This study investigates the potential of using smartwatches with built-in microphone sensors for monitoring coughs and detecting various cough types. We conducted a study involving 32 participants and collected 9 hours of audio data in a controlled manner. Afterward, we processed this data using a structured approach, resulting in 223 positive cough samples. We further improved the dataset through augmentation techniques and employed a specialized 1D CNN model. This model achieved an impressive accuracy rate of 98.49% while non-walking and 98.2% while walking, showing smartwatches can detect cough. Moreover, our research successfully identified four distinct types of coughs using clustering techniques.

中文翻译：

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利用智能手表麦克风传感器进行咳嗽检测和分类

这项研究调查了使用内置麦克风传感器的智能手表监测咳嗽和检测各种咳嗽类型的潜力。我们进行了一项涉及 32 名参与者的研究，并以受控方式收集了 9 小时的音频数据。随后，我们使用结构化方法处理这些数据，得到 223 个阳性咳嗽样本。我们通过增强技术进一步改进了数据集，并采用了专门的一维 CNN 模型。该模型在非步行时达到了 98.49% 的准确率，在步行时达到了 98.2% 的准确率，这表明智能手表可以检测咳嗽。此外，我们的研究使用聚类技术成功识别了四种不同类型的咳嗽。