Identifying typical physical activity on smartphone with varying positions and orientations.
Identifying typical physical activity on smartphone with varying positions and orientations.
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识别智能手机上不同位置和方向的典型身体活动
DOI：
10.1186/s12938-015-0026-4
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发表时间：
2015-04-13
影响因子：
3.9
通讯作者：
Ayoola I
中科院分区：
文献类型：
--
作者：
Miao F;He Y;Liu J;Li Y;Ayoola I
背景传统的活动识别解决方案由于昂贵的成本和使用众多传感器的不便而不能广泛应用。本文旨在借助智能手机的内置传感器自动识别身体活动，而不受对人体牢固附着的任何限制。方法通过引入一种判断手机是否在口袋中的方法，对7个受试者的6个位置采集的数据进行调查，选择对方向不敏感的5个信号进行活动分类。利用决策树(J48)、朴素贝叶斯和序列最小优化(SMO)对静态、行走、奔跑、上楼和下楼五种活动进行识别。结果基于8,097个活动数据的实验结果表明，J48分类器的识别性能最好，平均识别率为89.6%，可以作为最优的在线分类器。结论利用智能手机内置的传感器识别典型的身体活动是可行的，而不受任何牢固连接的限制。
BackgroundTraditional activity recognition solutions are not widely applicable due to a high cost and inconvenience to use with numerous sensors. This paper aims to automatically recognize physical activity with the help of the built-in sensors of the widespread smartphone without any limitation of firm attachment to the human body.MethodsBy introducing a method to judge whether the phone is in a pocket, we investigated the data collected from six positions of seven subjects, chose five signals that are insensitive to orientation for activity classification. Decision trees (J48), Naive Bayes and Sequential minimal optimization (SMO) were employed to recognize five activities: static, walking, running, walking upstairs and walking downstairs.ResultsThe experimental results based on 8,097 activity data demonstrated that the J48 classifier produced the best performance with an average recognition accuracy of 89.6% during the three classifiers, and thus would serve as the optimal online classifier.ConclusionsThe utilization of the built-in sensors of the smartphone to recognize typical physical activities without any limitation of firm attachment is feasible.
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DOI：
10.1109/titb.2010.2051955
发表时间：
2010-09-01
影响因子：
--
作者：
Khan, Adil Mehmood;Lee, Young-Koo;Kim, Tae-Seong
通讯作者：
Kim, Tae-Seong
DOI：
10.1109/tsmcc.2009.2032660
发表时间：
2010-01-01
期刊：
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS
影响因子：
--
作者：
Pantelopoulos, Alexandros;Bourbakis, Nikolaos G.
通讯作者：
Bourbakis, Nikolaos G.
影响因子：
8.5
作者：
Kwon, Yongjin;Kang, Kyuchang;Bae, Changseok
通讯作者：
Bae, Changseok
影响因子：
3.3
作者：
Staudenmayer, John;Pober, David;Freedson, Patty
通讯作者：
Freedson, Patty
利用智能手机内置运动传感器进行身体活动识别
影响因子：
2.3
作者：
He, Yi;Li, Ye
通讯作者：
Li, Ye