EMBridge: Enhancing Gesture Generalization from EMG Signals through Cross-Modal Representation Learning

EMBridge is a new AI framework that enhances gesture recognition from EMG biosignals by aligning them with high-quality structured data from videos and images. The technology enables zero-shot gesture generalization on low-power wearable devices, potentially advancing human-computer interaction applications.

• →EMBridge improves EMG signal processing by leveraging cross-modal representation learning from visual data.
• →The framework enables zero-shot gesture recognition without requiring specific training for new gestures.
• →The technology targets low-power wearable devices for continuous gesture prediction.
• →Surface electromyography (sEMG) provides a cost-effective alternative to vision-based gesture recognition.
• →The approach bridges bio-signals with structured high-quality visual modalities for better semantic understanding.