multidimensional data points is received at a processor. The processor processes each data points to determine its value about a deviation range, including optionally a z-vector score, standard deviation, median absolute deviation or cumulative percent. The processor generates and stores display data representative of data point indicia of the determined data point values at circumferentially spaced locations and with respect to an origin in a coordinate system. The data point indicia for the multidimensional data points are at circumferentially spaced locations, and a radial distance of the indicia with respect to the origin represents the determined data point values. Other embodiments include producing a visual display of the generated display data on a monitor or printer.

DESCRIPTION OF THE INVENTION

Introduction and Overview

Embodiments of the invention include computer systems, programmed media and methods to process multidimensional data, generate data representative of visual displays of the data, and to provide visual or graphical displays of the data. These visualization tools enable users to efficiently gain insight from complex multidimensional data. For example, the tools can enhance the users' abilities to understand the data and to facilitate accurate interpretation and diagnostic decisions. The data is transformed into a multidimensional (e.g., 2D) plane, enabling users to interactively discover multivariate relationships among a large number of dimensions. Embodiments of the invention can perform simultaneous analysis of multiple parameters to unveil previously unknown patterns which may lead to a deeper understanding of the underlying phenomena or trends. These embodiments can also provide simplified diagnostic views for users that give them the ability to quickly compare and visualize individual high-dimensional data points with normative samples.

FIG. 1is a diagrammatic illustration of a computer system10in accordance with embodiments of the invention. As shown, computer system10includes a graphical user interface12having a monitor14, keyboard16and mouse18. A processing system20that has memory (e.g., ROM and/or RAM, not separately shown) is coupled to the user interface12. Programs reflecting instructions and algorithms for performing data processing methods in accordance with embodiments of the invention, and data representative of visual displays in accordance with embodiments of the invention, can be stored in the memory. Computer system10can be interfaced (e.g., by wireless or wired networks) to other computer or data collection systems (not shown). For example, multidimensional data that is to be processed by computer system10can be received over such a network, and data representative of visual displays produced by the computer system can be transferred to other computer systems over such a network. Visual displays in accordance with the invention can be presented on monitor14or a printer (not shown). The illustrated embodiment of computer system10is shown for purposes of example, and other embodiments of the invention have different or additional components, such as other user interfaces for administrators and providers that use the system, and different or additional memory and database structures.

FIG. 2is an exemplary visual display of a coordinate system including three (3) sets of thirty-six (36) dimension data point indicia in accordance with embodiments of the invention. The data point indicia of the first set are represented by open dots (i.e., “∘”), those of the second set by closed dots (i.e., “•”), and those of the third set by the letter “x”. As shown, the data point indicia are in the form of a thirty six vertex polygon, where each vertex is circumferentially spaced about an origin, and located on an individual radius of a two-dimensional circumferential construct C such as a circle or oval with having a radius length RL, where:
RL=2×Deviation,
and Deviation is a selected number representative of a deviation range. In some embodiments, Deviation is 2-5. The data point indicia for each of the different dimensions is at a different circumferentially spaced location. The location of each data point indicia along the radius length RL represents the value of the data point along the deviation range (e.g., a standard normal distribution in the embodiment shown inFIG. 2). For example, in embodiments where Deviation=3, data points representing values having a standard deviation of −3σ are plotted at the origin (i.e., center of circle C), data points representing values having a standard deviation of +3σ are plotted at the circumference of the circle, and data points representing 0σ values are plotted mid-way between the origin and circumference of the circle. The display shown inFIG. 2includes a circle illustrating the 0σ coordinates, and shading that represent the range of −1.5σ to +1.5σ coordinates.

General Description

In embodiments of the invention, Y is a set of X N-dimensional data points to be processed and displayed, i.e.,
Y={yx=(yx,1,yx,2, . . . ,yx,N)|1≤x≤X}
where X is the total number of high-dimensional data points, and N is the dimension of the data or total number of variables.

