Supporting patient monitoring using activity recognition with a smartphone
Supporting patient monitoring using activity recognition with a smartphone
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DOI：
10.1109/iswcs.2010.5624490
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发表时间：
2010-11
期刊：
影响因子：
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通讯作者：
Sian Lun Lau;I. König;K. David;Baback Parandian;Christine Carius-Düssel;Martin Schultz
中科院分区：
文献类型：
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作者：
Sian Lun Lau;I. König;K. David;Baback Parandian;Christine Carius-Düssel;Martin Schultz
在我们的工作中，我们设想使用上下文感知来补充和改善远程医疗服务。一个具体的例子是识别用于治疗和治疗的身体活动（PA）。语境的使用可以通过帮助医疗人员和患者获得隐含信息来提供更新的服务。我们介绍的上下文感知远程监控助理（CARMA），应用程序实现的MATRIX远程医疗中间件平台。它能够使用非侵入式设备识别患者的活动。在本文中，一个运动识别方法进行了研究，使用智能手机内置加速度计。通过实验比较了分类算法、特征以及特征提取条件的组合对识别精度的影响。实验结果表明，该方法是可行的，并显示出很大的潜力。
In our work we envision the use of context awareness to complement and improve telemedicine services. One concrete example is the recognition of physical activity (PA) for therapies and treatments. The usage of context can provide newer services by assisting medical professionals and patients to obtain implicit information. We introduce the Context Aware Remote Monitoring Assistant (CARMA), an application implemented on the MATRIX telemedicine middleware platform. It enables activity recognition for patients using non-obtrusive devices. In this paper, a movement recognition approach is investigated using a smartphone with a built-in accelerometer. Experiments were carried out to compare the influences of classification algorithms, features and combinations for feature extraction conditions on the recognition accuracy. The obtained results indicated that the approach is viable and shows much potential.