Evelyn Morin PhD, P.Eng

Acting Associate Dean (Academic)

Phone: 613-533-6562 

Expertise: Biomedical Systems
Evelyn  Morin
Biography Research Teaching Publications

Evelyn Morin received her BSc in Physiology from the University of Toronto in 1981. She subsequently studied at the Institute of Biomedical Engineering at the University of New Brunswick and received her MScE (1984) and PhD (1988) in Electrical Engineering from UNB. She joined the Department of Electrical & Computer Engineering at Queen’s and is currently Professor Emerita. 

Research Interests: 

  • Biological signal analysis 
  • Muscle activation to force modeling 
  • Ergonomics and human performance 
My research involves the application of technology to further our understanding of biological systems, with a primary focus on understanding and modeling the relationship between the physiological and mechanical functions of muscle. This is done through the measurement and analysis of biological signals, both intrinsic signals that arise from tissues within the body, principally the electromyogram (EMG), and extrinsic signals that are due to body motion and interaction with the environment, e.g., limb segment accelerations and contact forces. Advanced surface EMG recording, processing and modeling techniques have been used to achieve better muscle force prediction under static and dynamic conditions. High density (HD) EMG has been recorded and processed using fast orthogonal search (FOS), machine learning (ML) and deep learning (DL) algorithms; impressive force estimation results, both on a per-subject basis and across subjects, have been achieved in the static case. We have additionally recorded data from an inertial measurement unit (IMU) and used the two signal modalities (EMG and IMU) to achieve promising dynamic force estimation results. As well, algorithms to track the development of muscle fatigue, which is commonly defined as a decrease in the output force or power capacity generated by a muscle, under dynamic conditions are being created. I am also involved in a multi-disciplinary project to develop tools which allow us to objectively assess the effects of supporting and carrying heavy loads (primarily in backpacks) on the upper body. In my research, I collaborate with Dr. Keyvan Hashtrudi-Zaad and Dr. Ali Etemad of the Dept. of Electrical and Computer Engineering and with researchers in the Department of Mechanical and Materials Engineering (Dr. Qingguo Li and Dr. Tim Bryant) and the School of Kinesiology and Health Studies (Dr. Joan Stevenson).

Current Research Project

Advanced Electromyogram (EMG) Analysis

The electromyogram (EMG) is detected and recorded during skeletal muscle contraction. In much past work, the EMG has been recorded under controlled experimental conditions, in which a subject maintains a constant position (isometric) and constant force (isotonic) contraction in the muscle under study. During normal activity, however, muscle contractions are neither isometric nor isotonic and the resulting EMG signal records are non-stationary and dynamic. The objective of this research is to obtain better and more flexible representations of muscle function under different conditions. This is being done via the use of enhanced EMG sensing technology (high density EMG), and advanced signal processing and modeling techniques. In addition, we are developing methods to track muscle fatigue over long duration contractions for improved forced prediction under fatiguing conditions. Applications of this work include more generalized muscle force prediction, analysis of muscle coordination and synchronization, and development of improved man-machine interfaces.

The Effects of Load Carriage

A set of tools to objectively assess the effects of supporting and carrying heavy loads on the upper body has been developed by the Objective Manikin-based Biomechanical Assessment of Soldier Torso-borne Equipment (OMBASTE) group under contract to Defence Research and Development Canada. The primary tool is a load carriage simulator in which an anthropometrically correct manikin simulates the forward lean and vertical motion of walking under load. Measurements, including strap forces, contact pressures under backpack elements, motion of load carriage elements and centre of mass of the backpack are collected synchronously and analyzed to evaluate the goodness of the load carriage system being tested. 

In the past 4 years, I have taught ELEC 299 - Mechatronics Project (2nd year core course), ELEC 408 - Biomedical Signal and Image Processing (4th year elective course), and ELEC 811 - Biological Signal Analysis (graduate course). 

Journal Papers (from 2015)

Hajian, G., Behinaein, B., Etemad, A. and Morin, E. Bagged tree ensemble modelling with feature selection for isometric EMG-based force estimation. Biomed. Sig. Proc. Cont., 78, 104012, 2022. 

