Using Wearable Activity Type Detection to Improve Physical Activity Energy Expenditure Estimation.
Using Wearable Activity Type Detection to Improve Physical Activity Energy Expenditure Estimation.
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DOI：
10.1145/1864349.1864396
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发表时间：
2010-09
期刊：
影响因子：
--
通讯作者：
Rosenberger M
中科院分区：
文献类型：
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作者：
Albinali F;Intille SS;Haskell W;Rosenberger M
Accurate, real-time measurement of energy expended during everyday activities would enable development of novel health monitoring and wellness technologies. A technique using three miniature wearable accelerometers is presented that improves upon state-of-the-art energy expenditure (EE) estimation. On a dataset acquired from 24 subjects performing gym and household activities, we demonstrate how knowledge of activity type, which can be automatically inferred from the accelerometer data, can improve EE estimates by more than 15% when compared to the best estimates from other methods.
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DOI：
10.1097/00005768-199805000-00021
发表时间：
1998-05-01
期刊：
MEDICINE AND SCIENCE IN SPORTS AND EXERCISE
影响因子：
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作者：
Freedson, PS;Melanson, E;Sirard, J
通讯作者：
Sirard, J
影响因子：
3.3
作者：
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通讯作者：
Freedson, Patty
影响因子：
3.3
作者：
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通讯作者：
Chen, Kong Y.
DOI：
10.1097/00005768-200009001-00009
发表时间：
2000-09-01
期刊：
MEDICINE AND SCIENCE IN SPORTS AND EXERCISE
影响因子：
--
作者：
Ainsworth, BE;Haskell, WL;Leon, AS
通讯作者：
Leon, AS
DOI：
10.1249/mss.0b013e3181a24536
发表时间：
2009-09-01
期刊：
MEDICINE AND SCIENCE IN SPORTS AND EXERCISE
影响因子：
--
作者：
Bonomi, Alberto G.;Goris, Annelies H. C.;Westerterp, Klaas R.
通讯作者：
Westerterp, Klaas R.