Towards a wearable system for continuous monitoring of sniffing and panting in dogs

R. Brugarolas, M. T. Agcayazi, S. Yuschak, D. Roberts, B. Sherman, A. Bozkurt
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引用次数: 9

Abstract

Although numerous advances have been made in instrumental odor detection systems, these still cannot match the efficient sampling, odor discrimination, agile mobility and the olfactory acuity of odor detection dogs. A limiting step in using dogs to detect odors is the subjectivity of the translation of odor information processed by the dog to its handler. We present our preliminary efforts towards a wireless wearable system for continuous auscultation of respiratory behavior by recording internal sounds at the neck and chest by means of a commercially available electronic stethoscope to provide objective decision support for handlers. We have identified discrete features of sniffing and panting in the time domain and utilize event duration, event rate, event mean energy, and the number of consecutive events in a row to build a decision tree classifier. Since feature extraction requires segmentation of individual sniffing and panting events, we developed an adaptive method using short-time energy contour and an adaptive threshold. The performance of the system was evaluated on recordings from a Greyhound and a Labrador Retriever and achieved high classification accuracies.
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研制一种可穿戴系统,用于连续监测狗的嗅探和喘气
尽管在仪器气味检测系统方面取得了许多进展,但这些仍然无法与气味检测犬的高效采样,气味识别,灵活的机动性和嗅觉敏锐度相匹配。使用狗来检测气味的一个限制步骤是狗向其处理者翻译气味信息的主观性。我们介绍了我们对无线可穿戴系统的初步努力,该系统通过使用市售电子听诊器记录颈部和胸部的内部声音来连续听诊呼吸行为,为处理人员提供客观的决策支持。我们已经确定了在时域内嗅探和喘息的离散特征,并利用事件持续时间、事件率、事件平均能量和连续事件的数量来构建决策树分类器。由于特征提取需要对单个嗅探和喘气事件进行分割,我们开发了一种使用短时间能量轮廓和自适应阈值的自适应方法。通过灰狗和拉布拉多猎犬的录音对系统的性能进行了评估,并取得了很高的分类准确性。
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