Assessment of medical conditions by determining mobility

• US 7,988,647 B2
• Filed: 03/16/2009
• Issued: 08/02/2011
• Est. Priority Date: 03/14/2008
• Status: Expired due to Fees

• Current Assignee: Frank E. Bunn, Richard D. Adair, William R. Bauer
• Original Assignee: Frank E. Bunn, Richard D. Adair, William R. Bauer
• Inventors: Adair, Richard D., Bunn, Frank E., Bauer, William R.
• Primary Examiner(s): HOEKSTRA, JEFFREY GERBEN
• Application Number:
  US12/382,401
• Publication Number:
  US 20100049095A1
• Time in Patent Office: 869 Days
• Field of Search: 600/300, 600/301, 600587-595, 702/127, 702138-154
• US Class Current: 600/595
• CPC Class Codes: A61B 2503/08 Elderly
• CPC Class Codes: A61B 5/1038 Measuring plantar pressure during gait
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1117 Fall detection
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/4023 Evaluating sense of balance
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G16H 40/60 for the operation of medical equipment or devices
• 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
• CPC Class Codes: G16H 70/00 ICT specially adapted for the handling or processing of medical references
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A mobility assessment detects abnormalities in motion using a stagger algorithm. The detected abnormalities are compared to known norms for a particular test to determine if the abnormalities are normal or not. The comparison can be made for abnormalities associated with different diseases and illnesses to classify whether or not the condition exists and its phase. The results may be used to generate a treatment regime.

Claims

1. A computer implemented system for assessing the mobility of a subject, said system comprising:

a camera to record motion of said subject;

a motion sensor to receive an output from said camera and determine movement of said subject, said motion sensor generating a data stream representative of such movement;

a database;

a first computer implemented assessment engine including a computer generated prompt to prompt an operator to provide data related to a test being performed by said subject,

an input to permit an operator to provide additional data in response to said prompt for recordal with said data stream in a database;

said system further including a second computer implemented assessment engine including a comparator to permit a comparison between motion represented by said data stream and representative movements recorded in said database to indicate whether said output is within said known norm, an allocator operable upon an indication of said comparator to allocate said motion to either a known norm or outside a known norm, and a deviation function to compare motion represented by said data stream with a representative movement and to detect abnormalities in such motion, and;

an output to indicate to an operator a classification of the mobility of said subject.

2. A system according to claim 1 wherein said database is organized to provide a pair of subsets of said database, each of which provides a respective known norm derived from the contents of the database, said comparator comparing said abnormalities to said known norms provided by said subsets of said database.

3. A system according to claim 2 wherein said allocator is operable to add said abnormalities to one of said databases.

4. A system according to claim 3 wherein said comparator implements a stagger algorithm to detect abnormalities.

5. A system according to claim 4 wherein said comparator incorporates a fuzzy logic decision engine to implement said stagger algorithm.

6. A system according to claim 2 including a mobility condition database containing records of abnormalities of prior assessments to permit the said output to be compared to prior assessments.

7. A system according to claim 6 wherein records of said mobility condition database include categories of conditions to permit said output to be compared to selected conditions and a classification of said condition obtained.

8. A system according to claim 7 including treatment database to permit said classification to generate a treatment regime.

9. A method of assessing mobility of a subject using a computer implemented system having a camera to record motion of said subject;

a motion sensor;

a database;

a first computer implemented assessment engine and a second computer implemented assessment engine, said method comprising the steps of;

recording motion of said subject with said camera,

utilising said motion detector to determine movement of said subject from an output from said camera,

utilising said first assessment engine to prompt an operator to provide data related to a test being performed by said subject,

recording an input provided by said operator in response to said prompt with said data stream in said database;

utilising said second computer implemented assessment engine to;

perform a comparison between motion represented by said data stream and representative movements recorded in said database, determining whether said comparison is within a known norm, allocating said motion according to whether or not it is within a known norm, applying a deviation function to compare motion represented by said data stream with a representative movement and to detect abnormalities in such motion, and;

providing an output to indicate to an operator a classification of the mobility of said subject.

10. A method according to claim 9 wherein said abnormalities are detected using a stagger algorithm.

11. A method according to claim 10 including the step of generating said known norms from a database of prior assessment.

12. A method according to claim 11 including the step of comparing said abnormalities to prior records of said subject.

13. A method according to claim 11 wherein said abnormalities are compared to prior assessments of different conditions.