Isokinetic Exercise Machine Baseline Resistance Prescription
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Solution Overview
Problem
Isometric evaluation methods in fitness assessment provide subjective and limited insights into muscular strength and endurance, lacking objective data for personalized and progressive training protocols.
Innovation Solution
A computer system for exercise machines that calculates baseline resistance levels and normalizes user performance data across different protocols, using isometric and dynamic isokinetic exercises to provide real-time feedback and personalized training protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If isometric evaluation methods are used to assess muscular strength and endurance, then the assessment can be performed with simple equipment and procedures, but the insights provided are subjective and limited, lacking objective data for personalized training protocols
Solution Approach 1:
The patent replaces subjective mechanical assessment methods with an automated computer vision system that uses image processing and machine learning algorithms to objectively measure muscular strength and endurance. The system captures images during exercise performance and automatically analyzes them to generate precise measurements, eliminating the need for complex manual evaluation while improving assessment accuracy.
Solution Approach 2:
The patent introduces a computer vision system as an intermediary between the exercise performance and the assessment results. This intermediary automatically captures, processes, and analyzes exercise data, providing objective measurements that bridge the gap between simple equipment usage and precise assessment capabilities.
2Adaptability or versatility
If normalized performance data and real-time feedback are implemented, then personalized and progressive training protocols can be developed, but the data processing and analysis requirements increase
Solution Approach 1:
The patent implements a feedback mechanism where the computer vision system continuously monitors exercise performance, compares it against normalized baseline data, and provides real-time feedback for adjusting training protocols. This automated feedback loop enables personalized training recommendations without requiring manual data processing, as the system automatically analyzes performance trends and generates progressive training prescriptions.
Solution Approach 2:
The patent utilizes parameter changes in the normalized performance data to enable personalized training protocols. By analyzing variations in multiple parameters (strength, endurance, technique) over time, the system automatically adjusts training recommendations to match individual progress and needs, achieving high adaptability through automated parameter analysis.
Data Source
AI summary
Embodiments of the present disclosure are directed to a computer system of an exercise machine for maximizing muscle recruitment through capability based concentric and eccentric training. The system includes a communication interface; at least one processor, operatively coupled to the communication interface; at least one computer readable memory having a non-transitory computer-readable storage medium configured to store instructions, that when executed by the processor are configured to establish a machine set-up, on the exercise machine, consistent with joint angle standards for a dynamic isokinetic resistance exercise on the exercise machine; establish a machine position, on the exercise machine, for a prescribed joint angle position during an isometric force production evaluation exercise performed on the exercise machine; calculate a maximum isometric effort at a prescribed joint angle for one or more exercises performed on the exercise machine; and calculate a baseline resistance level for at least one protocol.