Wearable system for monitoring strength training
First Claim
1. An exercise monitoring system comprising:
- a communications network;
a wearable transducer configured to generate physiologic data associated with movement of a wearer, and to form a communication link with the communications network;
a system memory in which command instructions are stored;
a user interface operably connected to the computer; and
a system processor configured to execute the command instructions toreceive the generated physiologic data,identify a type of movement indicated by the generated physiological data,analyze the received physiologic data with a multilayer perceptron, support vector machine, or hidden Markov (MSH) model based on the idenfied type of movement,model the analyzed physiologic data, andgenerate feedback based on a comparison of the model and a stored exercise object.
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Accused Products
Abstract
An exercise monitoring method and system in one embodiment includes a communications network, a wearable transducer configured to generate physiologic data associated with movement of a wearer, and to form a communication link with the communications network, a system memory in which command instructions are stored, a user interface operably connected to the computer, and a system processor configured to execute the command instructions to receive the generated physiologic data, analyze the received physiologic data with a multilayer perceptron/support vector machine/hidden Markov (MSH) model, model the analyzed physiologic data, and generate feedback based on a comparison of the model and a stored exercise object.
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Citations
20 Claims
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1. An exercise monitoring system comprising:
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a communications network; a wearable transducer configured to generate physiologic data associated with movement of a wearer, and to form a communication link with the communications network; a system memory in which command instructions are stored; a user interface operably connected to the computer; and a system processor configured to execute the command instructions to receive the generated physiologic data, identify a type of movement indicated by the generated physiological data, analyze the received physiologic data with a multilayer perceptron, support vector machine, or hidden Markov (MSH) model based on the idenfied type of movement, model the analyzed physiologic data, and generate feedback based on a comparison of the model and a stored exercise object. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method of monitoring physiologic data associated with an exercise routine performed by a user, comprising:
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generating physiologic data using at least one wearable transducer worn by the user; receiving the generated physiologic data at a system processor; identifying a type of movement indicated by the received physiological data using the system processor; analyzing the received physiologic data using the system processor based on the identified type of movement; modeling the analyzed physiologic data using the system processor; and generating feedback based on a comparison of the model and a stored exercise object using the system processor. - View Dependent Claims (13, 14, 15, 16)
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17. A method of monitoring physiologic data associated with an exercise routine performed by a user, comprising:
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selecting an exercise routine using an input/output device; receiving an exercise object for a model exercise routine associated with the selected exercise routine at a system processor; transmitting physiologic data associated with sensed physiologic conditions of a user to the system processor using a wearable transducer worn by the user; identifying a type of movement indicated by the received physiological data using the system processor; analyzing the transmitted physiologic data using the system processor based on the identified type of movement; generating a model based on the analyzed transmitted physiologic data using the system processor; comparing the exercise object with the model using the system processor; and generating selective feedback based on the comparison using the system processor. - View Dependent Claims (18, 19, 20)
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Specification