3/17/2023 0 Comments Lars earman![]() ![]() Then, we propose a novel method that exploits the "harmful" interference to maximize the subtle signal variation induced by eye blinks. We first quantitatively model the relationship between signal variation and the subtle movements caused by eye blink and interference. In this work, for the first time, we propose a system called BlinkListener to sense the subtle eye blink motion using acoustic signals in a contact-free manner. We find that even the very subtle involuntary head movement induced by breathing can severely interfere with eye blink detection. ![]() ![]() However, it is still very challenging to employ acoustic signals for eye blink detection due to the unique characteristics of eye blink (i.e., subtle, sparse and aperiodic) and severe interference (i.e., from the human target himself and surrounding objects). Promising progress has been achieved in fine-grained human motion sensing such as breathing using acoustic signals. Another trend favoring acoustic sensing is the wide availability of speakers and microphones in commodity devices. Among the wireless signals utilized for sensing, acoustic signals show a unique potential for fine-grained sensing owing to their low propagation speed in the air. On the other hand, wireless sensing without a need for dedicated sensors gains a tremendous amount of attention in recent years. Although traditional camera-based techniques are promising, multiple issues hinder their wide adoption including the privacy concern, strict lighting condition and line-of-sight (LoS) requirements. Eye blink detection plays a key role in many real-life applications such as Human-Computer Interaction (HCI), drowsy driving prevention and eye disease detection. ![]()
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