Active and passive mobile sensing has garnered much attention in recent years. In this paper, we focus on chronic pain measurement and management as a case application to exemplify the state of the art. We present a consolidated discussion on the leveraging of various sensing modalities along with modular server-side and on-device architectures required for this task. Modalities included are: activity monitoring from accelerometry and location sensing, audio analysis of speech, image processing for facial expressions as well as modern methods for effective patient self-reporting. We review examples that deliver actionable information to clinicians and patients while addressing privacy, usability, and computational constraints. We also discuss open challenges in the higher level inferencing of patient state and effective feedback with potential directions to address them. The methods and challenges presented here are also generalizable and relevant to a broad range of other applications in mobile sensing.

中文翻译：

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利用多模态传感实现移动健康：慢性疼痛的案例回顾

近年来，主动和被动移动传感引起了广泛关注。在本文中，我们重点关注慢性疼痛的测量和管理作为案例应用来举例说明最先进的技术。我们对利用各种传感模式以及该任务所需的模块化服务器端和设备上架构进行了综合讨论。包括的方式包括：通过加速度测量和位置传感进行活动监测、语音音频分析、面部表情图像处理以及有效患者自我报告的现代方法。我们回顾了向临床医生和患者提供可操作信息，同时解决隐私、可用性和计算限制的示例。我们还讨论了更高层次的患者状态推断和有效反馈方面的开放挑战以及解决这些问题的潜在方向。这里提出的方法和挑战也是通用的，并且与移动传感领域的广泛其他应用相关。