论文标题
消费者可穿戴设备和情感计算以提供健康支持
Consumer Wearables and Affective Computing for Wellbeing Support
论文作者
论文摘要
配备了普遍传感器的可穿戴设备使我们能够在日常生活中监视生理和行为信号。我们建议Wellaff系统能够识别情感状态以获得健康支持。它还包括医疗保健方案，尤其是患有双极疾病的慢性肾脏疾病（CKD）的患者。为了进行大规模的现场研究，我们在对情绪，压力，冥想，睡眠和体育活动识别和分析方面修订了50多个现成的设备。它们的可用性直接来自其拥有的传感器类型以及原始信号的质量和可用性。我们发现没有适合所有目的的多功能设备。使用Empatica E4和Samsung Galaxy手表，我们在数周内录制了11名参与者的生理信号。收集的数据使我们能够训练一个准确认识强烈情感状态的分类器。
Wearables equipped with pervasive sensors enable us to monitor physiological and behavioral signals in our everyday life. We propose the WellAff system able to recognize affective states for wellbeing support. It also includes health care scenarios, in particular patients with chronic kidney disease (CKD) suffering from bipolar disorders. For the need of a large-scale field study, we revised over 50 off-the-shelf devices in terms of usefulness for emotion, stress, meditation, sleep, and physical activity recognition and analysis. Their usability directly comes from the types of sensors they possess as well as the quality and availability of raw signals. We found there is no versatile device suitable for all purposes. Using Empatica E4 and Samsung Galaxy Watch, we have recorded physiological signals from 11 participants over many weeks. The gathered data enabled us to train a classifier that accurately recognizes strong affective states.
