Method and system of optimizing and personalizing resistance force in an exercise

Abstract

In one aspect, a method useful for automating, personalizing and optimizing a resistance force in an exercise across time and space, the system including the step of providing an exercise machine. The method includes the step of providing a biometric sensor couples with a user performing an exercise on the exercise machine. The method includes the step of obtaining a user's profile data, wherein the user's profile data comprises a user's history of exercising on the exercise machine. The method includes the step of obtaining a user input into an exercise resistance controller of the exercise machine. The method includes the step of, while the user performs one or more repetitions of the exercise on the exercise machine, obtaining a real-time data of a set of parameters of the one or more repetitions of the exercise on the exercise machine. The method includes the step of obtaining a user's biometric data. The method includes the step of based on the real-time data, user's biometric data, the user input into an exercise resistance controller and the user's profile data. The method includes the step of automatically adjusting the exercise resistance controller of the exercise machine within the three-dimensional (3D) geospatial motion of the user and across time of the exercise.

What is claimed as new and desired to be protected by Letters Patent of the United States is: 
     
         1 . A method useful for automating, personalizing and optimizing a resistance force in an exercise across time and space, the method comprising:
 providing an exercise machine;   providing a biometric sensor coupled with a user performing an exercise on the exercise machine;   obtaining a user's profile data, wherein the user's profile data comprise user's history of exercising on the exercise machine;   obtaining a user input into an exercise resistance controller of the exercise machine;   while the user performs one or more repetitions of the exercise on the exercise machine:
 obtaining a real-time data of a set of parameters of the one or more repetitions of the exercise on the exercise machine; 
 obtaining a user's biometric data; and 
   based on the real-time data, user's biometric data, the user input into an exercise resistance controller and the user's profile data:
 automatically adjusting the exercise resistance controller of the exercise machine within the three-dimensional (3D) geospatial motion of the user and across time of the exercise. 
   
     
     
         2 . The method of  claim 1 , wherein the user's profile data comprises a user's personal profile. 
     
     
         3 . The method of  claim 2 , wherein the user's personal data comprises a user's race, a user's gender, a user's height or a user's weight. 
     
     
         4 . The method of  claim 3 , wherein the user's personal profile comprises a user's medical history data. 
     
     
         5 . The method of  claim 3 , wherein the user's profile data comprises user's exercise history for the exercise. 
     
     
         6 . The method of  claim 4 , wherein the real-time data comprises a user inputs, machine-sensor data and biometric raw data. 
     
     
         7 . The method of  claim 1 , wherein the real-time data of a set of parameters of the one or more repetitions of the exercise on the exercise machine comprises an accelerometer data of the exercise machine and a resistance force sensor of the exercise machine. 
     
     
         8 . The method of  claim 1 , wherein the biometric sensor comprises a first wearable device that comprises a heart rate monitor and a second wearable device that comprises a surface Electromyographical (sEMG) sensor. 
     
     
         9 . The method of  claim 1 , wherein the user input into an exercise resistance controller of the exercise machine comprises an initial resistance force level of the exercise. 
     
     
         10 . The method of  claim 1 , wherein the exercise machine comprises a stationary bicycle, and wherein the exercise resistance controller manages the force resistance to the user peddling. 
     
     
         11 . A method useful for automating, personalizing and optimizing a resistance force in an exercise across time and space, the method comprising:
 providing a first exercise machine;   providing a second exercise machine;   providing a first biometric sensor coupled with a first user performing an exercise on the first exercise machine;   providing a second biometric sensor coupled with a second user performing an exercise on the second exercise machine;   obtaining a first user's profile data, wherein the first user's profile data comprises a first user's history of exercising on the exercise machine;   obtaining a second user's profile data, wherein the second user's profile data comprises a second user's history of exercising on the exercise machine;   obtaining a first user input into a first exercise resistance controller of the first exercise machine;   obtaining a second user input into second exercise resistance controller of the second exercise machine;   while the first user and the second user perform one or more repetitions of the exercise on the first exercise machine and the second exercise machine:
 obtaining a real-time data of a set of parameters of the one or more repetitions of the exercise on the first exercise machine and the second exercise machine; 
 obtaining a first user's biometric data; 
 obtaining a second user's biometric data; and 
   based on the, real-time data, the first user's biometric data, the second user's biometric data, the first user input into the first exercise resistance controller, the second user input into the second exercise resistance controller, the first user's profile data, the second user's profile data:   automatically adjusting the first exercise resistance controller of the first exercise machine within the three-dimensional (3D) geospatial motion of the first user and across time of the exercise; and   automatically adjusting the second exercise resistance controller of the second exercise machine within the three-dimensional (3D) geospatial motion of the second user and across time of the exercise.   
     
     
         12 . The method of  claim 11 , wherein the first exercise machine comprises a stationary bicycle, and wherein the first exercise resistance controller manages the first force resistance to the first user peddling. 
     
     
         13 . The method of  claim 12 , wherein the second exercise machine comprises a stationary bicycle, and wherein the second exercise resistance controller manages the second force resistance to the second user peddling. 
     
     
         14 . The method of  claim 11 , wherein the first exercise machine comprises a first bicep curl machine, and wherein the first exercise resistance controller manages the first force resistance to the first user performing a bicep curl. 
     
     
         15 . The method of  claim 12 , wherein the second exercise machine comprises a second bicep curl machine, and wherein the second exercise resistance controller manages the second force resistance to the second user performing a bicep curl. 
     
     
         16 . A computing useful for automating, personalizing and optimizing a resistance force in an exercise across time and space, the system comprising:
 a processor;   a memory containing instructions when executed on the processor, causes the processor to perform operations that:
 provide a first exercise machine; 
 provide a second exercise machine; 
 provide a first biometric sensor coupled with a first user performing an exercise on the first exercise machine: 
 provide a second biometric sensor coupled with a second user performing an exercise on the second exercise machine; 
 obtain a first user's profile data, wherein the first user's profile data comprises a first user's history of exercising on the exercise machine; 
 obtain a second user's profile data, wherein the second user's profile data comprises a second user's history of exercising on the exercise machine; 
 obtain a first user input into a first exercise resistance controller of the exercise machine; 
 obtain a second user input into a second exercise resistance controller of the second exercise machine; 
 while the first user and the second user perform one or more repetitions of the exercise on the first exercise machine and the second exercise machine:
 obtain a real-time data of a set of parameters of the one or more repetitions of the exercise on the first exercise machine and the second exercise machine; 
 obtain a first user's biometric data; 
 obtain a second user's biometric data; and 
 
 based on the real-time data, the first user's biometric data, the second user's biometric data, the first user input into the first exercise resistance controller, the second user input into the second exercise resistance controller, the first user's profile data, the second user's profile data:
 automatically adjust the first exercise resistance controller of the first exercise machine within the three-dimensional (3D) geospatial motion of the first user and across time of the exercise; and 
 automatically adjust the second exercise resistance controller of the second exercise machine within the three-dimensional (3D) geospatial motion of the second user and across time of the exercise.