HEALTH MONITORING SYSTEM FOR CALCULATING A TOTAL RISK SCORE

• US 20150324541A1
• Filed: 11/23/2012
• Published: 11/12/2015
• Est. Priority Date: 11/28/2011
• Status: Abandoned Application

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips N.V.
• Inventors: CHIAU, Choo Chiap, CHEUNG, Amy Oi Mee, ATAKHORRAMI, Maryam, WALKER, David Paul, NIJSEN, Tamara Mathea Elisabeth, TSAO, Rebecca
• Application Number:
  US14/360,691
• Publication Number:
  US 20150324541A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Embodiments of the invention provide for a health monitoring system comprising an activity monitor. The health monitoring system further comprises a processor and a memory for storing machine readable instructions. The instructions cause the processor to derive activity counts from the activity data acquired by the activity monitor. The instructions further cause the processor to store the activity counts in the memory, and are associated with a time. The instructions further cause the processor to calculate at least two statistical parameters from the activity counts, wherein the at least two statistical parameters are descriptive of the activity counts as a function of time. The instructions further causes the processor to calculate a risk score for each of the at least two statistical parameters. The instructions further cause the processor to calculate a total risk score using the risk score for each of the at least two statistical parameters.

Claims

1. A health monitoring system (400, 500), comprising:

an activity monitor (402, 412, 402′

) for acquiring activity data (410) descriptive of the time dependent motion of a subject (414);

a processor (404, 420, 508) for controlling the health monitoring system; and

a memory (406, 424, 514) for storing machine readable instructions (408, 434, 436, 438, 440), wherein execution of the instructions causes the processor to;

derive (208, 306) activity counts (426) from the activity data;

store (102, 210) the activity counts in the memory, wherein each of the activity counts is associated with a time;

calculate (104) at least two statistical parameters (428) from the activity counts, wherein the at least two statistical parameters are descriptive of the activity counts as a function of time;

calculate (106) a risk score (430) for each of the at least two statistical parameters; and

calculate (108) a total risk score (432) using the risk score for each of the at least two statistical parameters.

2. The health monitoring system of claim 1, wherein the activity monitor comprises an accelerometer (412, 602) for measuring accelerometer data, wherein the activity data comprises accelerometer data, wherein execution of the instructions causes the processor to derive the activity counts from the accelerometer data.

3. The health monitoring system of claim 2, wherein execution of the instructions further cause the processor to:

band pass filter (202, 302) the accelerometer data;

identify (204, 304) peaks (1804, 1806) in the band pass filtered accelerometer data; and

classify (206, 306) each of the peaks as either a stride or a half stride in accordance with the peak amplitude to calculate a time dependent walking speed, elapsed time from a previous step, and an estimated walking speed, wherein at least one of the two statistical parameters if descriptive of the time dependent walking speed.

4. The health monitoring system of claim 3, wherein the peaks are classified by comparing the peak amplitude, elapsed time from previous step (2002), and the estimated walking speed (2000) to a predetermined parameter space (2006, 2004).

5. The health monitoring system of claim 1, wherein the activity monitor comprises a respiration sensor (604) for measuring respiration data descriptive of the respiration rate of the subject, wherein the activity data comprises the respiration data, wherein execution of the instructions further causes the processor to:

calculate (606) respiration rate data from the respiration data;

store the respiration rate data in the memory, wherein the respiration rate data is associated with a time;

calculate (608) at least one additional statistical parameter using at least partially the respiration rate data; and

calculate an additional risk score for the at least one additional statistical parameters, wherein the total risk score is calculated (610) at least partially using the additional risk score.

6. The health monitoring system of claim 5, wherein the at least one additional statistical parameter is calculated using at least partially the activity counts to determine a respiration recovery rate (806).

7. The health monitoring system of claim 5, wherein the respiration sensor is any one of:

accelerometer, microphone, and a chest expansion sensor.

8. The health monitoring system of claim 1, wherein execution of the instructions further causes the processor to:

calculate at least one behavioral parameter (516, 1700) from the activity counts, wherein the behavioral parameter is descriptive of the activity counts as a function of time; and

calculate a behavioral similarity score (520, 1704) for the at least one behavioral parameter.

9. The health monitoring system of claim 8, wherein the at least one behavioral parameter is any one of the following:

a classification of activity intensity according to time of day, the longest period of time where the activity counts are above a predetermined activity, the time of day of the longest period of time where the activity counts are above a predetermined activity, waking time, sleeping time, sleep duration, total activity counts during sleep, the longest period of time where the activity counts are below a predetermined activity, the time of day of the longest period of time where the activity counts are below a predetermined activity, time of longest sustained activity, intensity level of longest sustained activity, duration of longest sustained activity, time of longest sustained inactivity, duration of longest sustained inactivity, average activity counts during different intervals of the day, pauses during walking, duration of pauses, time spent sitting, time spent lying, time spent walking, transition times between activities, and combinations thereof.

10. The health monitoring system of claim 8, wherein execution of the instructions causes the processor to calculate an activity template (524) from archived activity counts, wherein the at least one behavioral parameter is calculated making a comparison of the activity counts to the activity template.

11. The health monitoring system of claim 8, wherein the daily template is calculated by binning and averaging the archived activity counts in a predetermined number of daily time bins, wherein the comparison of the activity counts to the daily activity template is performed by:

binning the activity counts into the daily time bins; and

comparing the number of activity counts in each of the daily time bins to the average number of archived activity counts in each of the daily time bins.

12. The health monitoring system of claim 1, wherein the at least two statistical parameters comprise any one of the following:

total activity counts per day, average activity counts per day, the peak activity counts per day, the longest period of activity counts above a predetermined threshold, the longest period of activity counts below a predetermined threshold, an activity transition duration, and combinations thereof.

13. The health monitoring system of claim 1, wherein execution of the instructions further causes the processor to perform any one of the following:

display the total risk score on a display, forward the total risk score to a remote patient management system, email the total risk score, and combinations thereof.

14. A computer program product comprising machine executable instructions (408, 434, 436, 438, 440) for execution of a processor (404, 420, 508) of a health monitoring system (400, 500), wherein the health system comprises an activity monitor for acquiring activity data (410) descriptive of the time dependent motion of a subject (414), wherein execution of the instructions causes the processor to:

derive (208, 306) activity counts (426) from the activity data;

store (102, 210) the activity counts in the memory, wherein each of the activity counts is associated with a time;

calculate (104) at least two statistical parameters (428) from the activity counts, wherein the at least two statistical parameters are descriptive of the activity counts as a function of time;

calculate (106) a risk score (430) for each of the at least two statistical parameters; and

calculate (108) a total risk score (432) using the risk score for each of the at least two statistical parameters.

15. A method of health monitoring, the method comprising the steps of:

deriving (208, 306) activity counts (426) from the activity data of an activity monitor, wherein the activity monitor is operable for acquiring activity data descriptive of the time dependent motion of a subject;

recording (102, 210) the activity counts, wherein each of the activity counts is associated with a time;

calculating (104) at least two statistical parameters (428) from the activity counts, wherein the at least two statistical parameters are descriptive of the activity counts as a function of time;

calculating (106) a risk score (430) for each of the at least two statistical parameters; and

calculating (108) a total risk score (432) using the risk score for each of the at least two statistical parameters.

16. The method of claim 15, wherein the method further comprises the step of determining a risk stratification using the total risk score and/or calculating a risk classification for chronic obstructive pulmonary disease exacerbation and/or hospitalizing the subject if the total risk score is within a predetermined range.