Activity monitoring device and method

• US 8,979,774 B2
• Filed: 01/13/2009
• Issued: 03/17/2015
• Est. Priority Date: 01/13/2009
• Status: Active Grant

• Current Assignee: Robert Bosch GmbH
• Original Assignee: Robert Bosch GmbH
• Inventors: Srinivasan, Soundararajan, Gacic, Aca, Thiruvengada, Hari, Charania, Amirali Kayamali
• Primary Examiner(s): HENSON, DEVIN B
• Application Number:
  US12/352,935
• Publication Number:
  US 20100179452A1
• Time in Patent Office: 2,254 Days
• Field of Search: 600/587, 600/595
• 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 a multilayer perceptron model, 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 executing the multilayer perceptron model using acceleration data and energy expenditure data, 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, wherein the first data comprises an inferred activity in which the wearer participated, the inference based upon the executed multilayer perceptron model.

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, wherein the computer program further comprises computer instructions for executing the multilayer perceptron model 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. The system of claim 7, wherein the computer program further comprises computer instructions for executing the multilayer perceptron model to:

calibrate the multilayer perceptron model with a first transmitted physiologic data.

9. The system of claim 7, wherein the computer program further comprises computer instructions for executing the multilayer perceptron model to:

analyze a relative inclination, the determined periodic acceleration, and the spectral flatness to distinguish between a sitting activity, a standing activity, and a lying-down activity.

10. The system of claim 7, wherein the computer program further comprises computer instructions for executing the multilayer perceptron model to:

analyze the energy expenditure data, a velocity, the determined spectral flatness, and the determined periodic acceleration to distinguish between a dynamic wearer activity and a static wearer activity.

11. The system of claim 7, wherein the computer program further comprises computer instructions for executing the multilayer perceptron model to:

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

perform a log sigmoid activation function for an output layer.