Home diagnostic system

• US 8,388,532 B2
• Filed: 12/22/2006
• Issued: 03/05/2013
• Est. Priority Date: 12/22/2005
• Status: Active Grant

• Current Assignee: Lachesis Biosciences Limited
• Original Assignee: Lachesis Biosciences Pty., Ltd.
• Inventors: Morgan, Timothy Matthias
• Primary Examiner(s): Johnson, III, Henry M
• Assistant Examiner(s): SORIANO, BOBBY GILES
• Application Number:
  US11/645,022
• Publication Number:
  US 20070185391A1
• Time in Patent Office: 2,265 Days
• Field of Search: 600/300, 600/301, 128/923
• US Class Current: 600/301
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• 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: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A diagnostic system is disclosed. In one embodiment, the system includes i) an input interface for use by a person to submit user profile data, physical data and psychological data to the system, the physical data representing heart rate, blood pressure, and other biophysical parameters of the person, the psychological data representing quality of life and needs satisfaction and other psychological parameters of the person, ii) an analyzer for processing the physical data and psychological data to generate risk profile data based on criteria data for conditions and iii) an output interface for providing risk profile displays using the risk profile data to present for the person risk levels associated with the conditions.

Claims

1. A diagnostic computer system, comprising:

a processor implemented with a software-controlled computer, dedicated hardware circuits, or a combination of a software-controlled computer and dedicated hardware circuits, the processor being configured to;

(i) generate an input interface to receive user profile data, physical data and psychological data from a user, the user profile data including attributes with resource level data for the user, the physical data including at least one of heart rate, blood pressure, and other biophysical parameters of the user, and the psychological data including at least some basic needs satisfaction inventory (BNSI) parameters of the user;

(ii) process the physical data and psychological data to generate metric data including parameters for comparison against criteria data for conditions, the metric data representing satisfaction scores for BNSI categories obtained using the BNSI parameters;

(iii) generate risk profile data using the user profile data, the parameters, the metric data, and the criteria data;

(iv) generate recommendation data based on the user profile data, the parameters, the metric data, and the criteria data, the recommendation data representing recommendations for the user relating to the conditions and including activity data representing different activities to be performed by the user, the activity data being generated for each BNSI category based on said satisfaction scores by;

(a) retrieving all activities for the BNSI category for consideration;

(b) generating a difference value for each of the attributes of the user by comparing the attributes of the user with corresponding attributes of each of the retrieved activities; and

(c) selecting a subset of the retrieved activities as at least one of the different activities based on the difference values generated; and

(v) generate an output interface to provide a risk profile based on the risk profile data and the recommendation data, the risk profile presenting to the user risk levels associated with the conditions and recommendations based on the recommendation data, the recommendations including an activity recommendation to address at least one psychological condition.

2. A diagnostic system as claimed in claim 1, further comprising:

a diagnostic kit including diagnostic equipment for use by the user to obtain the physical data.

3. A diagnostic system as claimed in claim 1, wherein the other biophysical parameters include at least one of:

(i) body mass index (BMI) parameters;

(ii) a waist circumference parameter;

(iii) a triglycerides (TG) parameter;

(iv) a cholesterol parameter;

(v) a fasting glucose (FG) parameter; and

(vi) a heart rate parameter.

4. A diagnostic system as claimed in claim 3, wherein the conditions relate to unsatisfactory levels of the parameters as determined by the criteria data, and the conditions include metabolic syndrome.

5. A diagnostic system as claimed in claim 1, wherein the psychological parameters include health related quality of life survey score parameters, and the processor, using the survey score parameters, is configured to generate metric data representing physical and mental health score parameters.

6. A diagnostic system as claimed in claim 1, wherein the recommendations represent prevention and intervention recommendations.

7. A diagnostic system as claimed in claim 1, wherein the input interface includes an interface configured to submit compliance data representing compliance by the user with the recommendations.

8. A diagnostic system as claimed in claim 1, wherein the system is connected to a communications network and the input and output interfaces are accessed by the user using a client device to submit the data and receive the risk profile.

9. A diagnostic system as claimed in claim 1, wherein the communications network includes the Internet, and the client device includes a browser configured to access and render the interfaces.

10. A diagnostic system as claimed in claim 1, wherein the system is configured to store data submitted by the user at different times as historical data, and the analyzer is further configured to display the risk profile based on the historical data.

11. A diagnostic system as claimed in claim 1, wherein the risk profile is presented in the form of a report document.

12. A diagnostic system as claimed in claim 1, wherein the blood pressure parameters include a systolic blood pressure (SBP) parameter and a diastolic blood pressure (DBP) parameter.

13. A diagnostic system as claimed in claim 1, wherein the processor is further configured to generate metric data parameters using the waist circumference parameter, gender and ethnicity parameters of the user profile data, the TG parameter, the cholesterol parameter, the blood pressure parameters and the FG parameter to generate risk profile data for metabolic syndrome.

14. A diagnostic system as clamed in claim 1, wherein the body mass index parameters include height and weight of the user, and are used to generate metric data representing the body mass index (BMI) for the user.

15. A diagnostic system as claimed in claim 1, wherein the activity data is generated with an activity level for each BNSI category based on the score for the category.

16. A diagnostic system as clamed in claim 1, wherein the recommendation data for diet and exercise is generated on the basis of the BMI metric data and recommendation data generated using the waist circumference, TG, cholesterol, blood pressure, and FG parameters.

