Browsing Faculty Contributions by Subject "Fall detection"

Now showing items 1-6 of 6

    • A Reconfigurable Connected Health Platform Using ZYNQ System on Chip 

      Abunahia D.G.; Ismail T.A.; Abou Al Ola H.R.; Amira A.; Ait Si Ali A.; ... more authors ( Springer , 2018 , Book chapter)
      This paper presents a reconfigurable connected health platform for fall and cardiac disease detection to be used in smart home environments using Shimmer sensing device and ZYNQ System on Chip (SoC) platform. The system ...

    • High-resolution time-frequency distributions for fall detection 

      Amin M.G.; Zhang Y.D.; Boashash B. ( SPIE , 2015 , Conference Paper)
      In this paper, we examine the role of high-resolution time-frequency distributions (TFDs) of radar micro-Doppler signatures for fall detection. The work supports the recent and rising interest in using emerging radar ...

    • Iot-based fall and ecg monitoring system: Wireless communication system based firebase realtime database 

      Al-Kababji, Ayman; Shidqi, Lisan; Boukhennoufa, Issam; Amira, Abbes; Bensaali, Faycal; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)
      Monitoring elderlies living alone has been a rising issue that caregivers are interested in solving since many elderlies are at risk of experiencing a fall. In the absence of urgent help, serious consequences may occur. ...

    • Multiple comparator classifier framework for accelerometer-based fall detection and diagnostic 

      Gibson, Ryan M.; Amira, Abbes; Ramzan, Naeem; Casaseca-de-la-Higuera, Pablo; Pervez, Zeeshan ( Elsevier Ltd , 2016 , Article)
      There are a significant number of high fall risk individuals who are susceptible to falling and sustaining severe injuries. An automatic fall detection and diagnostic system is critical for ensuring a quick response with ...

    • Radar fall detection using principal component analysis 

      Jokanovic, Branka; Amin, Moeness; Ahmad, Fauzia; Boashash, B. ( SPIE , 2016 , Conference Paper)
      Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. ...

    • Radar fall detectors: A comparison 

      Erol, Baris; Amin, Moeness; Ahmad, Fauzia; Boashash, B. ( SPIE , 2016 , Conference Paper)
      Falls are a major cause of accidents in elderly people. Even simple falls can lead to severe injuries, and sometimes result in death. Doppler fall detection has drawn much attention in recent years. Micro-Doppler signatures ...