header iStoppFalls

Overview

The iStoppFalls consortium and project will develop an embedded AAL system that can predict and prevent falls by monitoring mobility-related activities and other risk factors of falls in real-life. Beyond continuous fall risk monitoring, this enables tailoring individualized exercise programs coached by iStoppFalls.

Fall risk graphThe Senior Mobility Monitor as a component of the iStoppFalls system will unobtrusively and continuously monitor mobility in daily life. It will evaluate quantitative information on frequency, duration and type of mobility activities and qualitative information on balance function and muscle power. The device is an inertial sensor system which can be worn as a necklace without restrictions. This way, the SMM provides continuous monitoring and trend analysis of potential fall risk indicators. It provides information on the effect of the training exercises for daily life of the user, and gives feedback to the training system to tailor exercises.

On the other hand, our PC/Kinect based fall preventive exercise game (Exergame) will facilitate real preventive exercise training (3 times a week), where data is acquired by unobtrusive sensing by the Kinect together with biomechanical modeling and optional heart rate data.

Our eHealth platform and the included Knowledge Based System for Fall Prediction & Prevention correlates these two types of mobility analysis information (SMM & Exergame), and in turn provides sufficient data to perform a trend analysis of these exercise entities, thus evidencing valid fall prediction & sustainable fall prevention.

iStoppFalls is completed by an innovative iTV application which will present advanced reasoning based on all the relevant data mentioned above to the users at home (personal health advisor), and thus provide all the necessary information for individualized fall prediction & prevention and other related components (eg. an e-inclusion module).

Our main evaluation study will analyze several falls related aspects and shall provide evidences for a successful dissemination and exploitation. All of these activities are complemented by a focused transfer program and monitored by the project management.

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iStoppFalls Gait Analysis Paper Published

31. March 2017:    Data from the iStoppFalls gait analysis have been published in the International Journal of Geriatric Gerontology, which is available here: Comparison between...  more ›

iStoppFalls Long-term Living Lab Results Published

7. November 2016:  Data from the iStoppFalls long-term living lab have been published in the ACM Transactions on Computer-Human Interaction (TOCHI), which is available here: ICT-Based Fall...  more ›

EU-FP7-AUS