Myoelectric Sensor Exercise Guidance Using Muscle State Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current fitness guidance methods, such as personal trainers and exercise monitoring devices, fail to accurately determine local muscle exercise states and are costly and inconvenient, leading to suboptimal exercise guidance.
Innovation Solution
An exercise guidance method using myoelectric sensors to collect and process muscle fatigue and excitement levels, calculating time-frequency parameters, and employing a vector machine algorithm to determine muscle states, generating guidance information for users through a wearable device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If heart-rate monitoring devices are used to determine exercise levels, then exercise monitoring can be performed, but the measurement precision of local muscle exercise states deteriorates
Solution Approach 1:
The patent divides the monitoring system into multiple myoelectric sensors positioned at different muscle groups (quadriceps, hamstrings, gastrocnemius, etc.), allowing independent measurement of each local muscle's exercise state. This segmentation enables precise local muscle monitoring rather than overall body monitoring through heart rate alone.
Solution Approach 2:
The patent replaces the mechanical/physiological heart-rate monitoring system with an electrical signal-based myoelectric sensing system. By detecting electrical signals from muscle contractions (EMG), the system directly measures local muscle exercise states with higher precision than indirect heart-rate-based methods.
2Reliability
If personal trainers provide exercise guidance, then exercise guidance quality improves, but the cost increases
Solution Approach 1:
The system enables users to perform self-monitoring and self-guided exercise through the myoelectric sensor device that automatically detects muscle activation patterns, provides real-time feedback, and guides exercise execution without requiring external personal trainer intervention, thereby reducing cost while maintaining guidance quality.
Solution Approach 2:
The system implements real-time feedback loops where myoelectric signals are continuously monitored, analyzed for muscle activation patterns, and used to provide immediate guidance corrections to the user, replicating the quality of personal trainer feedback through automated electronic feedback mechanisms.
3Ease of operation
If exercise monitoring devices are used, then exercise monitoring is achieved, but ease of operation deteriorates
Solution Approach 1:
The monitoring system is segmented into independent, modular myoelectric sensor units that can be individually applied to different muscle groups. Each sensor is a simple standalone component, making the overall system easier to operate and adjust compared to integrated complex monitoring devices.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides accurate and personalized exercise guidance, reducing costs and inconvenience while improving user experience by accurately reflecting local muscle states and providing real-time feedback.
Implementation Method 1
receiving myoelectric parameters of a user collected by a plurality of myoelectric sensors
Implementation Method 2
reconstituting and denoising said myoelectric parameters by wavelet transform method
Data Source
AI summary
The present disclosure provides an exercise guidance method and an exercise guidance device. The method includes receiving myoelectric parameters of a user collected by a plurality of myoelectric sensors, determining a current exercise state of the user based on myoelectric parameters, generating exercise guidance information based on the current exercise condition, and sending the exercise guidance information to a terminal.