Kamiar Aminian

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Adjunct Professor

kamiar.aminian@epfl.ch +41 21 69 32617 http://lmam.epfl.ch

MED 0 1315 (Bâtiment MED)
Station 9
CH-1015 Lausanne

MED 0 1315 (Bâtiment MED)
Station 9
CH-1015 Lausanne




Administrative data

Fields of expertise

Biomechanics of human movement
Wearable Technology / Inertial sensors
Gait Analysis / Physical Activity Monitoring
Physical activity Patterns
Sport Performance
Orthopedics / Rehabilitation engineering
Fall Prevention in Elderly
Motor function in Parkinson disease
Physical behavior in chronic pain



Other publications

Chapter in �Computational Intelligence for Movement Sciences: Neural Networks, Support Vector Machines and other Emerging Techniques, Editors: Begg, RK and Palaniswami, M. Idea Group Inc., USA, Chapter 3, 101-138, 2006
Human movement capture and their clinical applications
H. Dejnabadi, BM Jolles, E. Casanova, P. Fua, K. Aminian
IEEE Transactions on Biomedical Engineering, 53, 1385-1393, 2006
Estimation and Visualization of Sagittal Kinematics of Lower Limbs Orientation using Body-Fixed Sensors
H. Dejnabadi, BM Jolles, K. Aminian
IEEE Transactions on Biomedical Engineering, 52, 8, 1478-1484, 2005
A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes
A. Paraschiv-Ionescu, E.E. Buchser, B. Rutschmann, B. Najafi, K. Aminian
Gait & Posture, 20, 113-125, 2004
Ambulatory system for the quantitative and qualitative analysis of gait and posture in chronic pain patients treated with spinal cord stimulation
A. Salarian, H. Russmann, F. Vingerhoets , C. Dehollain, Y. Blanc, P. R. Burkhard, K. Aminian
IEEE Transactions on Biomedical Engineering, 51 (8), 1434 � 1443, 2004
Gait assessment in Parkinson�s disease: Toward an ambulatory system for long-term monitoring
Najafi B., Aminian K., Paraschiv-Ionescu A., Loew F., Bula C., Robert Ph
IEEE Transactions on Biomedical Engineering, 50 (6), 711-723, 2003
Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in elderly
Aminian, K., B. Najafi, et al.
Journal of Biomechanics 35(5): 689-699., 2002
Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes.
Najafi, B., K. Aminian, et al.
Ieee Transactions on Biomedical Engineering 49(8): 843-851., 2002
Measurement of stand-sit and sit-stand transitions using a miniature gyroscope and its application in fall risk evaluation in the elderly.
K. Aminian, Ph. Robert, E. E. Buchser, B. Rutschmann, D. Hayoz and M. Depairon
Med.Biol.Eng.Comput., 37, 304-308, 1999
Physical activity monitoring based on accelerometry: validation and comparison with video observation
Aminian K., Robert Ph., J�quier E., Schutz Y.
Medicine and Science in Sports and Execise, 27(2): 226-234, 1995
Incline, speed and distance assessment during unconstrained walking
K. Aminian, K. Rezakhanlou, E. De Andres, C. Fritsch, P.-F. Leyvraz and P. Robert
Med.Biol.Eng.Comput., 37, 686-691, 1999
Temporal features estimation during walking using miniature accelerometers: an analysis of gait improvement after hip arthroplasty


my Lab: LMAM

The multidisciplinary research of the Laboratory of Movement Analysis and Measurement (lmam.epfl.ch) aims to transfer bioengineering findings into clinical applications. We are particularly interested to characterize sport performances and pathologies affecting motor function such as osteoarthritis, frailty, pain or movement disorder by studying the movement ability.

Our research involves biomechanical instrumentation for measuring and modelling human biodynamics in daily conditions, during spontaneous activity or physical exercises.Based on body worn sensors, we design wearable systems and algorithms for long-term monitoring of physical activity and gait analysis, for the estimation of the 3D joint kinematics and kinetics, and for the sport performance evaluation. This involves advanced signal processing, multi-parametric approach, sensors’fusion and functional calibration methods to devise new methods for activity recognition and to extract relevant disease/health related features hidden in human biomechanical signals.

Based on these features and instruments new metrics are defined and validated to provide early diagnosis and objective clinimetry for outcome evaluation in orthopaedics and aging, to assess the change of motor function with disease and rehabilitation, to characterise improved performances in sport, and to classify movement disorders.