Graphically presenting features of rise or fall perturbations of sequential values of five or more clinical tests

• US 10,540,786 B2
• Filed: 02/28/2014
• Issued: 01/21/2020
• Est. Priority Date: 02/28/2013
• Status: Active Grant

• Current Assignee: Lawrence A. Lynn
• Original Assignee: Lawrence A. Lynn
• Inventors: Lynn, Lawrence A., Lynn, Eric N.
• Primary Examiner(s): Vanni, G Steven
• Application Number:
  US14/194,474
• Publication Number:
  US 20140241603A1
• Time in Patent Office: 2,153 Days
• Field of Search: None
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/4842 Monitoring progression or stage of a disease
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: G01N 33/48 Biological material, e.g. blood, urine G01N33/02, G01N33/26, G01N33/44, G01N33/46 take precedence; Haemocytometers counting blood corpuscules distributed over a surface by scanning the surface G06M11/02
• CPC Class Codes: G06T 11/00 2D [Two Dimensional] image generation
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A patient monitoring system detects perturbations and detects or determines features of the perturbations and generates image cells responsive to the perturbations, organelles within the cells responsive to the features, and clinical regions responsive to the cells, and visualizations responsive to the clinical regions. The system also generates time-lapsable motion images comprising the cells which change over time in response to changes in the features or the detection of new perturbations. The system may convert the features into quanta defined at least in part by the clinical condition and may generate image components, such as pixels or groups of pixels, responsive to the quanta. Motion images may be generated from the image components.

Claims

1. A patient monitoring system for generating real-time images of changes in severity of sepsis comprising:

a real-time patient monitor having a display, a memory comprising instructions, and a processor, communicatively coupled to the memory and the display, that executes or facilitates execution of the instructions, such that the processor is programmed to;

receive, for each of at least five different clinical tests, at least two sequential clinical test values of that test;

detect at least one perturbation of the sequential values of each test, each perturbation being one of a rise of the values of that test or a fall of the values of that test;

for each perturbation, determine at least two features, wherein each feature is a value of the perturbation corresponding to a feature type, wherein the feature type comprises at least one of;

a beginning value, an end value, a peak value, a nadir value, a slope, a duration, a percent change, a magnitude, or a product of the magnitude multiplied by the slope;

generate a feature image component for each determined feature, the feature image component having a visual aspect responsive to the corresponding determined feature;

generate a perturbation image component for each detected perturbation, wherein each perturbation image component comprises a time dimensioned horizontal bar responsive to the features of the detected perturbation; and

graphically present on the display an image comprising the horizontal bars and the feature image components on a time dimensioned map, the image changing in real-time in response to changes in the features, the image being indicative of a change in the severity of sepsis over time.

2. The patient monitoring system of claim 1, wherein the processor is further programmed to aggregate the horizontal bars, the aggregated bars in combination defining a vertical dimension which increases with an increasing number of vertically overlapping bars at any given time and decreases with a decreasing number of overlapping bars, the vertical dimension being responsive of the number of detected perturbations which are present at the same time.

3. The patient monitoring system of claim 2, wherein the processor is further programmed to aggregate the horizontal bars so that an increase in the vertical dimension is responsive to an increase in the severity of sepsis over time and a decrease in the vertical dimension is responsive to a decrease in the severity of sepsis over time.

4. The patient monitoring system of claim 3, wherein the visual aspect is color and the color is configured so that both the color and the vertical dimension of the aggregated bars are responsive to an increase in severity of sepsis over time or a decrease in severity of sepsis over time.

5. The patient monitoring system of claim 1, wherein the visual aspect is at least one of size, orientation, fill color or texture, border color or texture, or transparency.

6. The patient monitoring system of claim 1 wherein each horizontal bar grows across the map over time as the duration of the detected perturbation increases.

7. The patient monitoring system of claim 1 wherein each horizontal bar defines an area within that bar.

8. The patient monitoring system of claim 7, wherein the feature image components are displayed in or adjacent the area within the bar.

9. The patient monitoring system of claim 7, wherein the processor is further programmed to aggregate the feature image components in or adjacent the area within the bar and to graphically present on the display a time-lapsable image by displaying each bar and the aggregated feature image components adjacent or within each bar for a plurality of additional times.

10. The patient monitoring system of claim 1, wherein the processor is further programmed to generate a bar responsive to the features of a detected perturbation by aggregating the feature image components of the detected perturbation.

11. The patient monitoring system of claim 1, wherein the map comprises a plurality of clinical regions, and wherein each bar is displayed within a clinical region.

12. The patient monitoring system of claim 1, wherein the processor is further programed to:

detect at least one relational perturbation comprised of at least two pathophysiologically linked perturbations occurring in timed relationship with each other, and

generate a relational perturbation image component for the detected relational perturbation, wherein each perturbation image component comprises a time dimensioned horizontal bar responsive to the features of the detected relational perturbation.

13. The patient monitoring system of claim 12 wherein the time dimensioned horizontal bar grows across the map over time as the duration of the detected relational perturbation increases.

14. The patient monitoring system of claim 1, wherein the processor is further programmed to:

graphically present on display a plurality of defined regions, wherein each region corresponds to a clinical system,

graphically present each bar on the map within the defined region associated within the clinical system to which the detected perturbation relates and within the time corresponding to the beginning value, the duration, and the end value of the detected perturbation.

15. The patient monitoring system of claim 14, wherein the processor is further programmed to aggregate the bars within a defined region, the aggregated bars in combination defining a vertical dimension within the defined region which increases with an increasing number of vertically overlapping bars at any given time and decreases with a decreasing number of vertically overlapping bars at any given time, the vertical dimension being responsive to a change of the severity of sepsis induced change of the clinical system to which the region corresponds.