Hajian, G., Morin, E. and Etemad, A. Multimodal estimation of endpoint force during quasi-dynamic and dynamic muscle contractions using deep learning. IEEE Trans. Instrum. Meas., 71, 2513111, 2022. doi: 10.1109/TIM.2022.3189632

Hajian, G. and Morin, E. Deep multi-scale fusion of convolutional neural networks for EMG-based movement estimation. IEEE Trans. Neural Sys. Rehab. Eng., 30, 486-495, 2022. doi: 10.1109/TNSRE.2022.3153252.

Hajian, G., Etemad, A. and Morin, E. Generalized EMG-based isometric contact force estimation using a deep learning approach. Biomed. Sig. Proc. Cont., 70, 103012, 2021. 

Hajian, G., Etemad, A. and Morin, E. Automated channel selection in high-density sEMG for improved force estimation, Sensors, 20, 4858, 2020; doi:10.3390/s20174858

Johns, G, Morin, E and Hashtrudi-Zaad K. Force modelling of upper limb biomechanics using ensemble fast orthogonal search on high density electromyography, IEEE Trans Neural Sys Rehab Eng, 24(10), 1041-1050, 2016. doi: 10.1109/TNSRE.2016.2515087

Hashemi, J, Morin, E, Mousavi, P and Hashtrudi-Zaad, K. Enhanced dynamic EMG-force estimation through calibration and PCI modelling. IEEE Trans Neural Sys Rehab Eng, 23(1):41-50, 2015.

Book Chapter

Morin, E.L. Myoelectric Signal Processing. Akay, M. (ed.) Encyclopedia of Biomedical Engineering, Wiley & Sons, 2006.

Selected Conference Papers (from 2017)

Hajian, G., Morin, E. and Etemad, A. Convolutional neural network approach for elbow torque estimation during quasi-dynamic and dynamic contractions. 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 665-668, 2021. doi: 10.1109/EMBC46164.2021.9630287

Hajian, G, Morin, E, and Etemad, SA.  PCA-based channel selection in high-density EMG for improving force estimation. 41st Ann. Int. IEEE Eng. Med. Biol. Conf. (EMBC), Berlin, July 23-27, 2019.

Hajian, G, Etemad, SA, and Morin, E.  An investigation of dimensionality reduction techniques for EMG-based force estimation. 41st Ann. Int. IEEE Eng. Med. Biol. Conf. (EMBC), Berlin, July 23-27, 2019.

Massey, R, Morin, E, DeRosa, MC and Prakash, R. Label-free detection of dopamine using aptamer enhanced organic-electrolyte gated FET sensor. IEEE International Conference on Flexible and Printable Sensors and Systems, Glasgow, July 7-10, 2019.

Zhang, G., Morin, E., Zhang, Y. and Etemad, S.A. Non-invasive detection of low-level muscle fatigue using surface EMG with wavelet decomposition. 40th Ann. Int. IEEE Eng. Med. Biol. Conf. (EMBC), Honolulu, HI, July 17-21, 2018.

Tolls, V., Morin, E., K. Rudie, K., Seely, A., Raza, U. and Maslove, D. Heart rate variability response to vasopressor intervention in critically ill patients. AMIA 2018 Informatics Summit, San Francisco, CA, March 2018.

Hajian, G., Behinaein, B., Morin, E. and Etemad, S.A. Improving wrist force estimation with surface EMG during isometric contractions. 41st Can. Med. Biol. Eng. Conf., Charlottetown, PEI, May 8-11, 2018.

Rae, E., Lasso, A., Holden, M.S., Morin, E., Levy, R. and Fichtinger, G. Neurosurgical burr hole placement using the Microsoft HoloLens. SPIE Medical Imaging, Houston, TX, 10-15 Feb. 2018.

Hajian, G. and Morin, E. Effect of joint angle and forearm posture on the elbow flexor and extensor muscles during isometric contraction, 40th Can. Med. Biol. Eng. Conf., Winnipeg MB, May 23–26, 2017.

Wu, P. and Morin, E. A robust algorithm for muscle conduction velocity estimation. 40th Can. Med. Biol. Eng. Conf., Winnipeg MB, May 23–26, 2017.

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