# US 2020/0401934 A1 · Generated response using artificial intelligence (ai) based on biometric data > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0401934 A1 - Document ID: US20200401934A1 - Status: Published application - Kind: A1 - Application number: 16/448,803 - Filed: 2019-06-21 - Published: 2020-12-24 - Earliest claimed: 2019-06-21 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Craig M. Trim; Jeremy R. Fox; Zachary A. Silverstein; Sarbajit K. Rakshit - Web page: https://patentgrep.com/patent/US20200401934A1 ## CPC - A61B 5/165: {Evaluating the state of mind, e.g. depression, anxiety} - G06N 20/00: Machine learning - A61B 5/0022: {Monitoring a patient using a global network, e.g. telephone networks, internet} - A61B 5/0205: Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition - A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems} - G06N 5/02: Knowledge representation; Symbolic representation - G16H 10/20: for electronic clinical trials or questionnaires - G16H 40/67: for remote operation - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - G16H 50/30: for calculating health indices; for individual health risk assessment - A61B 5/7275: {Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor} - A61B 2503/12: Healthy persons not otherwise provided for, e.g. subjects of a marketing survey - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract An artificial intelligence-based method includes calculating, by a wearable device, a biometric index based on a plurality of biometric indicators associated with a user of the wearable device, based on the biometric index exceeding a threshold, identifying a change in a context of the user, determining whether the calculated biometric index is associated with the change in the context, based on the calculated biometric index being associated with the change, searching for an Internet of Things device available within the context, transmitting a notification to the Internet of Things device requesting assistance to the user, and in response to transmitting the notification, measuring a change in the biometric index. ## Claims ### Claim 1 An artificial intelligence-based method comprising: calculating, by a wearable device, a biometric index based on a plurality of biometric indicators associated with a user of the wearable device; based on the biometric index exceeding a threshold, identifying, by the wearable device, a change in a context of the user; determining, by the wearable device, whether the calculated biometric index is associated with the change in the context; based on the calculated biometric index being associated with the change, searching, by the wearable device, for an Internet of Things device available within the context; transmitting, by the wearable device, a notification to the Internet of Things device requesting assistance to the user; and in response to transmitting the notification, measuring a change in the biometric index. ### Claim 2 (depends on 1) The method of claim 1, wherein determining the biometric intensity index further comprises: capturing, by the wearable device, the plurality of biometric indicators, the plurality of biometric indicators are associated to physiological and behavioral characteristics corresponding to an emotional state of the user; determining, by the wearable device, the biometric index by calculating an overall score based on the captured plurality of biometric indicators; and comparing, by the wearable device, the determined biometric index with a previously obtained baseline for the user. ### Claim 3 (depends on 1) The method of claim 1, wherein identifying the change in the context of the user comprises: receiving, by the wearable device, information regarding the change in the context from surrounding Internet of Things devices. ### Claim 4 (depends on 1) The method of claim 1, wherein determining whether the biometric index is associated with the change in the context comprises: identifying an action performed by the user in response to the change; and matching a history of previous actions performed by the user in response to a similar situation. ### Claim 5 (depends on 1) The method of claim 1, further comprising: matching a history of previous actions performed by the user that had an ameliorative effect on the biometric index. ### Claim 6 (depends on 1) The method of claim 1, further comprising: based on machine learning techniques, predicting a fear-inducing event specific to the user based on a historical data of the user. ### Claim 7 (depends on 1) The method of claim 1, further comprising: based on an Internet of Things device not being available within the context, selecting, by the wearable device, positive and reassuring information regarding the change in the context; and delivering, by the wearable device, the positive and reassuring information to the user. ### Claim 8 An artificial intelligence-based computer system comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising: calculating, by a wearable device, a biometric index based on a plurality of biometric indicators associated with a user of the wearable device; based on the biometric index exceeding a threshold, identifying, by the wearable device, a change in a context of the user; determining, by the wearable device, whether the calculated biometric index is associated with the change in the context; based on the calculated biometric index being associated with the change, searching, by the wearable device, for an Internet of Things device available within the context; transmitting, by the wearable device, a notification to the Internet of Things device requesting assistance to the user; and in response to transmitting the notification, measuring a change in the biometric index. ### Claim 9 (depends on 8) The computer system of claim 8, wherein determining the biometric intensity index further comprises: capturing, by the wearable device, the plurality of biometric indicators, the plurality of biometric indicators are associated to physiological and behavioral characteristics corresponding to an emotional state of the user; determining, by the wearable device, the biometric index by calculating an overall score based on the captured plurality of biometric indicators; and comparing, by the wearable device, the determined biometric index with a previously obtained baseline for the user. ### Claim 10 (depends on 8) The computer system of claim 8, wherein identifying the change in the context of the user comprises: receiving, by the wearable device, information regarding the change in the context from surrounding Internet of Things devices. ### Claim 11 (depends on 8) The computer system of claim 8, wherein determining whether the biometric index is associated with the change in the context comprises: identifying an action performed by the user in response to the change; and matching a history of previous actions performed by the user in response to a similar situation. ### Claim 12 (depends on 8) The computer system of claim 8, further comprising: matching a history of previous actions performed by the user that had an ameliorative effect on the biometric index. ### Claim 13 (depends on 8) The computer system of claim 8, further comprising: based on machine learning techniques, predicting a fear-inducing event specific to the user based on a historical data of the user. ### Claim 14 (depends on 8) The computer system of claim 8, further comprising: based on an Internet of Things device not being available within the context, selecting, by the wearable device, positive and reassuring information regarding the change in the context; and delivering, by the wearable device, the positive and reassuring information to the user. ### Claim 15 An artificial intelligence-based computer program product comprising: a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a device to cause the device to perform a method comprising: calculating, by a wearable device, a biometric index based on a plurality of biometric indicators associated with a user of the wearable device; based on the biometric index exceeding a threshold, identifying, by the wearable device, a change in a context of the user; determining, by the wearable device, whether the calculated biometric index is associated with the change in the context; based on the calculated biometric index being associated with the change, searching, by the wearable device, for an Internet of Things device available within the context; transmitting, by the wearable device, a notification to the Internet of Things device requesting assistance to the user; and in response to transmitting the notification, measuring a change in the biometric index. ### Claim 16 (depends on 15) The computer program product of claim 15, wherein determining the biometric intensity index further comprises: capturing, by the wearable device, the plurality of biometric indicators, the plurality of biometric indicators are associated to physiological and behavioral characteristics corresponding to an emotional state of the user; determining, by the wearable device, the biometric index by calculating an overall score based on the captured plurality of biometric indicators; and comparing, by the wearable device, the determined biometric index with a previously obtained baseline for the user. ### Claim 17 (depends on 15) The computer program product of claim 15, wherein identifying the change in the context of the user comprises: receiving, by the wearable device, information regarding the change in the context from surrounding Internet of Things devices. ### Claim 18 (depends on 15) The computer program product of claim 15, wherein determining whether the biometric index is associated with the change in the context comprises: identifying an action performed by the user in response to the change; and matching a history of previous actions performed by the user in response to a similar situation. ### Claim 19 (depends on 15) The computer program product of claim 15, further comprising: matching a history of previous actions performed by the user that had an ameliorative effect on the biometric index; and based on machine learning techniques, predicting a fear-inducing event specific to the user based on a historical data of the user. ### Claim 20 (depends on 15) The computer program product of claim 15, further comprising: based on an Internet of Things device not being available within the context, selecting, by the wearable device, positive and reassuring information regarding the change in the context; and delivering, by the wearable device, the positive and reassuring information to the user.