Thanks to the pervasiveness of smart technologies, researchers could aggregate data and investigate user’s activities thus to deliver personalized home-care services. Activity recognition system have been widely developed, however some challenges still need to be addressed. This paper presents a system where information on body movement, vital signs and user indoor location are aggregated to improve the activity recognition. The system was tested in a realistic environment with a total of 3279 instances acquired from ten healthy users. These results encouraged the use of this approach in activity recognition applications, indeed, the overall accuracy values are satisfactory increased.

中文翻译：

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将可穿戴的生理和惯性传感器与室内用户定位网络相结合，以增强活动识别能力

由于智能技术的普及，研究人员可以汇总数据并调查用户的活动，从而提供个性化的家庭护理服务。活动识别系统已经得到了广泛的开发，但是仍然需要解决一些挑战。本文提出了一个系统，该系统将有关人体运动，生命体征和用户室内位置的信息进行汇总，以提高活动识别能力。该系统在现实环境中进行了测试，总共从十个健康用户那里获取了3279个实例。这些结果鼓励在活动识别应用中使用此方法，实际上，总体准确性值令人满意地提高了。