Systems and methods to detect and characterize stress using physiological sensors
A method includes receiving multimodal data collected using at least one wearable device during an assessment window. The method also includes extracting biomarker features from the multimodal data, based on changes in the extracted biomarker features. The method also includes detecting that a stress event occurred during the assessment window. The method also includes accessing a plurality of templates of patterns in biomarker features, wherein a first subset of the templates is associated with unhealthy response to stress and a second subset of the templates is associated with healthy response to stress. The method also includes determining whether the stress event corresponds to a healthy response or an unhealthy response based on similarities between a pattern in the extracted biomarker features and the plurality of templates. The method also includes responsive to the stress event corresponding to an unhealthy response, providing a stress management recommendation.
1 . A method comprising:
collecting physiological data from earbuds including at least one photoplethysmography (PPG) sensor and at least one inertial measurement unit (IMU) during an assessment window;
receiving multimodal data collected using the earbuds during the assessment window;
extracting biomarker features from the multimodal data, the extracted biomarker features corresponding to at least lung motion, motion due to heart pumping, and body appendage motion;
based on changes in the extracted biomarker features, detecting that a stress event occurred during the assessment window;
accessing a plurality of templates of patterns in biomarker features, wherein a first subset of the templates is associated with unhealthy response to stress and a second subset of the templates is associated with healthy response to stress;
determining whether the stress event corresponds to a healthy response or an unhealthy response based on similarities between a pattern in the extracted biomarker features and the plurality of templates; and
responsive to the stress event corresponding to an unhealthy response,
providing a stress management recommendation tailored based on the detected stress event and personalized to an individual wearing the earbuds and associated with at least one other device communicably coupled to the earbuds, the stress management recommendation displayed on the at least one other device, and
initiating a stress management intervention at one or more of the earbuds and the at least one other device based on the stress management recommendation, the stress management intervention comprising one or more of a haptic reminder, an auditory cue, or music.
2 . The method of claim 1 , wherein the multimodal data includes PPG data and IMU data, and one or more of electrocardiogram data and body temperature data.
3 . The method of claim 1 , wherein the at least one other device is one of a watch or a phone.
4 . The method of claim 1 , wherein the extracted biomarker features include one or more of: a heart rate, a time domain heart rate variability, a frequency domain heart rate variability, a non-linear heart rate variability, a breathing rate, an inhalation to exhalation ratio, a depth of breathing, a cardiac output, a stroke volume, a pulse transit time, or a pre-ejection period.
5 . The method of claim 1 , wherein the templates are associated with one or more of an anticipatory reaction, a lack of recovery, a lack of habituation, and repeated exposure.
6 . The method of claim 1 , wherein determining whether the stress event is a healthy response or an unhealthy response further comprises:
for each one of the plurality of templates, determining a similarity score between the pattern in the extracted biomarker features and a respective one of the plurality of templates; and
providing similarity scores and one or more response features associated with the extracted biomarker features as input to a machine learning model, the machine learning model trained to predict whether the stress event is a healthy response or an unhealthy response based on a probability distribution.
7 . The method of claim 6 , wherein the one or more response features include one or more of a level of changes from a baseline, elevation patterns, recovery patterns, an elevation duration, and a total stress event duration.
8 . An apparatus comprising:
at least one processing device configured to:
collect physiological data from earbuds including at least one photoplethysmography (PPG) sensor and at least one inertial measurement unit (IMU) during an assessment window;
receive multimodal data collected using the earbuds during the assessment window;
extract biomarker features from the multimodal data, the extracted biomarker features corresponding to at least lung motion, motion due to heart pumping, and body appendage motion;
based on changes in the extracted biomarker features, detect that a stress event occurred during the assessment window;
access a plurality of templates of patterns in biomarker features, wherein a first subset of the templates is associated with unhealthy response to stress and a second subset of the templates is associated with healthy response to stress;
determine whether the stress event corresponds to a healthy response or an unhealthy response based on similarities between a pattern in the extracted biomarker features and the plurality of templates; and
responsive to the stress event corresponding to an unhealthy response,
provide a stress management recommendation tailored based on the detected stress event and personalized to an individual wearing the earbuds and associated with at least one other device communicably coupled to the earbuds, the stress management recommendation displayed on the at least one other device, and
initiate a stress management intervention at one or more of the earbuds and the at least one other device based on the stress management recommendation, the stress management intervention comprising one or more of a haptic reminder, an auditory cue, or music.