30. A system as clamed in claim 1, wherein the output interface is further configured to display the risk profile.

32. A diagnostic system as claimed in claim 1, wherein the plurality of attributes of the user includes a psychological attribute and the corresponding attributes of the activities includes a corresponding psychological attribute.

33. A diagnostic system as claimed in claim 1, wherein the processor is configured to:

determine whether the user'"'"'s risk profile falls outside a threshold of a medical diagnostic criterion; and

cause the output interface to output an alert suggesting the user to contact a health professional if the user'"'"'s risk profile falls outside the threshold of the medical diagnostic criterion.

34. A diagnostic system as claimed in claim 33, wherein the medical diagnostic criterion is a psychological criterion and the health professional is a mental health professional.

35. A diagnostic system as claimed in claim 1, wherein the processor is configured to determine, from a plurality of response levels, a response level appropriate for each satisfaction score for each BNSI categories, the plurality of response levels including:

no activity recommendation needed;

some activity recommendation needed; and

generating advise to seek advice from a mental health professional.

17. A method executed by a diagnostic computer system, comprising:

generate a user interface to receive user profile data, physical data and psychological data from a user, the user profile data including attributes with resource level data for the user, the physical data including at lest one of heart rate, blood pressure and other biophysical parameters of the user, and the physiological data including basic needs satisfaction inventory (BNSI) parameters of the user;

processing the physical data and psychological data to generate results data based on criteria data for conditions, and the BNSI parameters are used to generate results data representing satisfaction scores for BNSI categories;

generating risk profile data using the results data and the criteria data;

generating recommendation data using the user profile data and the results data, the recommendation data representing recommendations for the user relating to the conditions and including activity data representing different activities to be performed by the user, the activity data being generated for each BNSI category based on said satisfaction scores by;

(a) retrieving all activities for the BNSI category for consideration;

(b) generating a difference value for each of the attributes of the user by comparing the attributes of the user with corresponding attributes of each of the retrieved activities; and

(c) selecting a subset of the retrieved activities as at least one of the different activities based on the difference values generated; and

generating an output interface to provide a risk profile based on the risk profile data and the recommendation data, the risk profile presenting to the user risk levels associated with the conditions and recommendations based on the recommendation data, the recommendations including an activity recommendation to address at least one psychological condition.

18. A method as claimed in claim 17, wherein the other parameters include at least one of:

(i) body mass index (BMI) parameters;

(ii) a waist circumference parameter;

(iii) a triglycerides (TG) parameter;

(iv) a cholesterol parameter;

(v) a fasting glucose (FG) parameter; and

(vi) a heart rate parameter.

19. A method as claimed in claim 18, wherein the conditions relate to unsatisfactory levels of the parameters as determined by the criteria data, and the conditions include metabolic syndrome.

20. A method as claimed in claim 17, wherein the parameters include health related quality of life survey score parameters, and the survey score parameters are used to generates results data representing physical and mental health score parameters.

21. A method as claimed in claim 17, wherein the recommendations represent prevention and intervention recommendations.

22. A method as claimed in claim 17, further including providing an interface configured to submit compliance data representing compliance by the user with the recommendations.

23. A method as claimed in claim 17, further including storing data submitted by the user at different times as historical data, and the historical data to generate the results data.

24. A process as claimed in claim 17, wherein the blood pressure parameters include a systolic blood pressure (SBP) parameter and a diastolic blood pressure (DBP) parameter.

25. A method as claimed in claim 24, further including using the waist circumference parameter, gender and ethnicity parameters of the user profile data, the TG parameter, the cholesterol parameter, the blood pressure parameters and the FG parameter to generate results data for metabolic syndrome.

26. A method as claimed in claim 17, wherein the body mass index parameters include height and weight of the user, and are used to generate results data representing the body mass index (BMI) for the user.

27. A method as clamed in claim 17, wherein the activity data is generated with an activity level for each BNSI category based on the score for the category.

28. A method as clamed in claim 27, wherein the recommendation data for diet and exercise is generated on the basis of the BMI results data and recommendation data generated using the waist circumference, TG, cholesterol, blood pressure, and FG parameters.

31. A method as claimed in claim 17, wherein the providing includes displaying the risk level.

29. A non-transitory computer-readable medium having processor-readable code that causes one or more processors to perform a method, comprising:

receiving user profile data, physical data and psychological data from a user, the user profile data including attributes with resource level data for the user, the physical data including blood pressure and other parameters of the user, and the physiological data including basic needs satisfaction inventory (BNSI) parameters;

processing the physical data and psychological data to generate results data based on criteria data for conditions, and the BNSI parameters are used to generate results data representing satisfaction scores for BNSI categories;

generating risk profile data using the results data and the criteria data;

generating recommendation data using the user profile data and the results data, the recommendation data including activity data representing the different activities to be performed by the user and generated for each BNSI category based on said satisfaction scores by;

(a) retrieving all activities for the BNSI category for consideration;

(b) generating a difference value for each of the attributes of the user by comparing the attributes of the user with corresponding attributes of each of the retrieved activities; and

(c) selecting a subset of the retrieved activities as at least one of the different activities based on the difference values generated; and

; and

providing, based on the results data, the risk profile data, and the recommendation data, the user with a risk level associated with the conditions and activities to address the conditions, the recommendations including an activity recommendation to address at least one psychological condition.