Method and system for monitoring and assessing a strength resistance workout

Abstract

Disclosed herein is a system for assessing a strength resistance workout, the system comprising a sensor device configured to measure at least one workout signal relating to measurement data associated with a movement of a weight; associate time data with the at least one workout signal; a user device configured to: receive workout data from the sensor device, the workout data comprising the at least one workout signal and the time data; receive user data provided from the input unit; a server configured to: obtain the workout data and the user data from the user device; analyze the workout data and the user data to assess a user workout according to predetermined workout parameters; generate a feedback notification; and, provide the feedback notification to the user device to facilitate presenting the feedback notification to a user.

1 . A system for assessing a strength resistance workout, the system comprising:
 a sensor device configured to:
 measure at least one workout signal relating to measurement data associated with a movement of a weight; 
 associate time data with the at least one workout signal; 
   a user device configured to:
 receive workout data from the sensor device, the workout data comprising the at least one workout signal and the time data; 
 receive user data provided from the input unit; 
   a server configured to:
 obtain the workout data and the user data from the user device; 
 analyze the workout data and the user data to assess a user workout according to predetermined workout parameters; 
 generate a feedback notification; and, 
 provide the feedback notification to the user device to facilitate presenting the feedback notification to a user. 
   
     
     
         2 . The system according to  claim 1 , wherein the server is further configured to:
 obtain historical workout data;   analyze the historical workout data to determine trends;   recognize patterns in the historical workout data;   generate a personalized recommendation message based on the patterns recognized in the historical workout data; and,   provide the personalized recommendation message to the user device.   
     
     
         3 . The system according to  claim 2 , wherein the personalized recommendation message describes a personalized workout recommendation. 
     
     
         4 . The system according to  claim 1 , wherein the sensor device comprises:
 a connection element for attaching the housing to a weight machine.   
     
     
         5 . The system according to  claim 1 , wherein the server is further configured to:
 generate an initial benchmark workout;   provide the initial benchmark workout to the user device to be presented to the user; and,   collect the workout data associated with the initial benchmark workout.   
     
     
         6 . The system according to  claim 1 , wherein the server is further configured to:
 generate a periodic benchmark workout;   provide the periodic benchmark workout to the user device to be presented to the user; and,   collect the workout data associated with the periodic benchmark workout.   
     
     
         7 . The system according to  claim 1 , wherein the server is further configured to:
 obtain feedback from the user device, wherein the feedback is provided by the user to the user device;   analyze the feedback; and,   adjust the personalized recommendation for the user.   
     
     
         8 . The system according to  claim 1 , wherein the server analyzes the workout data in real-time and provides real-time feedback notifications to provide to the user device. 
     
     
         9 . The system according to  claim 1 , wherein the weights for which measurement data is received are part of a weight stack of a weight machine or of a free weight. 
     
     
         10 . The system according to  claim 1 , wherein the sensor device comprises at least one sensor. 
     
     
         11 . The system according to  claim 10 , wherein the at least one sensor is a distance measuring sensor. 
     
     
         12 . The system according to  claim 10 , wherein the at least one sensor includes an accelerometer. 
     
     
         13 . The system according to  claim 12 , wherein the server is further configured to:
 collect acceleration data from the accelerometer;   divide the acceleration data into a predetermined number of intervals;   apply a Riemann Sum integration to the acceleration data;   determine whether a velocity should be zero;   perform a noise correction to the velocity when noise is detected in the velocity;   provide an output velocity;   read acceleration data received from the accelerometer;   detect a rest phase according to the acceleration data;   calculate a gravity vector; and,   apply the gravity vector to acceleration data.   
     
     
         14 . The system according to  claim 13 , wherein the at least one sensor includes a gyroscope configured to record angular velocity;
 wherein the server is further configured to:   receive the angular velocity from the at least one sensor;   define a horizontal plane according to the gravity vector;   calculate a tilt angle relative to the horizontal plane;   designate a tilt classification of the tilt angle;   generate a feedback notice according to the tilt classification;   provide the feedback notice to the user device.   
     
     
         15 . The system according to  claim 1 , wherein the personalized recommendation message is provided to the user device in real-time during the workout of the user. 
     
     
         16 . A method for assessing in real-time a user workout, the method comprising using at least one processor for:
 obtaining workout data and user data from a user device;   analyzing the workout data and the user data to assess a user workout according to predetermined workout parameters;   generating a feedback notification; and,   providing the feedback notification to the user device to facilitate presenting the feedback notification to a user.   
     
     
         17 . The method according to  claim 16 , further comprising:
 obtaining historical workout data;   analyzing the historical workout data to determine trends;   recognizing patterns in the historical workout data;   generating a personalized recommendation message based on the patterns recognized in the historical workout data; and,   providing the personalized recommendation message to the user device.   
     
     
         18 . The method according to  claim 16 , further comprising:
 generating an initial benchmark workout;   providing the initial benchmark workout to the user device to be presented to the user; and,   collecting the workout data associated with the initial benchmark workout.   
     
     
         19 . The method according to  claim 16 , further comprising:
 generating a periodic benchmark workout;   providing the periodic benchmark workout to the user device to be presented to the user;   collecting the workout data associated with the periodic benchmark workout;   obtaining feedback from the user device, wherein the feedback is provided by the user to the user device;   analyzing the feedback; and,   adjusting the personalized recommendation for the user.   
     
     
         20 . The method according to  claim 16 , further comprising:
 receiving workout data from a sensor device, the workout data comprising the at least one workout signal and the time data; and   receiving the user data provided from an input unit of the user device.