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  Fall detection by built-in tri-accelerometer of smartphone

He, Y., Li, Y., & Bao, S.-D. (2012). Fall detection by built-in tri-accelerometer of smartphone. In 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics (pp. 184-187). Piscataway, NJ, USA: IEEE.

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 Creators:
He, Y1, Author           
Li, Y, Author
Bao, S-D, Author
Affiliations:
1Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China, ou_persistent22              

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 Abstract: In this study, a fall detection system based on the data acquired from a waist-mounted smartphone has been developed in a real-time environment. The built-in tri-accelerometer was utilized to collect the information about body movement. At the same time, the smartphone is able to classify the data for activity recognition. Body motion can be classified into five different patterns, i.e. vertical activity, lying, sitting or static standing, horizontal activity and fall. If a fall is suspected, an automatic Multimedia Messaging Service (MMS) will be sent to pre-selected people, with information including the time, GPS coordinate, and Google map of suspected fall location. The major advantage of the proposed system is the use of smartphone which is readily available to most people.

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 Dates: 2012-01
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1109/BHI.2012.6211540
 Degree: -

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Title: IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2012)
Place of Event: Hongkong, China
Start-/End Date: 2012-01-05 - 2012-01-07

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Title: 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics
Source Genre: Proceedings
 Creator(s):
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Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 184 - 187 Identifier: ISBN: 978-1-4577-2177-9