April 26, 2024IEEE Internet of Things Journal

Intelligent Wearable System With Motion and Emotion Recognition Based on Digital Twin Technology

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FYFeng YuNanyang Technological University CYChenyu YuHohai University ZTZhangyuan TianWuhan Textile University

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Implication

Experimental evaluation demonstrates multimodal motion and emotion recognition in digital human interaction, highlighting utility for intelligent healthcare and virtual reality.

Key Points

High classification accuracy of 97.04% is achieved on the UCI-HAR dataset using the three-branch spatial-temporal feature extraction network, outperforming standard benchmarks.
Assessment of the intelligent wearable system incorporates a 120,000-sample electroencephalogram emotion classification dataset, supporting robust multidimensional monitoring.
May enable real-time information interaction between physical users and virtual avatars through digital twin technology, advancing intelligent healthcare and virtual reality systems.

Cite This Study

Yu et al. (2024) studied this question.

synapsesocial.com/papers/68e6d587b6db6435876529fc https://doi.org/10.1109/jiot.2024.3394244

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Implication

Experimental evaluation demonstrates multimodal motion and emotion recognition in digital human interaction, highlighting utility for intelligent healthcare and virtual reality.

Intelligent Wearable System With Motion and Emotion Recognition Based on Digital Twin Technology

Discussion

Member takes

Implication

Key Points

Cite This Study

Intelligent Wearable System With Motion and Emotion Recognition Based on Digital Twin Technology

Discussion

Member takes

Implication

Key Points

Cite This Study

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