Continuous monitoring of stress using accelerometer data
First Claim
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1. A method comprising, by one or more processors associated with one or more computing devices:
- accessing, by one or more of the processors, one or more data streams from a plurality of sensors, the sensors comprising an accelerometer and one or more of a heart-rate monitor, a blood-pressure monitor, a pulse oximeter, or a mood sensor, wherein;
the data streams comprise accelerometer data of a person from the accelerometer and 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, and self-reported mood data of the person from the mood sensor;
a first data set from the data streams was collected from the person at a first time, the person being engaged in a first activity at the first time; and
a second data set from the data streams was collected from the person at a second time, the person being engaged in a second activity at the second time;
accessing, by one or more of the processors, a stress model comprising baseline renal-Doppler data, baseline accelerometer data, and one or more of baseline heart-rate data, baseline blood-pressure data, baseline pulse-oximetry data, or baseline self-reported mood data, wherein the baseline-renal-Doppler data measures a stress response of the sympathetic nervous system, and wherein the stress model correlates the baseline renal-Doppler data with the baseline accelerometer data and one or more of the baseline heart-rate data, the baseline blood-pressure data, the baseline pulse-oximetry data, or the baseline self-reported mood data;
analyzing, by one or more of the processors, the first data set and second data set with respect to each other and with respect to the stress model; and
determining, by one or more of the processors, a current stress index of the person based on the analysis of the first data set and second data set with respect to each other and with respect to the stress model.
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Abstract
In particular embodiments, a method includes accessing data streams from an accelerometer and one or more of a heart-rate monitor, a blood-pressure monitor, a pulse oximeter, or a mood sensor monitoring a person, analyzing data sets collected from the person when the person is engaged in various activities, and determining a current stress index of the person based on the analysis.
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Citations
54 Claims
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1. A method comprising, by one or more processors associated with one or more computing devices:
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accessing, by one or more of the processors, one or more data streams from a plurality of sensors, the sensors comprising an accelerometer and one or more of a heart-rate monitor, a blood-pressure monitor, a pulse oximeter, or a mood sensor, wherein; the data streams comprise accelerometer data of a person from the accelerometer and 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, and self-reported mood data of the person from the mood sensor; a first data set from the data streams was collected from the person at a first time, the person being engaged in a first activity at the first time; and a second data set from the data streams was collected from the person at a second time, the person being engaged in a second activity at the second time; accessing, by one or more of the processors, a stress model comprising baseline renal-Doppler data, baseline accelerometer data, and one or more of baseline heart-rate data, baseline blood-pressure data, baseline pulse-oximetry data, or baseline self-reported mood data, wherein the baseline-renal-Doppler data measures a stress response of the sympathetic nervous system, and wherein the stress model correlates the baseline renal-Doppler data with the baseline accelerometer data and one or more of the baseline heart-rate data, the baseline blood-pressure data, the baseline pulse-oximetry data, or the baseline self-reported mood data; analyzing, by one or more of the processors, the first data set and second data set with respect to each other and with respect to the stress model; and determining, by one or more of the processors, a current stress index of the person based on the analysis of the first data set and second data set with respect to each other and with respect to the stress model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. An apparatus 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 data streams from a plurality of sensors, the sensors comprising an accelerometer and one or more of a heart-rate monitor, a blood-pressure monitor, a pulse oximeter, or a mood sensor, wherein; the data streams comprise accelerometer data of a person from the accelerometer and 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, and self-reported mood data of the person from the mood sensor; a first data set from the data streams was collected from the person at a first time, the person being engaged in a first activity at the first time; and a second data set from the data streams was collected from the person at a second time, the person being engaged in a second activity at the second time; access a stress model comprising baseline renal-Doppler data, baseline accelerometer data, and one or more of baseline heart-rate data, baseline blood-pressure data, baseline pulse-oximetry data, or baseline self-reported mood data, wherein the baseline-renal-Doppler data measures a stress response of the sympathetic nervous system, and wherein the stress model correlates the baseline renal-Doppler data with the baseline accelerometer data and one or more of the baseline heart-rate data, the baseline blood-pressure data, the baseline pulse-oximetry data, or the baseline self-reported mood data; analyze the first data set and second data set with respect to each other and with respect to the stress model; and determine a current stress index of the person based on the analysis of the first data set and second data set with respect to each other and with respect to the stress model. - View Dependent Claims (20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36)
- one or more processors; and
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37. One or more computer-readable non-transitory storage media embodying software that is operable when executed to:
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access one or more data streams from a plurality of sensors, the sensors comprising an accelerometer and one or more of a heart-rate monitor, a blood-pressure monitor, a pulse oximeter, or a mood sensor, wherein; the data streams comprise accelerometer data of a person from the accelerometer and 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, and self-reported mood data of the person from the mood sensor; a first data set from the data streams was collected from the person at a first time, the person being engaged in a first activity at the first time; and a second data set from the data streams was collected from the person at a second time, the person being engaged in a second activity at the second time; access a stress model comprising baseline renal-Doppler data, baseline accelerometer data, and one or more of baseline heart-rate data, baseline blood-pressure data, baseline pulse-oximetry data, or baseline self-reported mood data, wherein the baseline-renal-Doppler data measures a stress response of the sympathetic nervous system, and wherein the stress model correlates the baseline renal-Doppler data with the baseline accelerometer data and one or more of the baseline heart-rate data, the baseline blood-pressure data, the baseline pulse-oximetry data, or the baseline self-reported mood data; analyze the first data set and second data set with respect to each other and with respect to the stress model; and determine a current stress index of the person based on the analysis of the first data set and second data set with respect to each other and with respect to the stress model. - View Dependent Claims (38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54)
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Specification