Papers
2
Total Citations
6
H-Index
2
About
Yiran Tong is pioneering the field of soft wearable sensing for biomechanics and human performance monitoring, with a focus on muscle energetics and motion pattern recognition. Their research uniquely bridges neural-mechanical interfaces and machine learning to decode complex physiological signals in real time. In their 2025 work on *in-situ* real-time monitoring of muscle energetics, Tong introduced a soft neural-mechanical wearable sensor that tracks metabolic energy conversion during voluntary limb motion—a breakthrough for understanding motion dexterity and endurance. This approach offers a powerful framework for examining the fundamental mechanisms of skeletal muscle energetics, with implications for rehabilitation and athletic training. Complementing this, Tong developed a 1D-CNN classifier that fuses muscle and joint features for swimming pattern recognition, overcoming harsh underwater disturbances that limit single-mode sensing. This innovation advances underwater wearable robot control and competitive sports training. With early citations already accruing for these 2025 publications, Tong’s work is establishing a new paradigm in wearable biomechanics, demonstrating how soft sensing and AI can transform our understanding of human movement and energy efficiency.
Research Focus
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Top Papers
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