Synergistic Exercise Fatigue Assessment System

Publication ID: 24-11857838_0003_PTD
Published: October 28, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Synergistic Exercise Fatigue Assessment System,” Published Technical Disclosure No. 24-11857838_0003_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857838_0003_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,838.

Summary of the Inventive Concept

A novel system integrating AI, IoT, blockchain, and new materials to provide personalized exercise fatigue tracking and assessment, enabling users to optimize their training and recovery.

Background and Problem Solved

The original patent disclosed a method and device for assessing exercise fatigue, but it had limitations in terms of data security, environmental factor consideration, and material constraints. The new inventive concept addresses these limitations by incorporating synergistic combinations of distinct technologies to create a more powerful and accurate system.

Detailed Description of the Inventive Concept

The system comprises a wearable device with a graphene-based heart rate sensor, an AI-based exercise load computation model, and a blockchain-based data storage module. The AI-based model integrates with the heart rate sensor to calculate a training stress balance (TSB) and the blockchain-based module securely stores the TSB data for personalized fatigue level tracking. The system can also integrate with IoT-enabled environmental data, such as temperature, humidity, air quality, and noise levels, to provide a more comprehensive assessment of exercise fatigue. The graphene-based sensor enables accurate heart rate monitoring during intense exercise, while the blockchain-based module ensures secure and transparent data storage.

Novelty and Inventive Step

The new claims introduce the synergistic combination of AI, IoT, blockchain, and new materials, which is non-obvious and novel compared to the original patent. The integration of these distinct technologies enables a more powerful and accurate system for exercise fatigue assessment and tracking.

Alternative Embodiments and Variations

Alternative embodiments may include using different types of sensors, such as ECG or GPS, or integrating with other data sources, such as social media or health records. Variations may include adapting the system for specific sports or fitness activities, or developing a cloud-based platform for data analysis and visualization.

Potential Commercial Applications and Market

The synergistic exercise fatigue assessment system has significant commercial potential in the fitness and sports industries, particularly in professional sports, elite athletics, and personalized fitness training. The system can be marketed as a premium offering for athletes and fitness enthusiasts seeking to optimize their performance and recovery.

CPC Classifications

SectionClassGroup
A A63 A63B24/0062
A A61 A61B5/02438
A A61 A61B5/1112
A A61 A61B5/1118
G G16 G16H50/30
A A61 A61B2503/10
A A63 A63B2024/0065
A A63 A63B2220/62
A A63 A63B2230/062

Field of Art

Exercise physiology, wearable technology, and biometric monitoring systems, encompassing medical device technologies, fitness tracking, and computational methods for physiological data analysis

Person of Ordinary Skill (PHOSITA) Profile

A professional with expertise in biomedical engineering, computer science, or exercise science, possessing knowledge of sensor technologies, machine learning, data processing algorithms, and physiological monitoring techniques

Obviousness Rationale

A person of ordinary skill would recognize that integrating emerging technologies like AI, blockchain, and advanced sensors into existing exercise fatigue assessment methods represents a predictable technological evolution. The source patent's foundational exercise load computation model provides a clear framework that a skilled practitioner would naturally extend using contemporary technological approaches. The PTD's variations demonstrate standard engineering problem-solving by applying known computational and sensing technologies to enhance an existing exercise monitoring methodology.

Obvious Combinations & Variations

Source Patent Element
Exercise load computation model using heart rate parameters
PTD Variation
AI-enhanced exercise load computation model integrating additional environmental and IoT data
Obviousness Reasoning
Augmenting computational models with additional contextual data represents a predictable optimization technique known in the field of physiological monitoring
Source Patent Element
Heart rate-based fatigue assessment method
PTD Variation
Graphene-based heart rate sensor for improved monitoring accuracy
Obviousness Reasoning
Implementing advanced sensor materials to improve signal precision is a standard engineering approach for enhancing measurement technologies
Source Patent Element
Training stress balance (TSB) calculation method
PTD Variation
Blockchain-based secure data storage and personalized tracking of exercise metrics
Obviousness Reasoning
Applying distributed ledger technologies to secure and manage personal health data represents a logical technological progression in data management systems
Source Patent Element
Exercise heart rate monitoring technique
PTD Variation
IoT-enabled environmental data integration for comprehensive fatigue assessment
Obviousness Reasoning
Expanding physiological monitoring to include environmental context is a predictable extension of existing biometric tracking methodologies
Source Patent Element
Computer-implemented exercise fatigue assessment method
PTD Variation
AI-powered personalized fatigue level recommendations
Obviousness Reasoning
Implementing machine learning for personalized health insights represents a standard application of contemporary computational techniques
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857838 and the disclosed technological variations, a person of ordinary skill in the art would find the proposed exercise fatigue assessment system combinations to be obvious and lacking inventive step. The incremental technological enhancements represented by AI integration, blockchain storage, IoT data incorporation, and advanced sensing technologies constitute predictable variations that would be readily conceived by a skilled practitioner seeking to improve exercise monitoring methodologies.

Original Patent Information

Patent NumberUS 11,857,838
TitleMethod and device for assessing exercise fatigue
Assignee(s)Guangdong COROS Sports Technology Joint Stock Company