Along each dimension i,yi, σi, and mican be the corresponding mean, standard deviation, and median value across X objects, respectively. Hence, the equivalent N-dimensional mean, standard deviation and median vectors are given by,
Y={y1,y2, . . . ,yN}
σ={σ1,σ2, . . . ,σN}
M={m1,m2, . . . ,mN}
Methods in accordance with the invention transform the N-dimensional data point into an N-vertex polygon, where each vertex is located on the individual radius of a 2-D circle with a radius length of 2*Deviation, where Deviation is a value that can be set by the user, and is between 2 to 5 in some embodiments.

In the exemplary coordinate system shown inFIG. 3, each radius corresponds to one of the N variables (for e.g. N=32 inFIG. 3). The angular distance between each neighboring variable on the circumference of the circle is given by

(2*π)N.
Assuming without the loss of generality that the center of the circle is at origin (0,0), the location of the ithradius is given as,

Li={(r*cos⁡((i-1)*(2*π)N),r*sin⁡((i-1)*(2*π)N)|1≤i≤N}
where r is the radius of the circle equal to 2*Deviation. The method transforms the nthradius into a standard normal distribution for the corresponding nthvariable. The standard normal distribution for the nthvariable is derived from normal distribution N(yn, σn) by standardizing the values of nthvariable. In other words, calculating z-scores of value b for variable n, which is given by

z=b-y_nσn.
The center end of the radius corresponds to −Deviation*σnand nthpoint on the circumference corresponds to Deviation*σn. The value of Deviation is user-defined (e.g., as per the requirement of associate research).

FIG. 4is an illustration of a coordinate system shown inFIG. 3, when Deviation is set to 3. As represented by the bell curve, data plotted on the coordinate system ofFIG. 4will represent values over a standard normal deviation from of −3σ to +3σ. As is also shown inFIG. 4, as all the variables are transformed to their standard normal distribution on their respective radii, joining the standardized means (i.e. z=0) of all variables gives a concentric circle on the coordinate system. Similarly, other standard deviation values and ranges can be indicated on the coordinate system.FIG. 5, for example, shows the coordinate system ofFIG. 4with indicators such as shading that represents the values for any nthvariable below +1.5σnand above −1.5σn(i.e. within 1.5 standard deviations of the means). The value 1.5 in connection with the coordinate system shown inFIG. 5is user-defined and exemplary only, and an end-user can choose to display indicia representing any value between 0 and Deviation depending on an application. If for any variable, values go beyond this range (i.e. z>+1.5), then the corresponding point for that variable may be plotted out of the illustrated coordinate system.

In the embodiments described above, the data display is driven by the mean and standard deviation of the variables. However, the mean and standard deviations may be strongly impacted by outliers and hence models using mean as a central tendency indicator may be unlikely to detect outliers in samples. Accordingly, other embodiments of the invention use median as a measure of central tendency as opposed to mean. And instead of standard deviation, other embodiments use the median absolute deviation (MAD) for nthvariable, which can be represented as follows:
MADn=b*{Median (|yx,n−mn|)|1≤x≤X}
where b=1/Q(0.75), and Q(0.75) is the 0.75 quantile of the underlying distribution. In case of normal distribution, 1/Q(0.75) is 1.4826. The standardized z-score of value b for variable n is then given by:

z=b-mnMADn.
Visual analytics can be represented through two types of models in accordance with the invention:

Processing Algorithm

The following is a pseudo-code algorithm that can be implemented by embodiments of the invention (e.g., by computer system10) to visualize (e.g., generate and and plot) the N-dimensional data points on coordinate systems as described above:1. Given N-dimensional data point, D={d1, d2, . . . , dN}. The radius of the coordinate system is set to 2*Deviation.2. Convert the N-dimensional data point into z-vector,a. For (Y, σ),

zdi=di-miMADi|1≤i≤N3. Limiting the values of z-scores within [−Deviation, +Deviation] to fit in the coordinate system,
IFzdi>Deviation, thenzdi=Deviation. OR IFzdi<−Deviation thenzdi=−Deviation4. Scaling the Z-scores to fit the coordinate system,
zsdi=zdi+Deviation|1≤i≤N5. Plotting the scaled z-score on the respective radius of the coordinate system, assuming the center of the coordinate system is at origin (e.g., (0,0)),

