Mobile personal services platform for providing feedback

• US 7,894,849 B2
• Filed: 07/09/2007
• Issued: 02/22/2011
• Est. Priority Date: 07/10/2006
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Kass, Alex M., Le, Dana, Farina, Daniel, Hughes, Lucian P., Richter, Owen E.
• Primary Examiner(s): Anderson; Matthew D.
• Assistant Examiner(s): Safaipour; Bobbak
• Application Number:
  US11/775,026
• Publication Number:
  US 20080012701A1
• Time in Patent Office: 1,324 Days
• Field of Search: 455/550.1, 455/414.1, 455/566, 455/420, 455/3.06, 455/466, 455/456.1, 455/404.1, 340/539.11, 340/521, 340/573.1, 340/574, 704/236, 704/251, 704/270
• US Class Current: 455/550.1
• 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 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/4803 Speech analysis specially adapted for diagnostic purposes
• CPC Class Codes: A61B 5/6814 Head
• CPC Class Codes: A61B 5/6824 Arm or wrist
• CPC Class Codes: A61B 5/6829 Foot or ankle
• CPC Class Codes: A63B 2071/0663 worn on the wrist, e.g. wrist bands
• CPC Class Codes: A63B 24/0075 Means for generating exercise programs or schemes, e.g. computerized virtual trainer, e.g. using expert databases
• 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

Methods, systems, and apparatus, including computer program products, for generating feedback. In one aspect, a method includes receiving sensor data from a plurality of sensors, wherein at least one of the plurality of sensors is associated with a mobile device of a user; aggregating the received sensor data to generate aggregated sensor data; processing the aggregated sensor data to determine an aggregated metric; comparing the aggregated metric to a target associated with the user to determine a measure of performance; and generating feedback based on the determined measure of performance. Further, the mobile device can comprise a mobile personal services device that includes one or more of an audio sensor, a video sensor, an environmental sensor, a biometric sensor, a location sensor, an activity detector, and a health monitor. The feedback can be displayed on the mobile personal services device. The feedback also can be displayed in near real-time.

Claims

1. A method of providing feedback, the method comprising:

receiving sensor data from a plurality of sensors, wherein at least one of the plurality of sensors is an audio sensor associated with a mobile device of a user;

aggregating the received sensor data to generate aggregated sensor data;

analyzing the content of a conversation between the user and another person, using at least a portion of the aggregated sensor data;

in response to analyzing the content of the conversation, determining an aggregated metric relating to an effectiveness of the user in communicating with the other person during the conversation;

comparing the aggregated metric to a user-defined conversation habit target to determine a conversation score; and

providing a conversation interface to the user, the conversation interface including feedback regarding the effectiveness of the user in communicating with the other person during the conversation, the feedback including the aggregated metric, the user-defined conversation habit target, and the conversation score,

wherein;

determining the aggregated metric further comprises determining, based on one or more of the words, that the user has made a specific point during the conversation, and

comparing the aggregated metric further comprises comparing the specific point to a user-defined checklist of points that the user intends to make during the conversation, and

providing the conversation interface further comprises providing information to the user that identifies one or more points that the user has not yet made during the conversation.

2. The method of claim 1, wherein the mobile device comprises a mobile personal services device that includes two or more of an audio sensor, a video sensor, an environmental sensor, a biometric sensor, a location sensor, an activity detector, and a health monitor.

3. The method of claim 2, further comprising displaying the conversation interface on the mobile device.

4. The method of claim 3, further comprising displaying the feedback in near real-time to receiving the sensor data.

5. The method of claim 1, wherein the sensor data is received in real-time.

6. The method of claim 2, further comprising:

receiving location data from a location-based device indicating a current position of the mobile device; and

processing the aggregated sensor data in accordance with the received location data.

7. The method of claim 2, wherein at least one of the plurality of sensors is associated with a mobile device of another user.

8. The method of claim 1, further comprising:

processing the received sensor data associated with at least one of the plurality of sensors to determine a second metric; and

computing a composite score based on the aggregated metric and the second metric,

wherein the feedback further includes the composite score.

9. The method of claim 1, further comprising:

identifying the other person, using at least a portion of the aggregated sensor data,

responsive to identifying the other person, selecting the user-defined conversation habit target associated with the other person, from among multiple user-defined conversation habit targets.

10. The method of claim 9, wherein the conversation habit target specifies a number of times that the user defines as acceptable to interrupt the other person during the conversation.

11. The method of claim 1, wherein determining the aggregated metric further comprises:

determining an amount of time that the user spent talking during the conversation, and

determining an amount of time that the user spent listening during the conversation.

12. The method of claim 1, wherein determining the aggregated metric further comprises:

determining, based on one or more of the words, a number of questions asked by the user.

13. The method of claim 1, further comprising:

determining that the conversation has begun when the aggregated sensor data indicates that the user has entered a room in which the other person is present.

14. The method of claim 1, further comprising:

determining that the conversation has begun when the aggregated sensor data indicates that the user is within a predetermined distance of the other person, and that at least one of the user or the other person are speaking.

15. The method of claim 1, further comprising:

determining that the conversation has begun when the aggregated sensor data indicates that the user and the other person have spoken for more than a predetermined amount of time.

16. The method of claim 1, wherein the feedback further comprises information identifying a start time of the conversation, an end time of the conversation, and a location of the conversation.

17. A system for providing feedback, the system comprising:

one or more computers; and

a non-transitory computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising;

receiving sensor data from a plurality of sensors, wherein at least one of the plurality of sensors is an audio sensor associated with a mobile device of a user;

aggregating the received sensor data to generate aggregated sensor data;

analyzing the content of a conversation between the user and another person, using at least a portion of the aggregated sensor data;

in response to analyzing the content of the conversation, determining an aggregated metric relating to an effectiveness of the user in communicating with the other person during the conversation;

comparing the aggregated metric to a user-defined conversation habit target to determine a conversation score; and

providing a conversation interface to the user, the conversation interface including feedback regarding the effectiveness of the user in communicating with the other person during the conversation, the feedback including the aggregated metric, the user-defined conversation habit target, and the conversation score,

wherein;

determining the aggregated metric further comprises determining, based on one or more of the words, that the user has made a specific point during the conversation, and

comparing the aggregated metric further comprises comparing the specific point to a user-defined checklist of points that the user intends to make during the conversation, and

providing the conversation interface further comprises providing information to the user that identifies one or more points that the user has not yet made during the conversation.

18. A non-transitory computer readable medium encoded with a computer program for providing feedback, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising:

receiving sensor data from a plurality of sensors, wherein at least one of the plurality of sensors is an audio sensor associated with a mobile device of a user;

aggregating the received sensor data to generate aggregated sensor data;

analyzing the content of a conversation between the user and another person, using at least a portion of the aggregated sensor data;

in response to analyzing the content of the conversation, determining an aggregated metric relating to an effectiveness of the user in communicating with the other person during the conversation;

comparing the aggregated metric to a user-defined conversation habit target to determine a conversation score; and

providing a conversation interface to the user, the conversation interface including feedback regarding the effectiveness of the user in communicating with the other person during the conversation, the feedback including the aggregated metric, the user-defined conversation habit target, and the conversation score,

wherein;

determining the aggregated metric further comprises determining, based on one or more of the words, that the user has made a specific point during the conversation, and

comparing the aggregated metric further comprises comparing the specific point to a user-defined checklist of points that the user intends to make during the conversation, and

providing the conversation interface further comprises providing information to the user that identifies one or more points that the user has not yet made during the conversation.