Literature DB >> 19163185

Real-time signal processing of accelerometer data for wearable medical patient monitoring devices.

Matt Van Wieringen1, J Eklund.   

Abstract

Elderly and other people who live at home but required some physical assistance to do so are often more susceptible injury causing falls in and around their place of residence. In the event that a fall does occur, as a direct result of a previous medical condition or the fall itself, these people are typically less likely to be able to seek timely medical help without assistance. The goal of this research is to develop a wearable sensor device that uses an accelerometer for monitoring the movement of the person to detect falls after they have occurred in order to enable timely medical assistance. The data coming from the accelerometer is processed in real-time in the device and sent to a remote monitoring station where operators can attempt to make contact with the person and/or notify medical personnel of the situation. The ADXL330 accelerometer is contained within a Nintendo WiiMote controller, which forms the basis of the wearable medical sensor. The accelerometer data can then be sent via Bluetooth connection and processed by a local gateway processor. If a fall is detected, the gateway will then contact a remote monitoring station, on a cellular network, for example, via satellite, and/or through a hardwired phone or Internet connection. To detect the occurrence of ta fall, the accelerometer data is passed through a matched filter and the data is compared to benchmark analysis data that will define the conditions that represents the occurrence of a fall.

Entities:  

Mesh:

Year:  2008        PMID: 19163185     DOI: 10.1109/IEMBS.2008.4649682

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

Review 1.  Fall detection with body-worn sensors : a systematic review.

Authors:  L Schwickert; C Becker; U Lindemann; C Maréchal; A Bourke; L Chiari; J L Helbostad; W Zijlstra; K Aminian; C Todd; S Bandinelli; J Klenk
Journal:  Z Gerontol Geriatr       Date:  2013-12       Impact factor: 1.281

Review 2.  Fall detection devices and their use with older adults: a systematic review.

Authors:  Shomir Chaudhuri; Hilaire Thompson; George Demiris
Journal:  J Geriatr Phys Ther       Date:  2014 Oct-Dec       Impact factor: 3.381

3.  Sensitivity of fNIRS measurement to head motion: an applied use of smartphones in the lab.

Authors:  Xu Cui; Joseph M Baker; Ning Liu; Allan L Reiss
Journal:  J Neurosci Methods       Date:  2015-02-14       Impact factor: 2.390

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.