Towards Sensing and Sharing Auditory Context Information Using Wearable Device
Towards Sensing and Sharing Auditory Context Information Using Wearable Device
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DOI：
10.1007/978-3-030-43887-6_5
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发表时间：
2019-09
期刊：
影响因子：
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通讯作者：
A. Sashima;M. Kawamoto
中科院分区：
文献类型：
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作者：
A. Sashima;M. Kawamoto
使用可穿戴设备的数据驱动信息服务在医疗保健、医疗保健和教育服务领域引起了关注。在这些服务中，用户的日常行为是用个人身体状态的感知数据来建模的，例如身体运动、心率等。然而，为了更深入地理解人类行为，了解用户的上下文信息也很重要，如周围环境和参与的活动。在本文中，我们描述了从智能手表感知的环境声音数据中提取听觉上下文信息。首先，我们使用智能手表描述了我们的可穿戴环境声音传感系统的原型。然后，我们描述了对系统检测到的声音数据的分析。在研究的第一步，我们将上下文提取过程形式化为多维时间序列数据的无监督分割，并将非负矩阵分解(NMF)和k-均值聚类应用于分割。我们确认，通过分析划分的时期大致符合实际情况。
Data-driven information services using wearable devices have attracted attention in the areas of healthcare, medical care, and educational services. In the services, the users’ daily behaviors are modeled with the sensing data of the physical statuses of individual users, e.g., body movements, heart rates, etc. However, to understand human behaviors more deeply, it is also important to know the context information of the users, such as the surrounding environment and participating activities. In this paper, we describe extracting auditory context information from ambient sound data sensed by smart watches. First, we describe a prototype of our wearable ambient sound sensing system by using smart watches. Then, we describe an analysis of the sound data sensed by the system. We formalize the context extraction process as unsupervised segmentation of multi-dimensional time-series data and apply non-negative matrix factorization (NMF) and k-means clustering to the segmentation at the first step of the study. We confirm that the periods segmented by the analysis roughly correspond to actual contexts.