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从数据采集到数据融合:使用移动设备识别日常生活活动的全面综述与路线图

From Data Acquisition to Data Fusion: A Comprehensive Review and a Roadmap for the Identification of Activities of Daily Living Using Mobile Devices.

作者信息

Pires Ivan Miguel, Garcia Nuno M, Pombo Nuno, Flórez-Revuelta Francisco

机构信息

Instituto de Telecomunicações, University of Beira Interior, 6201-001 Covilhã, Portugal.

Altranportugal, 1990-096 Lisbon, Portugal.

出版信息

Sensors (Basel). 2016 Feb 2;16(2):184. doi: 10.3390/s16020184.

Abstract

This paper focuses on the research on the state of the art for sensor fusion techniques, applied to the sensors embedded in mobile devices, as a means to help identify the mobile device user's daily activities. Sensor data fusion techniques are used to consolidate the data collected from several sensors, increasing the reliability of the algorithms for the identification of the different activities. However, mobile devices have several constraints, e.g., low memory, low battery life and low processing power, and some data fusion techniques are not suited to this scenario. The main purpose of this paper is to present an overview of the state of the art to identify examples of sensor data fusion techniques that can be applied to the sensors available in mobile devices aiming to identify activities of daily living (ADLs).

摘要

本文着重研究应用于移动设备中嵌入式传感器的传感器融合技术的最新进展,以此作为帮助识别移动设备用户日常活动的一种手段。传感器数据融合技术用于整合从多个传感器收集的数据,提高识别不同活动算法的可靠性。然而,移动设备存在诸多限制,例如内存低、电池续航时间短和处理能力低,一些数据融合技术并不适用于这种情况。本文的主要目的是概述最新进展,以识别可应用于移动设备中现有传感器的传感器数据融合技术示例,旨在识别日常生活活动(ADL)。

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