Example

Case Study I: Acute Hypoxia Effects on Oculometrics

Thirty two (32) oculometric features are measured by using non-contact, non-invasive eye-tracking technology during the performance of computerized neuro-cognitive tests. All oculometric features are categorized mainly into four categories and can be grouped accordingly: fixations, saccades, blinks and pupillary dynamics.FIG. 6shows the visualization of oculometric features for one subject performing a neuro-cognitive test in hypoxia (data points of curve formed by open dots (i.e., “∘”). The curve formed by closed dot data points (i.e., “•”) represents the average curve of oculometric features across twenty subjects at normal baseline. It is evident from the display ofFIG. 6that the test time (variable #1), fluctuation in fixation time (variable #5), many saccadic features mainly including average saccadic lengths (variable #14), saccadic velocities (variable #19), and then blink rate (variable #23) and blink durations (variable #24) of the subject are significantly affected by hypoxia. This display also shows how hidden trends of oculometrics in hypoxic environments can be unveiled by the invention.

FIG. 7is an illustration of a display showing a comparison of oculometric features for the same subject (from which data shown inFIG. 6was collected) but different hypoxic conditions: normoxic baseline (curve formed by open dots) and hypoxia (curve formed by closed dots). From this display it is very that the blink rate (variable #23), fluctuation in left (variable #28) and right (variable #31) pupil size are affected in hypoxia for this individual subject.

Example

Case Study II: Acute Hypoxia Effects on Cardiovascular Parameters

Embodiments of the invention have been applied to visualize complete hemodynamic physiological data that includes five different sets of cardiovascular parameters as follows:1. Twelve beat-to-beat (BTB) cardiovascular parameters: RR-interval (RRI), Heart Rate, Systolic Blood Pressure (sBP), Diastolic Blood Pressure (dBP), Mean Arterial Blood Pressure, Stoke Volume, Stroke Index, Cardiac Output, Cardiac Index, Total Peripheral Resistance, Total Peripheral Resistance Index, Maximum rise in Pulse Pressure.2. Six Transthoracic Bioimpedance Cardiography (ICG) parameters: End-diastolic Index (EDI), IC, Acceleration Contractibility Index (ACI), Left Ventricular Work Index (LVWI), Left Ventricular Ejection Time (LVET), and Thoracic Fluid Content (TFC).3. Eight autonomic heart rate variability (HRV) parameters: RRI Low Frequency normalized unit (LFnu-RRI), RRI High Frequency normalized unit (HFnu-RRI), RRI Very Low Frequency (VLF-RRI), RRI Low Frequency (LF-RRI), RRI High Frequency (HF-RRI), RRI Power Spectral Density (PSD-RRI), RRI Ratio of Low Frequency to High Frequency (LF/HF-RRI), and Ratio of Low Frequency to High Frequency (LF/HF)4. Eight parameters related to the frequency analysis of systolic blood pressure: sBP Low Frequency normalized unit (LFnu-sBP), sBP High Frequency normalized unit (HFnu-sBP), sBP Very Low Frequency (VLF-sBP), sBP Low Frequency (LF-sBP), sBP High Frequency (HF-sBP), sBP Power Spectral Density (PSD-sBP), sBP Ratio of Low Frequency to High Frequency (LF/HF-sBP), and Ratio of Low Frequency to High Frequency (LF/HF).5. Eight parameters related to the frequency analysis of diastolic blood pressure: dBP Low Frequency normalized unit (LFnu-dBP), dBP High Frequency normalized unit (HFnu-dBP), dBP Very Low Frequency (VLF-dBP), dBP Low Frequency (LF-dBP), dBP High Frequency (HF-dBP), dBP Power Spectral Density (PSD-dBP), dBP Ratio of Low Frequency to High Frequency (LF/HF-dBP), and Ratio of Low Frequency to High Frequency (LF/HF).

