Triggering user queries based on sensor inputs

Patent metadata

Field	Value
Publication number	US-9173567-B2
Application number	US-201113107022-A
Country	US
Kind code	B2
Filing date	May 13, 2011
Priority date	May 13, 2011
Publication date	Nov 3, 2015
Grant date	Nov 3, 2015

Abstract

In particular embodiments, a method includes accessing one or more physiological data streams, analyzing each physiological data stream in reference to a set of control parameters, and, if a data stream deviates from its control parameters, then transmitting a query to a mood sensor or a behavioral sensor.

First claim

What is claimed is:

1. A method for querying for self-reported mood or behavior data based on physiological sensor input comprising,
one or more processors, associated with one or more computing devices, accessing one or more physiological data streams from one or more physiological sensors, the physiological data streams comprising physiological data of a person, the physiological data comprising at least renal-Doppler data, and one or more of heart-rate data, blood-pressure data, pulse-oximetry data, or accelerometer data;
the one or more of the processors accessing a stress model comprising baseline renal-Doppler data, and one or more of baseline heart-rate data of the person, baseline blood-pressure data of the person, baseline pulse-oximetry data of the person, or baseline accelerometer data of the person, wherein the baseline renal-Doppler data measures a stress response of the sympathetic nervous system, and the stress model correlates the baseline renal-Doppler data of the person with one or more of the baseline heart-rate data of the person, the baseline blood-pressure data of the person, the baseline pulse-oximetry data of the person, or the baseline accelerometer data of the person;
the one or more of the processors analyzing each physiological data stream in reference to a corresponding set of control parameters to determine whether one or more of the physiological data streams deviates from the set of control parameters, the set of control parameters being based on the stress model; and
the one or more of the processors transmitting a query to a client system of the person if at least one of the physiological data streams deviates from its corresponding set of control parameters, wherein the query prompts the person to input self-reported mood data of the person or self-reported behavioral data of the person.

2. The method of claim 1 , further comprising:
the one or more processors receiving one or more non-physiological data streams from one or more of the mood sensor or the behavioral sensor in response to the query, the non-physiological data streams comprising one or more self-reported mood data of the person or elf-reported behavioral data of the person.

3. The method of claim 1 , further comprising:
the one or more processors analyzing each physiological data stream to identify an operating range for the sensor; and
the one or more processors generating for each physiological data stream the corresponding set of control parameters based on the operating range of the sensors.

4. The method of claim 1 , further comprising:
the one or more processors accessing one or more environmental data streams from one or more environmental sensors, the environmental data streams comprising environmental data;
the one or more processors analyzing each environmental data stream in reference to a corresponding set of control parameters;
if at least one of the environmental data streams deviates from its corresponding set of control parameters, then transmitting a query to one or more of a mood sensor or a behavioral sensor for self-reported mood data of the person or self-reported behavioral data of the person.

5. The method of claim 4 , wherein one or more of the environmental sensors comprises a barometer, a weather sensor, a pollen counter, a location sensor, a seismometer, an altimeter, a hydrometer, a decibel meter, a light meter, a thermometer, a wind sensor, or a traffic sensor.

6. The method of claim 4 , wherein one or more of the environmental sensors is a physiological sensor configured to be affixed to a second person.

7. The method of claim 4 , wherein one or more of the environmental sensors is a data feed.

8. The method of claim 7 , wherein the data feed is selected from a group consisting of a stock-market ticker, a weather report, a news feed, a traffic-condition update, a public-health notice, an electronic calendar, and a social network news feed.

9. The method of claim 1 , further comprising:
the one or more processors transmitting a query to an environment sensor for environmental data.

10. The method of claim 1 , wherein one or more of the physiological sensors is configured to be affixed to the person's body.

11. The method of claim 1 , wherein the control parameters specify one or more of a set point for the sensor, an operating range for the sensor, an operating threshold for the sensor, a sampling rate for the sensor, or a sample size for the sensor.

12. The method of claim 1 , wherein the physiological sensors comprise one or more of a heart-rate monitor, a blood-pressure monitor, a pulse oximeter, or an accelerometer, and the physiological data streams comprise one or more of heart-rate data of the person from the heart-rate monitor, blood-pressure data of the person from the blood-pressure monitor, pulse oximetry data of the person from the pulse oximeter, or accelerometer data of the person from the accelerometer.

13. The method of claim 1 , wherein:
the physiological sensors further comprise an electrocardiograph; and
the physiological data streams further comprise electrocardiograph data of the person from the electrocardiograph.

14. The method of claim 1 , wherein:
the physiological sensors further comprise a glucocorticoid meter; and
the physiological data streams further comprise glucocorticoid data of the person from the glucocorticoid meter.

15. The method of claim 1 , wherein:
the physiological sensors further comprise an electromyograph; and
the physiological data streams further comprise electromyograph data of the person from the electromyograph.

16. The method of claim 1 , wherein:
the physiological sensors further comprise a respiration sensor; and
the data streams further comprise respiration data of the person from the respiration sensor.

17. The method of claim 1 , wherein:
the physiological sensors further comprise a galvanic-skin-response sensor; and
the data streams further comprise galvanic-skin-response data of the person from the galvanic-skin-response sensor.

18. An apparatus for querying for self-reported mood or behavior data based on physiological sensor input comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to:
access one or more physiological data streams from one or more physiological sensors, the physiological data streams comprising physiological data of a person, the physiological data comprising at least renal-Doppler data, and one or more of heart-rate data, blood-pressure data, pulse-oximetry data, or accelerometer data;
access a stress model comprising baseline renal-Doppler data, and one or more of baseline heart-rate data of the person, baseline blood-pressure data of the person, baseline pulse-oximetry data of the person, or baseline accelerometer data of the person, wherein the baseline renal-Doppler data measures a stress response of the sympathetic nervous system, and the stress model correlates the baseline renal-Doppler data of the person with one or more of the baseline heart-rate data of the person, the baseline blood-pressure data of the person, the baseline pulse-oximetry data of the person, or the baseline accelerometer data of the person;
analyze each physiological data stream in reference to a corresponding set of control parameters to determine whether one or more of the physiological data streams deviates from the set of control parameters, the set of control parameters being based on the stress model; and
trans

Assignees

• Jain Jawahar
• Marvit David Loren
• Reinhardt Albert H M
• Fujitsu Ltd

Inventors

• Jain Jawahar
• Marvit David Loren
• Reinhardt Albert H M

Classifications

• A61B5/7232

  involving compression of the physiological signal, e.g. to extend the signal recording period · CPC title

• G06F19/3418

  Physics · mapped topic

• A61B5/0022 Primary

  Monitoring a patient using a global network, e.g. telephone networks, internet · CPC title

• A61B2560/0242

  adapted to measure environmental factors, e.g. temperature, pollution · CPC title

• A61B5/165

  Evaluating the state of mind, e.g. depression, anxiety · CPC title