Activity Recognition for Persons With Stroke Using Mobile Phone Technology: Toward Improved Performance in a Home Setting.
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How a diverse research ecosystem has generated new rehabilitation technologies: Review of NIDILRR's Rehabilitation Engineering Research Centers.Fall Detection in Individuals With Lower Limb Amputations Using Mobile Phones: Machine Learning Enhances Robustness for Real-World Applications.The use of assistive technologies after stroke is debunking the myths about the elderly.Activity Recognition in Individuals Walking With Assistive Devices: The Benefits of Device-Specific Models
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Activity Recognition for Persons With Stroke Using Mobile Phone Technology: Toward Improved Performance in a Home Setting.
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2017 nî lūn-bûn
@nan
2017 թուականի Մայիսին հրատարակուած գիտական յօդուած
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2017 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2017年の論文
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2017年論文
@yue
2017年論文
@zh-hant
2017年論文
@zh-hk
2017年論文
@zh-mo
2017年論文
@zh-tw
2017年论文
@wuu
name
Activity Recognition for Perso ...... Performance in a Home Setting.
@ast
Activity Recognition for Perso ...... Performance in a Home Setting.
@en
type
label
Activity Recognition for Perso ...... Performance in a Home Setting.
@ast
Activity Recognition for Perso ...... Performance in a Home Setting.
@en
prefLabel
Activity Recognition for Perso ...... Performance in a Home Setting.
@ast
Activity Recognition for Perso ...... Performance in a Home Setting.
@en
P2093
P2860
P50
P356
P1476
Activity Recognition for Perso ...... Performance in a Home Setting
@en
P2093
Chaithanya K Mummidisetty
Megan K O'Brien
Saninder Kaur
P2860
P356
10.2196/JMIR.7385
P50
P577
2017-05-25T00:00:00Z