Overall, all 42 parameters from 5 different sets of hemodynamic systems were combined and displayed to provide complete diagnostic view and interactivity to discover multivariate relationships between multiple physiological data sets.FIG. 8shows the individualized cardiovascular performance in hypoxic environment. The shaded zone represents the normal range of all 42 parameters for the given subject. The curve in the center of the shaded zone is the baseline measurement and another curve represents the cardiovascular performance of the same subject after breathing five minutes of hypoxic gas (8% O2+balance N2) which is equivalent to breathing at 22000 feet. The generated display clearly shows the cardiovascular performance difference of the same individual at high altitude as compared to the baseline. This kind of individualized display can be used in research as well as diagnostic purpose to evaluate the physiological performance not only in high altitudes but also in other challenging environments such as, but not limited to, space, deep water diving, during surgical operations etc. Similar to this case study, displays generated in accordance with embodiments of the invention can visualize the lab results of all medical tests conducted during a medical exam. Thus, displays in accordance with the invention have the potential to visualize an entire Electronic Medical Record (EMR) of a patient. This will facilitate all physicians to have one unified view of all labs to diagnose the medical problem and effectively provide medical treatment based on the results of all lab tests.

Example

Case Study III: Early Warning Signs during Hyperventilation

Embodiments of the invention have been adapted to continuously monitor multiple physiological parameters as shown inFIG. 9.FIG. 9shows the adaptation of a display that monitors the changes of eight hemodynamic parameters during hyperventilation, where each set of multidimensional data is presented on a common coordinate system. A curve in the middle of the shaded zone corresponds to the baseline of the subject before hyperventilation. The data represented by one curve corresponds to the hemodynamic performance of the subject after 1 minute of hyperventilation, which is clearly outside the shaded zone for most of the parameters. It should be noted that at 1 minute of hyperventilation even though hemodynamic parameters are significantly different from their respective baselines the subject did not perceive any symptoms. In this particular situation, if one continues to hyperventilate further, he/she can later experience common symptoms of hyperventilation such as dizziness, lightheadedness, tingling sensation, cognitive impairment and in worst case loss of consciousness. In this specific case example, based on the interpretive visualization power of displays in accordance with embodiments of the invention, a warning sign can be generated after 1 minute of hyperventilation to alert an individual about hyperventilation. As a result, the subject tries to recover, which can be observed in the display by curves showing the status of hemodynamic parameters at 2ndand 3rdminute of hyperventilation coming close to the shaded zone. At 4thand 5thminute, the hemodynamic parameters are close to the baseline showing the complete recovery from hyperventilation. Thus, displays in accordance with embodiments of the invention can be integrated in real-time systems that continuously monitor multiple physiological parameters, and can provide holistic view of all monitored parameters in a single snapshot to assist diagnostic decisions and provide early warning signs.

Embodiments of the invention can be extended to additional domains. For example, displays in accordance with embodiments of the invention can be presented in 3D.FIG. 10is an example of a 3D display that visualizes multiple displays along time axes. Sets of multidimensional data are presented in the multiple displays having separate coordinate systems in a common image or display frame. The time axes can also represent number of subjects where each display corresponds to each subject to monitor multiple subjects at the same time.

Displays in accordance with the invention can be presented in a dynamic or video domain. For example, the continuous monitoring of oculometric performance during the parachute flight from high altitude (e.g., 30000 feet) to the ground level can be presented by a sequence of one or more displays over time, with each sequential display labeled to identify features of the displayed data such as the altitude at which the data was taken. The displayed curves corresponding to high altitudes (e.g., the curves presented during the earlier portions of the sequence) may show significant deviation (e.g., outside the shaded zone) indicating significant changes in the oculometric performance due to hypoxia. In later-displayed curves corresponding to data taken at lower altitudes and as the altitude drops towards the ground level, the oculometric performance may be mainly in the shaded zone indicating return to the normal baseline.

Although the present invention has been described with reference to preferred embodiments, those of ordinary skill in the art will recognize that changes can be made in form and detail without departing from the spirit and scope of the invention. For example, althoughFIGS. 6 and 7illustrate displays of oculometric data, the invention is not so limited. Other types of data can be processed and displayed in accordance with other embodiments of the invention.