Falltec ist ein Projekt im Masterstudiengang Digital Healthcare an der FH St. Pölten. Bei Interesse bitten wir um Anfragen per E-Mail.
Außerdem finden Sie uns auf der Website der Fachhochschule.
Hier gibt es das Video vom Vortrag bei der Veranstaltung Build-Well-Being in St. Pölten um Juni 2019:
Weiter unten findet ihr eine Zusammenfassung des Projekts auf Englisch.
Many elderly people suffer from consequences of falls, which cost 32 billion euros per year in Europe [1]. Falls reduce the quality of life and lead to an earlier death. The fall risk for people with dementia is even 2-3x higher [2]. By analysing their gait, the fall risk can be identified and preventive Interventions can be set [3].
The aim of this project is to analyse gait patterns and reduce fall risk by inventing a fall risk assessment system based on a single wearable sensor.
How FallTec helps
Recent studies have shown, that gait parameters like lower step frequency and higher stride length variability do not only indicate a higher fall risk but are useful for the prediction of a future dementia [4].
Our device is a prototype which can help to prevent falls. The patient with dementia must wear the sensor. The collected data will be screened in our web-based application which analyses the data and visualizes if intervention is indicated.
FallTec can be a useful tool to increase quality of life and reduce of healthcare costs caused by falls.
[1] S. Turner, R. Kisser, and W. Rogmans, “EuroSafe Falls Report EU-28.” European Association for Injury Prevention and Safety Promotion, Jun-2015.
[2] J. Härlein, T. Dassen, R. J. G. Halfens, and C. Heinze, “Fall risk factors in older people with dementia or cognitive impairment: a systematic review,” J. Adv. Nurs., vol. 65, no. 5, pp. 922–933, May 2009.
[3] E. Dolatabadi, K. Van Ooteghem, B. Taati, and A. Iaboni, “Quantitative Mobility Assessment for Fall Risk Prediction in Dementia: A Systematic Review,” Dement. Geriatr. Cogn. Disord., vol. 45, no. 5–6, pp. 353–367, 2018.
[4] O. Beauchet et al., “Poor Gait Performance and Prediction of Dementia: Results From a Meta-Analysis,” J. Am. Med. Dir. Assoc., vol. 17, no. 6, pp. 482–490, Jun. 2016.