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An on-line swallow detection algorithm based on the quadratic variation of dual-axis accelerometry (2010)
| Content Provider | CiteSeerX |
|---|---|
| Author | Damouras, Sotirios Steele, Catriona M. Chau, Tom |
| Abstract | Abstract—Swallow accelerometry is an emerging tool for non-invasive 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 compa-rable to previously proposed swallow segmentation algorithms, with the added benefit of online detection and no signal pre-pro-cessing. The volatility-based detector may be useful for event identification in other biomechanical applications that rely on accelerometry signals. Index Terms—Event detection, quadratic variation, semi-mar-tingales, swallow accelerometry. I. |
| File Format | |
| Journal | IEEE Trans Signal Process |
| Language | English |
| Publisher Date | 2010-01-01 |
| Access Restriction | Open |
| Subject Keyword | Quadratic Variation Dual-axis Accelerometry On-line Swallow Detection Algorithm Online Detection Acceleration Signal Automatic Detection Swallow Segmentation Algorithm Added Benefit Healthy Participant Online Fashion Swallowing Event Abstract Swallow Accelerometry Signal Pre-pro-cessing Accelerometry Signal Event Identification Raw Acceleration Signal Volatility-based Swallow Event Detector Non-invasive Dysphagia Screening Biomechanical Application Swallow Accelerometry Contaminant Vibration Index Term Event Detection Volatility-based Detector Head Motion Stochastic Diffusion |
| Content Type | Text |
| Resource Type | Article |
