Wearable health monitoring device and methods for step detection

• US 9,295,412 B2
• Filed: 08/15/2008
• Issued: 03/29/2016
• Est. Priority Date: 08/15/2007
• Status: Active Grant

• Current Assignee: MobileHelp, LLC
• Original Assignee: Integrity Tracking LLC
• Inventors: Otto, Chris A., Chen, Xiaofang
• Primary Examiner(s): Dvorak, Linda
• Assistant Examiner(s): LLOYD, EMILY M
• Application Number:
  US12/192,830
• Publication Number:
  US 20090069724A1
• Time in Patent Office: 2,783 Days
• Field of Search: 600/595
• US Class Current: 1/1
• 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 5/1117 Fall detection
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses

Abstract

A wearable health monitoring device includes at least one sensor for obtaining a signal indicative of movement of a user in at least one axis and logic configured to determine, based upon the signal, whether the user has taken a step.

Claims

1. A step detection device configured for detecting a step of a user, comprising:

an accelerometer configured to be coupled to the user'"'"'s torso and further configured for continuously measuring movement of the user and outputting three signals indicative of the movements of the user in three orthogonal axes, wherein each signal comprises an alternating current (AC) component representing dynamic motion and a direct current (DC) component representing static effects due to gravity; and

a processor electrically coupled to the accelerometer and configured for periodically sampling the three signals and storing digital data indicative of the three signals in a memory, wherein the memory is electrically coupled to the processor, the processor further configured for calculating activity induced energy expenditure (AEE) values based upon the AC components of the sampled signals and wherein AEE is a function of the AC components calculated over an integration period, the processor further configured to determine that the user has taken a step when;

(a) the processor determines when one of the AEE values calculated from the AC components exceeded a first threshold, wherein the first threshold is of a magnitude that indicates activity levels that are above stationary activity levels,

(b) after the processor determines that one of the AEE values has exceeded the first threshold, the processor compares a series of consecutive AC components following the AC component of the AEE value that exceeded the threshold to determine when one of the consecutive AC components has a value less than the other consecutive AC components,

(c) after the processor determines that one of the consecutive AC components has a value less than the other consecutive AC components, the processor determines when one of the consecutive AC components has a value greater than the other consecutive AC components,

(d) after the processor determines when one of the consecutive AC components has a value greater than the other consecutive AC components, the processor determines whether the user is vertical, and

(e) when the processor determines the user is vertical, the processor stores data in the memory indicative of a step,

the processor further configured to transmit the data indicative of the step to a central monitoring device automatically or in response to user input, and the central monitoring device is configured to provide the data indicative of the step to a service provider such that the service provider may determine the user'"'"'s well-being.

2. The step detection device configured to detect a step of the user of claim 1, wherein the processor is further configured for filtering the AC component from each of the three signals indicative of movement of the user and outputting the respective DC component of each of the three signals indicative of movement of the user for further processing.

3. The step detection device configured to detect a step of the user of claim 2, wherein the processor is further configured for subtracting each of the DC components from a respective one of the signals indicative of movement of the user and outputting the respective AC component of each of the three signals indicative of movement of the user for further processing.

4. The step detection device configured to detect a step of the user of claim 1, wherein the processor is further configured for filtering the DC component from each of the three signals indicative of movement of the user and outputting the respective AC component of each of the three signals indicative of movement of the user for further processing.

5. The step detection device configured to detect a step of the user of claim 4, wherein the processor is further configured for subtracting each of the AC components from a respective one of the signals indicative of movement of the user and outputting the DC component of each of the three signals indicative of movement of the user for further processing.

6. The step detection device configured to detect a step of the user of claim 1, wherein the processor is further configured for calculating the AEE over the integration period by:

(1) calculating the square root of the sum of the squares of the AC components for each discrete sample during the integration period; and

(2) summing the calculated values for each discrete sample during the integration period, wherein the sum is the AEE.

7. A step detection method for detecting a step of a user, comprising:

measuring movement of the user with an accelerometer configured for coupling to a user'"'"'s torso;

outputting, by the accelerometer, three signals indicative of the movement of the user'"'"'s torso in three orthogonal axes, wherein each signal comprises an alternating current (AC) component representing dynamic motion and a direct current (DC) component representing static effects due to gravity;

periodically sampling the three signals with a processor coupled to the accelerometer;

storing, by the processor, digital data indicative of the sampled signals in a memory, wherein the memory is electrically coupled to the processor;

periodically calculating, by the processor, activity-induced energy expenditure (AEE) values based on the AC components of the sampled signals and wherein AEE is a function of the AC components calculated over an integration period;

determining, by the processor, that the user has taken a step when;

(a) the processor determines when one of the AEE values calculated from the AC components exceeded a first threshold, wherein the first threshold is of a magnitude that indicates activity levels that are above stationary activity levels,

(b) after the processor determines that one of the AEE values has exceeded the first threshold, the processor compares a series of consecutive AC components following the AC component of the AEE value that exceeded the threshold to determine when one of the consecutive AC components has a value less than the other consecutive AC components,

(c) after the processor determines that one of the consecutive AC components has a value less than the other consecutive AC components, the processor determines when one of the consecutive AC components has a value greater than the other consecutive AC components,

(d) after the processor determines when one of the consecutive AC components has a value greater than the other consecutive AC components, the processor determines whether the user is vertical, and

(e) when the processor determines the user is vertical, the processor stores data in the memory indicative of a step,

transmitting the data to a central monitoring device automatically or in response to user input; and

providing the data, by the central monitoring device, to a service provider for use in determining the user'"'"'s well-being.

8. The step detection method configured to detect a step of the user of claim 7, further comprising:

filtering, by the processor, the AC component from each of the three signals indicative of movement of the user; and

outputting, by the processor, the DC component of each of the three signals indicative of movement of the user for further processing.

9. The step detection method configured to detect a step of the user of claim 8, further comprising:

subtracting, by the processor, each of the DC components from a respective one of the signals indicative of movement of the user; and

outputting, by the processor, the AC components of the three signals indicative of movement of the user for further processing.

10. The step detection method configured to detect a step of the user of claim 7, further comprising

filtering, by the processor, the DC component from each of the respective signals indicative of movement of the user;

and

outputting, by the processor, the AC component of each of the three signals indicative of movement of the user for further processing.

11. The step detection method configured to detect a step of the user of claim 10, further comprising:

subtracting, by the processor, each of the AC components from a respective one of the signals indicative of movement of the user; and

outputting, by the processor, the DC components of the three signals indicative of movement of the user for further processing.

12. The step detection method configured to detect a step of the user of claim 7, further comprising:

calculating, by the processor, the AEE over the integration period by;

(1) calculating the square root of the sum of the squares of the AC components for each discrete sample during the integration period; and

(2) summing the calculated values for each discrete sample during the integration period, wherein the sum is the AEE.

13. The step detection method configured to detect a step of the user of claim 7, wherein the periodic calculating of AEE is performed for each sample of the three measured signals indicative of movement of the user.