FallTec Sturzrisiko-Analyse

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.

Bild von Sensor in rotem Gehäuse

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.

Web-Oberfläche des Projektes

[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.

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