Systems and methods for determining and using health conditions based on machine learning algorithms and a smart vital device

Abstract

In some instances, the disclosure provides a method performed by a smart vital device. The method comprises receiving sensor information indicating one or more health characteristics associated with an individual, wherein the sensor information comprises audio information indicating audio signals from a surrounding environment and temperature information indicating temperature readings from the surrounding environment, determining one or more health audio characteristics of the individual based on inputting the audio signals into one or more health condition machine learning datasets, determining one or more health temperature characteristics of the individual based on the temperature readings from the surrounding environment, determining one or more health conditions of the individual based on the one or more health audio characteristics and the one or more health temperature characteristics, and outputting the one or more health conditions of the individual.

1 . A method, comprising:
 obtaining, by a smart vital device, sensor information indicating one or more health characteristics associated with an individual, wherein the sensor information comprises audio information indicating audio signals from a surrounding environment and temperature information indicating temperature readings from the surrounding environment;   determining, by the smart vital device, one or more health audio characteristics of the individual based on inputting the audio signals into one or more health condition machine learning models;   determining, by the smart vital device, one or more health temperature characteristics of the individual based on the temperature readings from the surrounding environment;   determining, by the smart vital device, a plurality of health conditions of the individual based on the one or more health audio characteristics and the one or more health temperature characteristics;   based on the plurality of health conditions and one or more weights associated with the plurality of health conditions, determining, by the smart vital device, a medical condition of the individual; and   outputting, by the smart vital device, the plurality of health conditions and the medical condition of the individual.   
     
     
         2 . The method of  claim 1 , further comprising:
 providing the plurality of health conditions of the individual and the medical condition of the individual to an enterprise computing system.   
     
     
         3 . The method of  claim 1 , further comprising:
 determining, based on the temperature information, that the temperature readings indicate a temperature of a particular body part of the individual, and   wherein determining the plurality of health conditions of the individual is based on the temperature of the particular body part of the individual.   
     
     
         4 . The method of  claim 1 , further comprising:
 inputting the temperature information into the one or more health condition machine learning models to generate temperature data, and   wherein determining the plurality of health conditions of the individual is based on the temperature data from the one or more health condition machine learning models.   
     
     
         5 . The method of  claim 1 , wherein the sensor information further comprises humidity information indicating a humidity reading of the surrounding environment, and wherein determining the plurality of health conditions of the individual is further based on the humidity information. 
     
     
         6 . The method of  claim 1 , wherein the sensor information further comprises a captured image of the individual, wherein the method further comprises:
 determining, by the smart vital device, one or more image characteristics of the individual based on inputting the captured image into the one or more health condition machine learning models, and   wherein determining the plurality of health conditions is further based on the one or more image characteristics.   
     
     
         7 . The method of  claim 1 , further comprising:
 determining, by the smart vital device and based on the sensor information and the medical condition, a degree of accuracy associated with the medical condition; and   outputting, by the smart vital device, the degree of accuracy.   
     
     
         8 . The method of  claim 1 , wherein determining the medical condition of the individual further comprises:
 inputting the plurality of health conditions and the one or more weights associated with the plurality of health conditions into one or more second machine learning models to determine the medical condition of the individual.   
     
     
         9 . The method of  claim 1 , wherein each of the plurality of health conditions is in a Boolean format, and wherein each of the plurality of health conditions is associated with a weight from the one or more weights. 
     
     
         10 . The method of  claim 1 , wherein outputting the plurality of health conditions and the medical condition of the individual comprises providing a vocal notification indicating the medical condition of the individual. 
     
     
         11 . The method of  claim 1 , further comprising:
 receiving a plurality of audio files indicating coughs and/or sneezes;   receiving a plurality of infrared images indicating elevated temperature readings of a plurality of individuals; and   training the one or more health condition machine learning models based on the plurality of received audio files and the plurality of received infrared images.   
     
     
         12 . The method of  claim 1 , further comprising:
 determining whether a user device of the individual is within a proximity of the smart vital device; and   based on determining the user device is within the proximity of the smart vital device, providing, to the user device, instructions to cause display of the plurality of health conditions and the medical condition of the individual on the user device.   
     
     
         13 . The method of  claim 12 , further comprising:
 receiving an indication that the individual has been authenticated by an enterprise computing system, wherein the indication indicates the user device, and   wherein determining whether the user device of the individual is within the proximity of the smart vital device is based on the received indication.   
     
     
         14 . A smart vital device, comprising:
 one or more sensors;   one or more processors; and   a non-transitory computer-readable medium having processor-executable instructions stored thereon, wherein the processor-executable instructions, when executed by the one or more processors, facilitate:
 obtaining, using the one or more sensors, sensor information indicating one or more health characteristics associated with an individual, wherein the sensor information comprises audio information indicating audio signals from a surrounding environment and temperature information indicating temperature readings from the surrounding environment; 
 determining one or more health audio characteristics of the individual based on inputting the audio signals into one or more health condition machine learning models; 
 determining one or more health temperature characteristics of the individual based on the temperature readings from the surrounding environment; 
 determining a plurality of health conditions of the individual based on the one or more health audio characteristics and the one or more health temperature characteristics; 
 based on the plurality of health conditions and one or more weights associated with the plurality of health conditions, determining a medical condition of the individual; and 
 outputting the plurality of health conditions and the medical condition of the individual. 
   
     
     
         15 . The smart vital device of  claim 14 , wherein the processor-executable instructions, when executed by the one or more processors, further facilitate:
 providing the plurality of health conditions of the individual and the medical condition of the individual to an enterprise computing system.   
     
     
         16 . The smart vital device of  claim 14 , wherein the processor-executable instructions, when executed by the one or more processors, further facilitate:
 determining, based on the temperature information, that the temperature readings indicate a temperature of a particular body part of the individual, and   wherein determining the plurality of health conditions of the individual is based on the temperature of the particular body part of the individual.   
     
     
         17 . The smart vital device of  claim 14 , wherein the processor-executable instructions, when executed by the one or more processors, further facilitate:
 inputting the temperature information into the one or more health condition machine learning models to generate temperature data, and   wherein determining the plurality of health conditions of the individual is based on the temperature data from the one or more health condition machine learning models.   
     
     
         18 . The smart vital device of  claim 14 , wherein the sensor information further comprises humidity information indicating a humidity reading of the surrounding environment, and wherein determining the plurality of health conditions of the individual is further based on the humidity information. 
     
     
         19 . The smart vital device of  claim 14 , wherein the processor-executable instructions, when executed by the one or more processors, further facilitate:
 determining, based on the sensor information and the medical condition, a degree of accuracy associated with the medical condition; and   outputting the degree of accuracy.   
     
     
         20 . A non-transitory computer-readable medium having processor-executable instructions stored thereon, wherein the processor-executable instructions, when executed, facilitate:
 obtaining sensor information indicating one or more health characteristics associated with an individual, wherein the sensor information comprises audio information indicating audio signals from a surrounding environment and temperature information indicating temperature readings from the surrounding environment;   determining one or more health audio characteristics of the individual based on inputting the audio signals into one or more health condition machine learning models;   determining one or more health temperature characteristics of the individual based on the temperature readings from the surrounding environment;   determining a plurality of health conditions of the individual based on the one or more health audio characteristics and the one or more health temperature characteristics;   based on the plurality of health conditions and one or more weights associated with the plurality of health conditions, determining a medical condition of the individual; and   outputting the plurality of health conditions and the medical condition of the individual.