Neuromuscular system disease can cause severe paralysis and even speech impairments. To communicate with others, the patients can use breathing to encode information. However, traditional solutions only allow patients to output several predefined sentences. Other solutions require patients to interact with the Windows system, which are not suitable for blind paralyzed patients. To address these problems, we present a text input system based on commercial-off-the-shelf RFID devices, named Respiration-Type (ReType). A passive lightweight RFID tag is attached to the user's chest area over the clothes. By interrogating the tag continuously, an RFID reader can output phase data stream, which will be modulated by the chest fluctuation caused by respiration. Based on this phenomenon, we let normal breath and deep breath represent binary 0 and 1, respectively. To extract the feature information related to breath in real time from the noisy phase data stream, we develop a novel algorithm that is robust to noise and baseline drift. To ensure the robustness of decoding, a breath-control model is established for decoding normal breath and deep breath. Comprehensive experiments show that ReType can achieve an average recognition accuracy of 92.22% and is robust against environment changes and user diversity.
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