BodyBeat:一种移动系统,用于感知非语言的身体声音

Tauhidur Rahman, A. Adams, Mi Zhang, E. Cherry, Bobby Zhou, Huaishu Peng, Tanzeem Choudhury
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引用次数: 173

摘要

在本文中,我们提出了BodyBeat,一个新的移动传感系统,用于捕捉和识别现实生活中各种各样的非言语肢体声音。非言语的身体声音,如进食、呼吸、笑声和咳嗽的声音,包含了关于我们的饮食行为、呼吸生理和情绪的宝贵信息。BodyBeat移动传感系统由一个定制的压电麦克风和一个利用ARM微控制器和Android智能手机的分布式计算框架组成。这款定制的麦克风可以直接从身体表面捕捉细微的身体振动,而不会受到外界声音的干扰。麦克风连接到一个带有悬挂机构的3D打印项圈上。ARM嵌入式系统和Android智能手机对来自麦克风的声音信号进行处理,识别非语音的肢体声音。我们对BodyBeat移动传感系统进行了广泛的评估。我们的研究结果表明,BodyBeat在捕捉和识别不同类型的重要非语音体音方面优于其他现有的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BodyBeat: a mobile system for sensing non-speech body sounds
In this paper, we propose BodyBeat, a novel mobile sensing system for capturing and recognizing a diverse range of non-speech body sounds in real-life scenarios. Non-speech body sounds, such as sounds of food intake, breath, laughter, and cough contain invaluable information about our dietary behavior, respiratory physiology, and affect. The BodyBeat mobile sensing system consists of a custom-built piezoelectric microphone and a distributed computational framework that utilizes an ARM microcontroller and an Android smartphone. The custom-built microphone is designed to capture subtle body vibrations directly from the body surface without being perturbed by external sounds. The microphone is attached to a 3D printed neckpiece with a suspension mechanism. The ARM embedded system and the Android smartphone process the acoustic signal from the microphone and identify non-speech body sounds. We have extensively evaluated the BodyBeat mobile sensing system. Our results show that BodyBeat outperforms other existing solutions in capturing and recognizing different types of important non-speech body sounds.
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