An Online Swallow Detection Algorithm Based on the Quadratic Variation of Dual-Axis Accelerometry
An Online Swallow Detection Algorithm Based on the Quadratic Variation of Dual-Axis Accelerometry
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DOI：
10.1109/tsp.2010.2043972
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发表时间：
2010-06-01
影响因子：
5.4
通讯作者：
Chau, Tom
中科院分区：
文献类型：
--
作者：
Damouras, Sotirios;Sejdic, Ervin;Chau, Tom
吞咽加速度法是一种新兴的非侵入性吞咽困难筛查工具。然而，由于头部运动、语音和咳嗽引起的污染振动，吞咽事件的自动检测是具有挑战性的。在本文中，我们将加速度信号视为随机扩散，其中运动与漂移有关，吞噬与波动有关。利用这个模型，我们开发了一个基于波动性的燕子事件检测器，它以在线方式对原始加速度信号进行操作。利用来自健康参与者和吞咽困难患者的数据，所提出的检测器实现了与先前提出的燕子分割算法相当的性能，并增加了在线检测和无信号预处理的好处。基于波动率的检测器可用于依赖加速度计信号的其他生物力学应用中的事件识别。
Swallow accelerometry is an emerging tool for noninvasive dysphagia screening. However, the automatic detection of a swallowing event is challenging due to contaminant vibrations arising from head motion, speech and coughing. In this paper, we consider the acceleration signal as a stochastic diffusion where movement is associated with drift and swallowing with volatility. Using this model, we develop a volatility-based swallow event detector that operates on the raw acceleration signal in an online fashion. With data from healthy participants and patients with dysphagia, the proposed detector achieves performance comparable to previously proposed swallow segmentation algorithms, with the added benefit of online detection and no signal pre-processing. The volatility-based detector may be useful for event identification in other biomechanical applications that rely on accelerometry signals.