A Panoramic Study of Fall Detection Technologies
Falls are a major risk of injury for elderly aged 65 or over, blind people, people with balance disorder and leg weakness. In this regard, assistive technology which aims to identify fall events at real time can reduce the rate of impairments and mortality. This study offer a literature research reference value for bioengineers for further research. Much of the past and the current fall detection research, the vital signals features and the way features are extracted and fed to a classifier are introduced. The study concludes with an assessment of the current technologies highlighting their critical limitations along with suggestions for future research direction in this rapidly developing field of study.
Keywords: Fall detection, elderly monitoring, accelerometer, tilt, gyroscope, vision-based, ambience-base, pressure sensor, SVM, KNN, classification.
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ABOUT THE AUTHORS
Laiali Almazaydeh
Laiali Almazaydeh has received a B.S. in Computer Science from Al Hussein Bin Talal University, M.S. in Computer Information Systems from The Arab Academy for Banking and Financial in 2003 and 2007, respectively, and Ph.D. from University of Bridgeport from U.S.A in 2009. Currently she is working as an Assidtant Professor at Al Hussein Bin Talal University. In February 2011, Almazaydeh was invited to the United Nations in Manhattan to lead panels aimed at attracting more women into the field of science and technology. And the American Association of University Women asked her talk about the status of women and girls rights globally, in celebration of the 100th anniversary of International Women’s Day. Recently Laiali has been awarded financial scholarship from Upsilon Pi Epsilon, the international honors society for computing and information sciences, she was selected based on her superlative academic record, extracurricular activities, and recommendations from academic advisers. Laiali has published more than 25 journal and conference papers, her current research interests are in wireless sensor networks and Human Computer Interaction.
Khitam Al-Otoon
Faculty of Engineering, Al-Hussein Bin Talal University Ma'an, Jordan
Ayman Al Dmour
Faculty of Information Technology, Al-Hussein Bin Talal University Ma'an, Jordan
Khaled Elleithy
Computer Science and Engineering Department, University of Bridgeport Bridgeport, CT, USA
Laiali Almazaydeh
Laiali Almazaydeh has received a B.S. in Computer Science from Al Hussein Bin Talal University, M.S. in Computer Information Systems from The Arab Academy for Banking and Financial in 2003 and 2007, respectively, and Ph.D. from University of Bridgeport from U.S.A in 2009. Currently she is working as an Assidtant Professor at Al Hussein Bin Talal University. In February 2011, Almazaydeh was invited to the United Nations in Manhattan to lead panels aimed at attracting more women into the field of science and technology. And the American Association of University Women asked her talk about the status of women and girls rights globally, in celebration of the 100th anniversary of International Women’s Day. Recently Laiali has been awarded financial scholarship from Upsilon Pi Epsilon, the international honors society for computing and information sciences, she was selected based on her superlative academic record, extracurricular activities, and recommendations from academic advisers. Laiali has published more than 25 journal and conference papers, her current research interests are in wireless sensor networks and Human Computer Interaction.
Khitam Al-Otoon
Faculty of Engineering, Al-Hussein Bin Talal University Ma'an, Jordan
Ayman Al Dmour
Faculty of Information Technology, Al-Hussein Bin Talal University Ma'an, Jordan
Khaled Elleithy
Computer Science and Engineering Department, University of Bridgeport Bridgeport, CT, USA
