Mechanomyography Sensor Array with Pressure Bias System
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Solution Overview
Problem
Existing muscle activity monitoring technologies, such as surface electromyography (sEMG), face challenges including electrode-skin impedance, sensor positioning, and high hardware costs, while mechanomyography (MMG) offers a low-cost, robust alternative but struggles with assessing motor unit activations and is affected by fat layer thickness and motion artifacts.
Innovation Solution
An apparatus featuring an array of spatially distributed mechanomyography sensors with a pressure bias system that modulates contact pressure, combined with electromyography electrodes and pressure sensors, to enhance signal detection and processing, allowing for the determination of muscle activity and neural activity at different depths and contact pressures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If surface electromyography (sEMG) is used for muscle activity monitoring, then electrical activity can be detected, but electrode-skin impedance and sensor positioning challenges arise
Solution Approach 1:
The patent replaces electrical-based sEMG sensing with mechanical-based MMG sensing using contactless or minimal-contact sensors that detect muscle vibrations and movements mechanically, eliminating electrode-skin impedance issues and simplifying positioning requirements
2Ease of manufacture
If mechanomyography (MMG) is used as a low-cost alternative, then hardware costs are reduced and skin preparation is eliminated, but motor unit activation assessment becomes difficult
Solution Approach 1:
The patent divides the sensing function into multiple MMG sensors arranged in arrays, where each sensor captures localized mechanical vibrations. By segmenting the measurement across multiple spatial locations, the system can resolve individual motor unit activations through signal decomposition techniques
Solution Approach 2:
The patent adds spatial dimensionality to MMG measurements by using arrays of sensors distributed across the muscle surface, transforming single-point mechanical detection into multi-dimensional mechanical field mapping, enabling motor unit source localization
3Measurement precision
If MMG sensors are placed on the body surface, then muscle vibrations can be detected, but signal quality is affected by fat layer thickness
Solution Approach 1:
The patent applies different sensing characteristics to different sensor locations in the array, with sensors positioned to optimize detection through varying tissue layers. The system adapts local measurement qualities to compensate for heterogeneous tissue composition including fat layers
4Measurement precision
If accelerometers are used for MMG, then mechanical vibrations are detected with better spectral flatness, but motion artifacts increase during dynamic tasks
Solution Approach 1:
The patent introduces skin or a compliant interface material as an intermediary between the accelerometer and the body surface. This intermediary layer filters high-frequency motion artifacts while preserving the lower-frequency mechanical vibrations generated by muscle contractions
5Reliability
If microphone MMG is used, then robustness to motion artifacts is improved, but detection capability in static conditions may be limited
Solution Approach 1:
The patent combines multiple MMG sensing modalities (accelerometers, microphones, and other vibration sensors) into a hybrid system that leverages the strengths of each modality, achieving both motion artifact robustness and high detection sensitivity across varying task conditions
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
The apparatus improves the accuracy and robustness of muscle activity monitoring by increasing signal amplitude and reducing noise, enabling effective detection of muscle and neural activities, and optimizing gesture detection, particularly for amputees, with adjustable contact pressure enhancing the system's performance.
Implementation Method 1
These mechanical responses are captured in the form of oscillations produced by displacement and dimensional changes of muscle fibres that occur during a contraction
Implementation Method 2
a pressure bias system configured to provide a variation in contact pressure of the mechanomyography sensors to the body surface to receive mechanomyography signals at different levels of applied contact pressure
Data Source
AI summary
An apparatus configured for application to a surface of a body, the apparatus comprising:an array of mechanomyography sensors spatially distributed across a substrate, each mechanomyography sensor configured to detect mechanomyography signals from the body to which the apparatus is applied; and a pressure bias system configured to provide a variation in contact pressure of the mechanomyography sensors to the body surface to receive mechanomyography signals at different levels of applied contact pressure.