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Université de Fribourg

Fast and automatic assessment of fall risk by coupling machine learning algorithms with a depth camera to monitor simple balance tasks

Dubois, Amandine ; Mouthon, Audrey ; Sivagnanaselvam, Ranjith Steve ; Bresciani, Jean-Pierre

In: Journal of NeuroEngineering and Rehabilitation, 2019, vol. 16, no. 1, p. 71

Falls in the elderly constitute a major health issue associated to population ageing. Current clinical tests evaluating fall risk mostly consist in assessing balance abilities. The devices used for these tests can be expensive or inconvenient to set up. We investigated whether, how and to which extent fall risk could be assessed using a low cost ambient sensor to monitor balance tasks.Method:...

Consortium of Swiss Academic Libraries

Multilinear Factorizations for Multi-Camera Rigid Structure from Motion Problems

Angst, Roland ; Pollefeys, Marc

In: International Journal of Computer Vision, 2013, vol. 103, no. 2, p. 240-266

Université de Fribourg

Automating the timed up and go test using a depth camera

Dubois, Amandine ; Bihl, Titus ; Bresciani, Jean-Pierre

In: Sensors, 2017, vol. 18, no. 1, p. 14

Fall prevention is a human, economic and social issue. The Timed Up and Go (TUG) test is widely used to identify individuals with a high fall risk. However, this test has been criticized because its “diagnostic” is too dependent on the conditions in which it is performed and on the healthcare professionals running it. We used the Microsoft Kinect ambient sensor to automate this test in...