Patient Care Recommendation System

• US 20150150514A1
• Filed: 08/05/2011
• Published: 06/04/2015
• Est. Priority Date: 08/06/2010
• Status: Abandoned Application

• Current Assignee: United States Secretary of the Army, U.S. Army Medical Research And Materiel Command
• Original Assignee: Conceptual MindWorks Incorporated
• Inventors: Batchinsky, Andriy, Cancio, Leopoldo C., Salinas, Jose, Doderer, Mark
• Application Number:
  US13/204,460
• Publication Number:
  US 20150150514A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/7228 Signal modulation applied to the input signal sent to patient or subject; demodulation to recover the physiological signal modulation H03C
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• 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: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Disclosed are systems and methods to provide a patient care recommendation. The systems and methods receive patient information and a plurality of patient physiological signals that are related to a patient. The systems and methods are then operable to produce at least one derived patient signal from at least one of the plurality of patient physiological signals. The systems and methods use the patient information, at least one of the plurality of patient physiological signals, and the at least one derived patient signal to provide at least one patient care recommendation.

Claims

1-30. -30. (canceled)

31. An information handling system comprising:

a processor;

a patient information input coupled to the processor;

at least one patient physiological signal input coupled to the processor;

a diagnosis engine; and

a waveform analysis engine that is coupled to the diagnosis engine, operable to receive at least one patient physiological signal from the at least one patient physiological signal input, and use the at least one patient physiological signal to produce at least one derived patient signal; and

wherein the diagnosis engine is operable to provide at least one patient care recommendation using patient information received from the patient information input, at least one patient physiological signal received from the at least one patient physiological signal input, and the at least one derived patient signal from the waveform analysis engine.

32. The system according to claim 31, wherein the at least one physiological signal includes a respiratory rate signal.

33. The system according to claim 31, wherein the at least one physiological signal includes a heart rate signal.

34. The system according to claim 31, wherein the at least one derived patient signal produced by the waveform analysis engine includes a respiratory sinus arrhythmia signal produced using a patient respiratory signal received from the at least one patient physiological signal input and a patient heart signal received from the at least one patient physiological signal input.

35. The system according to claim 31, wherein the at least one derived patient signal produced by the waveform analysis engine includes a sample entropy signal.

36. The system according to claim 31, wherein the at least one patient care recommendation includes patient triage category recommendation and a patient life saving intervention (LSI) recommendation.

37. The system according to claim 36, wherein the patient triage category recommendation includes a recommended patient location and the patient LSI recommendation includes a predetermined severity scale value.

38. The system according to claim 31, wherein the patient information includes a patient physical characteristic.

39. The system according to claim 38, wherein the patient physical characteristic is selected from a group consisting of the patient'"'"'s age, the patient'"'"'s sex, the patient'"'"'s weight, and the patient'"'"'s height.

40. The system according to claim 31, further comprising:

a display output coupled to the processor, wherein the at least one patient care recommendation to provided to the display output.

41. The system according to claim 31, wherein the waveform analysis engine is operable to produce the at least one derived patient signal using at least one of a fast Fourier transform, a complex demodulation, a detrended fluctuation analysis, a similarity of distribution, and a fractal analysis.

42. The system according to claim 31, wherein the patient information is selected from a group consisting of a Glasgow Coma Score, a Field Triage Score, a revised Trauma Score, at least one physical exam score, a patient mechanism of injury, patient disease symptom data, and lab findings data.

43. The system according to claim 31, wherein

the diagnosis engine includes a neural network;

and

the at least one patient care recommendation includes a patient triage category recommendation including a value expressing the priority a patient has to be evacuated and a patient life saving intervention (LSI) recommendation produced by the neural network.

44. The system according to claim 31, wherein the waveform analysis engine is operable to produce the at least one derived patient signal using at least one of a detrended fluctuation analysis, a similarity of distribution, and a fractal analysis of the at least one physiological signal.

45. An information handling system, comprising:

a processor;

a patient information input coupled to the processor;

at least two patient physiological signal inputs coupled to the processor;

a diagnosis engine including a neural network; and

a waveform analysis engine that is coupled to the diagnosis engine, operable to receive at least one patient physiological signal from the at least one patient physiological signal input, and use the at least one patient physiological signal to produce at least one derived patient signal; and

wherein the diagnosis engine is operable to provide at least one patient care recommendation using patient information received from the patient information input, a plurality of patient physiological signals originating from one or more of the patient physiological signal inputs, the at least one derived patient signal from the waveform analysis engine, and trends in at least one of the at least one of the plurality of physiological signals and the at least one derived patient signal, and

wherein the at least one patient care recommendation includes a patient triage category recommendation and a patient life saving intervention (LSI) recommendation produced by the neural network present.

46. The system according to claim 45, wherein the at least two physiological signal includes a respiratory rate signal and a heart rate signal.

47. The system according to claim 45, wherein the at least one derived patient signal produced by the waveform analysis engine includes a respiratory sinus arrhythmia signal produced using a patient respiratory signal received from the at least one patient physiological signal input and a patient heart signal received from the at least one patient physiological signal input.

48. The system according to claim 45, wherein the patient information includes a patient physical characteristic selected from a group consisting of the patient'"'"'s age, the patient'"'"'s sex, the patient'"'"'s weight, and the patient'"'"'s height.

49. The system according to claim 45, further comprising:

a display output coupled to the processor, wherein the at least one patient care recommendation to provided to the display output.

50. The system according to claim 45, wherein the waveform analysis engine is operable to produce the at least one derived patient signal using at least one of a fast Fourier transform, a complex demodulation, a detrended fluctuation analysis, a similarity of distribution, and a fractal analysis.