Papapanagiotou Vasileios, Diou Christos, van den Boer Janet, Mars Monica, Delopoulos Anastasios
Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:6485-6488. doi: 10.1109/EMBC.2016.7592214.
Monitoring of human eating behaviour has been attracting interest over the last few years, as a means to a healthy lifestyle, but also due to its association with serious health conditions, such as eating disorders and obesity. Use of self-reports and other non-automated means of monitoring have been found to be unreliable, compared to the use of wearable sensors. Various modalities have been reported, such as acoustic signal from ear-worn microphones, or signal from wearable strain sensors. In this work, we introduce a new sensor for the task of chewing detection, based on a novel photoplethysmography (PPG) sensor placed on the outer earlobe to perform the task. We also present a processing pipeline that includes two chewing detection algorithms from literature and one new algorithm, to process the captured PPG signal, and present their effectiveness. Experiments are performed on an annotated dataset recorded from 21 individuals, including more than 10 hours of eating and non-eating activities. Results show that the PPG sensor can be successfully used to support dietary monitoring.
在过去几年中，对人类饮食行为的监测一直备受关注，这既是实现健康生活方式的一种手段，也是因为它与饮食失调和肥胖等严重健康状况有关。与使用可穿戴传感器相比，使用自我报告和其他非自动化监测手段被发现是不可靠的。已经报道了各种方式，例如来自耳戴式麦克风的声学信号，或来自可穿戴应变传感器的信号。在这项工作中，我们基于放置在外耳垂上的新型光电容积脉搏波描记法（PPG）传感器，为咀嚼检测任务引入了一种新传感器，以执行该任务。我们还提出了一个处理流程，其中包括来自文献的两种咀嚼检测算法和一种新算法，用于处理捕获的PPG信号，并展示它们的有效性。对从21个人记录的带注释数据集进行了实验，包括超过10小时的进食和非进食活动。结果表明，PPG传感器可以成功用于支持饮食监测。
