A Smart Wireless IoT Ring for Real-time Keystroke Recognition Using Edge Computing

Enabling a single ring to recognize 3D keystrokes is a daunting challenge, especially for real-time keystrokes recognition. In this work, we integrated edge computing and machine learning algorithms into a microcontroller unit (MCU) of a smart ring so that keystrokes motion can be accurately recognized in real-time. We developed a multi-level decision (MLD) algorithm and embed a lightweight support vector machine (SVM) algorithm to execute computation for keystroke recognition on the edge of the smart ring. With this method, we can reduce the time for data transmission and avoid the data redundancy problem with the huge dispersion calculation workload; thus, improving the real-time performance of the smart ring device. Consequently, the application of this smart ring-based virtual keyboard system has minimum requirements for hardware, such as memory space and computing capacity. This study demonstrates that the use of low-performance chips in future virtual keyboard systems is possible in order to achieve lower development cost, reduced device size, and improved ease of use. The proposed smart ring is expected to provide a novel and convenient technology for real-world human-computer-interface applications in the future.