9 . The apparatus of claim 8 , wherein the multimodal data includes PPG data and IMU data, and one or more of electrocardiogram data and body temperature data.
10 . The apparatus of claim 8 , wherein the at least one other device is one of a watch or a phone.
11 . The apparatus of claim 8 , wherein the extracted biomarker features include one or more of: a heart rate, a time domain heart rate variability, a frequency domain heart rate variability, a non-linear heart rate variability, a breathing rate, an inhalation to exhalation ratio, a depth of breathing, a cardiac output, a stroke volume, a pulse transit time, or a pre-ejection period.
12 . The apparatus of claim 8 , wherein the templates are associated with one or more of an anticipatory reaction, a lack of recovery, a lack of habituation, and repeated exposure.
13 . The apparatus of claim 8 , wherein, to determine whether the stress event is a healthy response or an unhealthy response, the at least one processing device is further configured to:
for each one of the plurality of templates, determine a similarity score between the pattern in the extracted biomarker features and a respective one of the plurality of templates; and
provide similarity scores and one or more response features associated with the extracted biomarker features as input to a machine learning model, the machine learning model trained to predict whether the stress event is a healthy response or an unhealthy response based on a probability distribution.
14 . The apparatus of claim 13 , wherein the one or more response features include one or more of a level of changes from a baseline, elevation patterns, recovery patterns, an elevation duration, and a total stress event duration.
15 . A non-transitory computer readable medium containing instructions that when executed cause at least one processor of an electronic device to:
collect physiological data from earbuds including at least one photoplethysmography (PPG) sensor and at least one inertial measurement unit (IMU) during an assessment window;
receive multimodal data collected using the earbuds during the assessment window;
extract biomarker features from the multimodal data, the extracted biomarker features corresponding to at least lung motion, motion due to heart pumping, and body appendage motion;
based on changes in the extracted biomarker features, detect that a stress event occurred during the assessment window;
access a plurality of templates of patterns in biomarker features, wherein a first subset of the templates is associated with unhealthy response to stress and a second subset of the templates is associated with healthy response to stress;
determine whether the stress event corresponds to a healthy response or an unhealthy response based on similarities between a pattern in the extracted biomarker features and the plurality of templates; and
responsive to the stress event corresponding to an unhealthy response,
provide a stress management recommendation tailored based on the detected stress event and personalized to an individual wearing the earbuds and associated with at least one other device communicably coupled to the earbuds, the stress management recommendation displayed on the at least one other device, and
initiate a stress management intervention at one or more of the earbuds and the at least one other device based on the stress management recommendation, the stress management intervention comprising one or more of a haptic reminder, an auditory cue, or music.
16 . The non-transitory computer readable medium of claim 15 , wherein the multimodal data includes PPG data and IMU data, and one or more of electrocardiogram data and body temperature data.
17 . The non-transitory computer readable medium of claim 15 , wherein the at least one other device is one of a watch or a phone.
18 . The non-transitory computer readable medium of claim 15 , wherein the extracted biomarker features include one or more of: a heart rate, a time domain heart rate variability, a frequency domain heart rate variability, a non-linear heart rate variability, a breathing rate, an inhalation to exhalation ratio, a depth of breathing, a cardiac output, a stroke volume, a pulse transit time, or a pre-ejection period.
19 . The non-transitory computer readable medium of claim 15 , wherein the templates are associated with one or more of an anticipatory reaction, a lack of recovery, a lack of habituation, and repeated exposure.
20 . The non-transitory computer readable medium of claim 15 , wherein the instructions when executed cause the at least one processor to determine whether the stress event is a healthy response or an unhealthy response comprise instructions that when executed cause the at least one processor to:
for each one of the plurality of templates, determine a similarity score between the pattern in the extracted biomarker features and a respective one of the plurality of templates; and
provide similarity scores and one or more response features associated with the extracted biomarker features as input to a machine learning model, the machine learning model trained to predict whether the stress event is a healthy response or an unhealthy response based on a probability distribution.