ACTIVITY MONITORING DEVICE AND METHOD

• US 20100234693A1
• Filed: 03/16/2009
• Published: 09/16/2010
• Est. Priority Date: 03/16/2009
• Status: Active Grant

• Current Assignee: Robert Bosch GmbH
• Original Assignee: Robert Bosch GmbH
• Inventors: Ganti, Raghu Kiran, Srinivasan, Soundararajan, Gacic, Aca
• Granted Patent: US 8,152,694 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A63B 2220/64 Frequency, e.g. of vibration oscillation
• CPC Class Codes: A63B 2220/70 Measuring or simulating ambient conditions, e.g. weather, terrain or surface conditions
• CPC Class Codes: A63B 2220/803 Motion sensors
• CPC Class Codes: A63B 2220/808 Microphones
• CPC Class Codes: A63B 2220/836 Sensors arranged on the body of the user
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G06V 40/23 Recognition of whole body movements, e.g. for sport training
• CPC Class Codes: G06V 40/25 Recognition of walking or running movements, e.g. gait recognition

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 audio context data associated with a sensed audio context of the wearer, and to form a communication link with the communications network, a memory for storing the physiologic data and the audio context data, a computer and a computer program executed by the computer, wherein the computer program comprises computer instructions for rendering activity data associated with the physiologic data and the audio context data, and a user interface operably connected to the computer for rendering the activity 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 audio context data associated with a sensed audio context of the wearer, and to form a communication link with the communications network;

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

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

a user interface operably connected to the computer for rendering the activity data.

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

3. The system of claim 2, wherein the received signal is generated by an activity of the wearer.

4. The system of claim 1, wherein:

the wearable sensor device is further configured to generate non-audio context data;

the memory is configured to store the non-audio context data; and

the computer program executed by the computer comprises computer instructions for associating the non-audio context data and the audio context data.

5. The system of claim 1, wherein the non-audio context 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 hidden Markov Model (HMM) stored within the memory for:

determining a 3-dimensional vector magnitude of acceleration;

determining a magnitude of the 3-dimensional vector magnitude of acceleration; and

determining a skewness of the magnitude of the 3-dimensional vector magnitude of acceleration.

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

storing an activity inference engine;

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

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

using the stored activity inference engine to determine the nature of the activity based upon the physiologic data and the context data; and

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

9. The method of claim 8, wherein using the stored activity inference engine comprises:

determining a 3-dimensional vector magnitude of acceleration; and

determining at least one cepstral coefficient.

10. The method of claim 9, wherein using the stored activity inference engine further comprises:

determining a magnitude of the 3-dimensional vector magnitude of acceleration;

determining a skewness of the magnitude of the 3-dimensional vector magnitude; and

determining cepstral coefficients.

11. The method of claim 8, wherein generating context data further comprises:

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

12. The method of claim 11, further comprising:

displaying an identification of a geographic location associated with the context data.

13. The method of claim 8, wherein generating context data further comprises:

generating context data associated with a received signal from a mobile device.

14. The method of claim 13, further comprising:

displaying a name of an individual based upon the context data.

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

analyzing the audio context data;

identifying the wearer activity based upon the analyses; and

displaying the identity of the activity.

16. The method of claim 15, further comprising:

generating non-audio context data associated with a sensed non-audio context of the wearer during the wearer activity; and

displaying the non-audio context data.

17. The method of claim 16, wherein displaying the non-audio context data comprises:

displaying a name of a geographic location.

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

determining a 3-dimensional vector magnitude of acceleration.

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

using data associated with a magnitude of the 3-dimensional vector magnitude of acceleration.

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

using data associated with a skewness of the magnitude of the 3-dimensional vector magnitude.