K
Kamiar Aminian
Researcher at École Polytechnique Fédérale de Lausanne
Publications - 412
Citations - 16975
Kamiar Aminian is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: Gait (human) & Gait analysis. The author has an hindex of 58, co-authored 388 publications receiving 14815 citations. Previous affiliations of Kamiar Aminian include École Normale Supérieure & University of Geneva.
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Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes
TL;DR: An ambulatory system for estimation of spatio-temporal parameters during long periods of walking based on wavelet analysis to compute the values of temporal gait parameters from the angular velocity of lower limbs, which is light, portable, inexpensive and does not provoke any discomfort to subjects.
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Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly
TL;DR: The ambulatory system showed a very high accuracy (> 99%) in identifying the 62 transfers or rolling out of bed, as well as 144 different posture changes to the back, ventral, right and left sides, in both first and second studies.
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Gait assessment in Parkinson's disease: toward an ambulatory system for long-term monitoring
A. Salarian,H. Russmann,François Vingerhoets,Catherine Dehollain,Y. Blanc,Pierre Burkhard,Kamiar Aminian +6 more
TL;DR: The method provides a simple yet effective way of ambulatory gait analysis in PD patients with results confirming those obtained from much more complex and expensive methods used in gait labs.
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iTUG, a Sensitive and Reliable Measure of Mobility
TL;DR: An instrumented TUG is proposed, called iTUG, using portable inertial sensors to improve TUG in several ways: automatic detection and separation of subcomponents, detailed analysis of each one of them and a higher sensitivity than TUG.
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Evaluation of accelerometer-based fall detection algorithms on real-world falls.
Fabio Bagalà,Clemens Becker,Angelo Cappello,Lorenzo Chiari,Kamiar Aminian,Jeffrey M. Hausdorff,Wiebren Zijlstra,Jochen Klenk +7 more
TL;DR: The present results support the idea that a large, shared real-world fall database could, potentially, provide an enhanced understanding of the fall process and the information needed to design and evaluate a high-performance fall detector.