Patent Issued for Suggesting behavioral adjustments based on physiological responses to stimuli on electronic devices (USPTO 11568166): Verily Life Sciences LLC
2023 FEB 16 (NewsRx) -- By a
Patent number 11568166 is assigned to
The following quote was obtained by the news editors from the background information supplied by the inventors: “Contemporary research has begun exploring how stimuli presented by electronic devices affect the health state. Such research has considered emotion as a predictor of media selection, an outcome of media exposure, a mediator of other psychological/behavioral outcomes resulting from media exposure, etc. For example, several studies have examined the emotional consequences of using social media (e.g., photo-sharing social networking services, video-sharing social networking services, and micro-blogging social networking services). These studies have shown that the use of social media can cause positive and negative feelings, which can facilitate or hinder the development of social capital and social connectedness.
“The drawings depict various embodiments for the purpose of illustration only. Those skilled in the art will recognize that alternative embodiments may be employed without departing from the principles of the technology. Accordingly, while specific embodiments are shown in the drawings, the technology is amenable to various modifications.”
In addition to the background information obtained for this patent, NewsRx journalists also obtained the inventors’ summary information for this patent: “Ubiquitous use of electronic devices, particularly in the context of social media, is known to be negatively linked with physical, mental, and emotional health. Accordingly, entities have begun developing healthcare-focused computer programs that can automatically identify, monitor, and promote different aspects of physical, mental, and emotional well-being. Some computer programs expressly solicit feedback directly from individuals (also referred to as “subjects” or “patients”), for example, via manually populated forms. Other computer programs continually track behavior along multiple dimensions without requiring input from the individuals. For example, a computer program may monitor interactions with a social media application that resides on a mobile phone. As another example, a computer program may monitor interactions with a calling application or a messaging application that resides on a mobile phone.
“Classification algorithms can then be applied by the computer program to detect deviations from routine patterns. A classification algorithm may be designed to identify deviations in the frequency with which an individual interacts with an application, the time spent interacting with the application, the digital activities performed using the application, etc. By applying the classification algorithms, the computer program can automatically assess the health state based on health characteristics inferred from these behaviors. Health characteristics can include, for example, estimated sleep duration, physical activities, communication activities, and social interactions.
“However, these computer programs cannot capture much of the contextual resolution necessary to fully understand the health implications of various stimuli. For instance, little is known about which stimuli presented by an electronic device actually cause an individual to experience physiological responses, either positive or negative. Consequently, actions cannot be taken to actively prevent the individual from performing those activities that negatively impact the health state. Similarly, actions cannot be taken to actively encourage the individual to perform those activities that positively impact the health state.
“Introduced here, therefore, are health management platforms able to monitor changes in the health state of an individual based on the context of digital activities performed by, or involving, the individual. More specifically, a health management platform can examine physiological data associated with an individual to identify a physiological response (also referred to as a “physiological event”) and then identify a stimulus presented by an electronic device that caused the physiological response. The term “stimulus” can refer to any digital content shown by the electronic device or any digital activity involving the electronic device.
“The physiological response may correspond to one or more values in the physiological data that exceed a predetermined threshold, match a predetermined pattern, etc. In some embodiments, the individual is prompted to specify whether the physiological response is a positive physiological response or a negative physiological response. Thus, the individual may provide feedback that indicates whether the stimulus resulted in an upward shift in health or a downward shift in health. Physiological responses that result in upward shifts in health may be referred to as “positive physiological responses,” while physiological responses that result in downward shifts in health may be referred to as “negative physiological responses.” The terms “health” and “health state,” meanwhile, can refer to physical health, mental health, emotional health, or any combination thereof.”
The claims supplied by the inventors are:
“1. A non-transitory computer-readable medium with instructions stored thereon that, when executed by a processor, cause the processor to perform operations comprising: acquiring physiological data generated by a first electronic device that monitors physical activity of an individual; detecting a physiological event by parsing the physiological data to discover a subset of the physiological data that matches a predetermined pattern; acquiring, from a second electronic device, contextual data that includes one or more screenshots documenting one or more interactions with a computer program executing on the second electronic device by the individual; identifying, based on an analytical function, a stimulus expected to be responsible for causing the physiological event by examining the contextual data to identify a screenshot that is temporally correlated with the physiological event; generating a digital record that associates the stimulus with the physiological event; and storing the digital record in a personalized stimuli profile associated with the individual.
