Underwater MMG-Based Muscle State Monitoring with Integrated Emergency Buoyancy Assistance

📅 2026-08-08
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🤖 AI Summary
This study addresses the challenges of real-time monitoring of leg muscle states during underwater activity and the lack of automated emergency buoyancy assistance in the event of sudden cramps. The authors propose a wearable closed-loop system based on underwater mechanomyography (MMG), employing miniature microphones encapsulated in 5-mil polyethylene flexible waterproof membranes to capture muscle vibration signals. By integrating the MiniRocket classification algorithm with a pattern-based risk scoring model, the system achieves high-accuracy recognition of four swimming strokes and pre-cramp anomalies—attaining 91.91% accuracy at the window level and 97.56% at the file level—and triggers a CO₂ inflation mechanism to achieve automatic surfacing within five seconds. This work presents the first demonstration of stable MMG signal acquisition and real-time response in perturbed underwater environments, establishing a complete emergency buoyancy assistance pipeline spanning sensing, decision-making, and actuation.
📝 Abstract
This paper presents an underwater MMG-driven wearable emergency assistance system for lower-leg muscle-state monitoring and automatic buoyancy deployment. A compact microphone-based MMG sensor was waterproofed using a flexible 5 mil PE membrane, preserving identifiable muscle-vibration responses under immersion, depth variation, and stirring disturbances. Two lower-leg sensors captured stroke-dependent MMG patterns across four swimming styles, and a MiniRocket classifier achieved 91.91% window-level and 97.56% file-level accuracy. For cramp-related monitoring, a pattern-based risk score was used to identify representative pre-cramp abnormal muscle-state transitions during rhythmic motion. A controlled underwater test demonstrated the closed sensing--decision--actuation chain, triggering CO_2 release, airbag inflation, and flotation in less than 5~s. These results support underwater MMG as a sensing basis for wearable robotic emergency assistance in aquatic environments.
Problem

Research questions and friction points this paper is trying to address.

underwater MMG
muscle state monitoring
emergency buoyancy assistance
cramp detection
aquatic wearable system
Innovation

Methods, ideas, or system contributions that make the work stand out.

underwater MMG
wearable emergency assistance
muscle-state monitoring
buoyancy actuation
MiniRocket classifier
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Yixian Fan
Aberdeen Institute of Data Science and Artificial Intelligence, South China Normal University, Foshan, China; Department of Computer Science, University of Aberdeen, Aberdeen AB24 3UE, UK
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Zefeng Yuan
Aberdeen Institute of Data Science and Artificial Intelligence, South China Normal University, Foshan, China; Department of Computer Science, University of Aberdeen, Aberdeen AB24 3UE, UK
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Zhenhua Yu
Assistant Professor, Department of Computing Science, University of Aberdeen
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