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- W4386597504 abstract "In Internet of Things (IoT) services, wearable devices have been widely used for gesture recognition applications. Recently, gesture recognition based on high-density surface electromyogram (HD-sEMG) has attracted growing attention because its ability to recognize various gestures and achieve good performance. However, most previous studies based on HD-sEMG focused on the forearm while people prefer wrist-worn IoT devices like smartwatches. Although some studies have used single-end sEMG for wrist-worn gesture recognition, its recognition accuracy needs to be improved. An ideal gesture recognition should balance comfort and accuracy. In this work, we propose and design a gesture recognition system based on wrist-worn HD-sEMG. This wearing method is more intuitive and comfortable to use compared to the forearm-worn method. In the test, our proposed gesture recognition system achieves 98.08% accuracy. Our method facilitates a more comfortable gesture recognition without compromising the accuracy." @default.
- W4386597504 created "2023-09-12" @default.
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- W4386597504 date "2023-08-18" @default.
- W4386597504 modified "2023-09-23" @default.
- W4386597504 title "A Comfortable Wrist-Worn Gesture Recognition System via HD-sEMG" @default.
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- W4386597504 doi "https://doi.org/10.1109/iciea58696.2023.10241817" @default.
- W4386597504 hasPublicationYear "2023" @default.
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