“2. The non-transitory computer-readable medium of claim 1, wherein said acquiring the contextual data comprises: generating a signal in response to detecting the physiological event; and transmitting the signal to the second electronic device, wherein receipt of the signal causes the electronic device to capture the screenshot.
“3. The non-transitory computer-readable medium of claim 1, wherein the first electronic device is a wearable electronic device, and wherein the second electronic device is a mobile phone.
“4. The non-transitory computer-readable medium of claim 1, wherein the physiological data includes values for pulse rate, electrodermal activity, or any combination thereof.
“5. The non-transitory computer-readable medium of claim 1, the operations further comprising: generating a notification that requests the individual provide feedback indicating whether the physiological event corresponds to an upward shift in health or a downward shift in health; transmitting the notification to the first electronic device, the second electronic device, or another electronic device accessible to the individual; and receiving the feedback.
“6. The non-transitory computer-readable medium of claim 5, the operations further comprising: detecting another instance of the stimulus by examining the contextual data; determining that the other instance of the stimulus will exist for an interval of time; and performing, based on the feedback, an action with respect to the other instance of the stimulus.
“7. The non-transitory computer-readable medium of claim 6, wherein the feedback specifies that the stimulus resulted in an upward shift in health, and wherein the action includes promoting exposure of the individual to the other instance of the stimulus.
“8. The non-transitory computer-readable medium of claim 6, wherein the feedback specifies that the stimulus resulted in a downward shift in health, and wherein the action includes inhibiting exposure of the individual to the other instance of the stimulus.
“9. The non-transitory computer-readable medium of claim 1, wherein the analytical function is configured to isolate one or more representations of the stimulus in the contextual data and categorize the one or more representations into at least one type of stimulus.
“10. A computer-implemented method comprising: acquiring, by a health management platform, physiological data generated by a first electronic device that monitors physical activity of an individual; detecting, by the health management platform, an occurrence of a physiological event by examining the physiological data to discover one or more values that match a predetermined pattern or exceed a predetermined threshold; acquiring, by the health management platform, contextual data generated by a second electronic device that monitors digital activities of the individual on the second electronic device, wherein the contextual data digitally represents the digital activities; identifying, by the health management platform, a stimulus responsible for provoking the physiological event by implementing an analytical function that examines a first portion of the contextual data that temporally corresponds to the physiological event in order to isolate a representation of the stimulus; determining, by the health management platform, whether the physiological event corresponds to an upward shift in health or a downward shift in health; detecting, by the health management platform, another instance of the stimulus by examining a second portion of the contextual data; and performing, based on an outcome of said determining, an action with respect to the other instance of the stimulus.
“11. The computer-implemented method of claim 10, wherein the health management platform resides on the second electronic device.
“12. The computer-implemented method of claim 10, wherein the health management platform resides on a network-connected server system accessible to the second electronic device across a network.
“13. The computer-implemented method of claim 10, wherein the physiological event results in an upward shift in health, and wherein said performing comprises: promoting exposure of the individual to the other instance of the stimulus.
“14. The computer-implemented method of claim 10, wherein the physiological event results in a downward shift in health, and wherein said performing comprises: inhibiting exposure of the individual to the other instance of the stimulus.
“15. The computer-implemented method of claim 10, wherein said determining comprises: analyzing input provided by the individual that indicates whether the physiological event corresponds to an upward shift in health or a downward shift in health.
“16. A computer-implemented method comprising: acquiring, by a processor, physiological data generated by a first electronic device that monitors physical activity of an individual; identifying, by the processor, an occurrence of a physiological event by examining the physiological data, wherein the occurrence of the physiological event corresponds to a series of values in the physiological data that match a predetermined pattern or exceed a predetermined threshold; causing, by the processor in response to said identifying, a second electronic device to capture a screenshot of a computer program through which the individual performs a digital activity, so as to capture evidence of the digital activity performed by the individual substantially contemporaneously with identification of the physiological event experienced by the individual; analyzing, by the processor, the screenshot to discover a characteristic of the digital activity; and generating, by the processor, a digital record that associates the physiological event with the characteristic of the digital activity.
“17. The computer-implemented method of claim 16, wherein the processor resides in the second electronic device.
“18. The computer-implemented method of claim 16, wherein the physiological data includes a time-varying series of values representative of discrete measurements of pulse rate, electrodermal activity (EDA), skin temperature, or sweat level.”
URL and more information on this patent, see: Rainaldi, Erin. Suggesting behavioral adjustments based on physiological responses to stimuli on electronic devices.
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