Activity Monitoring Device and Method

• US 20100179452A1
• Filed: 01/13/2009
• Published: 07/15/2010
• Est. Priority Date: 01/13/2009
• Status: Active Grant

• Current Assignee: Robert Bosch GmbH
• Original Assignee: Robert Bosch GmbH
• Inventors: Thiruvengada, Hari, Charania, Amirali Kayamali, Srinivasan, Soundararajan, Gacic, Aca
• Granted Patent: US 8,979,774 B2
• Time in Patent Office: Days
• US Class Current: 600/595
• 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: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

A physical activity monitoring method and system in one embodiment includes a communications network, a wearable sensor device configured to generate physiologic data associated with a sensed physiologic condition of a wearer, and to generate context data associated with a sensed context of the wearer, and to transmit the physiologic data and the context data over the communications network, a memory for storing the physiologic data and the context data, a computer and a computer program executed by the computer, wherein the computer program comprises computer instructions for rendering first data associated with the physiologic data and second data associated with the context data, and a user interface operably connected to the computer for rendering the first data and the second data.

Claims

1. A physical activity monitoring system comprising:

a communications network;

a wearable sensor device configured to generate physiologic data associated with a sensed physiologic condition of a wearer, and to generate context data associated with a sensed context of the wearer, and to transmit the physiologic data and the context data over the communications network;

a memory for storing the physiologic data and the context data;

a computer and a computer program executed by the computer, wherein the computer program comprises computer instructions for rendering first data associated with the physiologic data and second data associated with the context data; and

a user interface operably connected to the computer for rendering the first data and the second data.

2. The system of claim 1, wherein the wearable sensor device is configured to generate the context data based upon a signal received by the wearable sensor device.

3. The system of claim 2, wherein the received signal is a global positioning satellite (GPS) signal.

4. The system of claim 2, wherein the received signal is a signal transmitted by a portable electronic device.

5. The system of claim 1, wherein the second data comprises:

the identification of an individual in the company of the wearer when the physiologic condition was sensed.

6. The system of claim 1, wherein the computer program comprises computer instructions for rendering:

activity information data;

activity recording data;

activity goal setting data; and

activity reviewing data.

7. The system of claim 1, further comprising a multilayer perceptron model operably connected to the computer and configured to:

determine a change in a y-axis orientation of the wearer;

determine a change in a z-axis orientation of the wearer;

determine a change in a three dimensional velocity of the wearer;

determine if there is a periodic acceleration in the z-axis using an autocorrelation function; and

determine a spectral flatness measure of power spectral density coefficients.

8. A method of displaying data associated with physical activities comprising:

storing a multilayer perceptron model;

transmitting first physiologic data associated with a first sensed physiologic condition of a wearer;

calibrating the multilayer perceptron model with the first transmitted physiologic data;

transmitting second physiologic data associated with a second sensed physiologic condition of the wearer during an activity;

using the stored multilayer perceptron model to determine at least one characteristic of the wearer during the activity;

determining the nature of the activity based upon the determined at least one characteristic; and

displaying first data associated with the second physiologic data and second data associated with the determined nature of the activity.

9. The method of claim 8, wherein using the stored multilayer perceptron model comprises:

determining a change in a y-axis orientation of the wearer;

determining a change in a z-axis orientation of the wearer; and

determining a change in a three dimensional velocity of the wearer.

10. The method of claim 9, wherein using the stored multilayer perceptron model further comprises:

determining if there is a periodic acceleration in the z-axis using an autocorrelation function.

11. The method of claim 10, wherein using the stored multilayer perceptron model further comprises:

determining a spectral flatness measure of power spectral density coefficients.

12. The method of claim 8, wherein the stored multilayer perceptron model comprises:

a hyperbolic tangent sigmoid activation function for a hidden layer; and

a log sigmoid activation function for an output layer.

13. The method of claim 8, further comprising:

transmitting context data associated with a sensed context of the wearer during the activity; and

displaying third data associated with the context data.

14. The method of claim 13, wherein displaying third data comprises:

displaying a name of an individual.

15. A method of monitoring physical activity comprising:

attaching a sensor to a wearer;

activating the sensor;

generating physiologic data associated with a sensed physiologic condition of the wearer during a wearer activity;

generating context data associated with a sensed context of the wearer during the wearer activity;

analyzing the physiologic data with a multilayer perceptron;

identifying the wearer activity based upon the analyses; and

displaying the identity of the activity and the context data.

16. The method of claim 15, wherein displaying the context data comprises:

displaying a name of an individual.

17. The method of claim 16, wherein displaying the context data further comprises:

displaying a name of a geographic location.

18. The method of claim 15, wherein analyzing the physiologic data comprises:

determining a change in a y-axis orientation of the wearer;

determining a change in a z-axis orientation of the wearer;

determining a velocity of the wearer;

determining a change in a three dimensional velocity of the wearer;

determining if there is a periodic acceleration in the z-axis using an autocorrelation function; and

determining a spectral flatness measure of power spectral density coefficients.

19. The method of claim 18, wherein identifying the wearer activity comprises:

analyzing a relative inclination, the periodicity, and the spectral flatness to distinguish between a sitting activity, a standing activity, and a lying-down activity.

20. The method of claim 18, wherein identifying the wearer activity comprises:

analyzing an energy expenditure of the wearer, the velocity, the spectral flatness, and the periodicity to distinguish between a dynamic wearer activity and a static wearer activity.