@howitworkssss: In 2016, two students from the University of Washington created a wearable prototype called SignAloud. This project gained attention through the Lemelson MIT Student Prize at the Massachusetts Institute of Technology. The system uses gloves with motion and flex sensors that detect finger bends and hand movements as a person signs in American Sign Language. The collected data is sent wirelessly to a connected device. There, machine learning software examines the gesture patterns and matches them to a programmed vocabulary. Once identified, the system converts the recognized signs into written text and spoken words almost in real time. While this innovation has great potential to improve communication between deaf and hearing individuals, it has limitations. Sign language also relies on facial expressions, body posture, and complex grammar, which the gloves cannot fully interpret. Therefore, it remains an evolving assistive technology rather than a complete replacement for professional interpreters. Via: YugaTech/YT (This content posted strictly for educational purposes only. No copyright infringement intended. DM for Credit/Removal.) #MIT #Science #space

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Tuesday 10 November 2026 09:58:02 GMT