Fall Detection and Efficiency Enhancement via Wearable Technology
Author:
Affiliation:
1. TIM Akilli Kiyafetleri ve Bilisim Teknolojisi A.S.
2. Istanbul Technical University,Electronical, and Communicational Engineering Department
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10525679/10525701/10525997.pdf?arnumber=10525997
Reference12 articles.
1. The WEKA data mining software: An update;Hall;ACM SIGKDD Explorations Newsletter,2009
2. Human motion tracking for rehabilitation—A survey
3. Statistical Database of Human Motion Recognition Using Wearable IoT—A Review
4. The FARSEEING real-world fall repository: a large-scale collaborative database to collect and share sensor signals from real-world falls;Klenk;Eur Rev Aging Phys Act,2016
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