Profile
Omar Aziz received the B.Eng. degree in 2005 in Mechatronics Engineering from the National University of Science and Technology, Islamabad, Pakistan, the MASc. degree in 2009 and the Ph.D. degree in 2015 from the School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada. He is a Postdoctoral Fellow at Biomechatronic Systems Laboratory at Simon Fraser University, Surrey, BC, Canada. His research interests include: wearable sensors and their application to human movement analysis, human activity classification, injury prevention in older adults, biomechanics, robotics, and control. At Simon Fraser University, his research focuses on the development of a wearable sensor systems and corresponding machine learning algorithms to monitor activity patterns, to detect falls pre- and post-impact, to determine the causes of falls, and to distinguish events of imbalance and near falls from activities of daily living. Outputs
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Category |
Date |
Authors |
| Distinguishing near-falls from daily activities with wearable accelerometers and gyroscopes using support vector machines5.2 PRED-FALL Simon Fraser University | Scientific Excellence - Advancing Knowledge | 2012-08-01 | | | Accuracy of wearable accelerometers in distinguishing falls due to internal versus external perturbations.5.2 PRED-FALL Simon Fraser University | Scientific Excellence - Advancing Knowledge | 2011-05-01 | | | The effect of window size and lead time on pre-impact fall detection accuracy using support vector machine analysis of waist mounted inertial sensor data5.2 PRED-FALL Simon Fraser University | Scientific Excellence - Advancing Knowledge | 2014-08-01 | | | Distinguishing the causes of falls in humans using an array of wearable tri-axial accelerometers.5.2 PRED-FALL Simon Fraser University | Scientific Excellence - Advancing Knowledge | 2014-01-01 | | | Physics of Injuries5.2 PRED-FALL Simon Fraser University, University of British Columbia, KITE Research Institute at University Health Network | Scientific Excellence - Advancing Knowledge | 2015-09-01 | | | Classifying walking, transferring and sedentary activities in humans using an array of wearable inertial sensors: a machine learning approach5.2 PRED-FALL Simon Fraser University | Scientific Excellence - Leadership | 2016-06-03 | | | Validation of accuracy of SVM-based fall detection system using real-world fall and non-fall datasetsAziz O, Klenk J, Schwickert L, Chiari L, Becker C, Park EJ, Mori G, Robinovitch SN:
Validation of accuracy of SVM-based fall detection system using real-world fall and non-fall
datasets. PLoS One. 12(7): e0180318 (11 pages), 20175.2 PRED-FALL Simon Fraser University | Scientific Excellence - Advancing Knowledge | 2017-07-05 | | | Association Between Sedentary Behaviour and Physical, Cognitive and Psychosocial Status Among Older Adults in Assisted LivingLeung PM, Ejupi A, van Schooten KS, Aziz O, Feldman F, Mackey DC, Ashe MC,
Robinovitch SN: Association between Sedentary Behaviour and Physical, Cognitive, and
Psychosocial Status among Older Adults in Assisted Living. BioMed Research International
2017: 9160504 (7 pages), 20175.2 PRED-FALL New Vista Society, Simon Fraser University, Fraser Health | Scientific Excellence - Advancing Knowledge | 2017-03-03 | |
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