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Episode 14 features Ginger Gosnell-Myers in conversation with Am Johal and Jamie-Leigh Gonzales.
Author (aut): Gosnell-Myers, Ginger, Author (aut): Johal, Am, Author (aut): Gonzales, Jamie-Leigh
Date created: 2019-04-08
Episode 16 features Libby Davies, an activist and former Member of Parliament for Vancouver East. Libby spent the past four decades advocating for the Downtown Eastside community as a grassroots organizer, and an elected representative at the municipal and federal levels. She was also the first publicly out woman to be elected to parliament in Canada. SFU’s Melissa Roach and Jamie-Leigh Gonzales interview Libby about her newly released memoir, “Outside In”, covering her early days of community organizing, her experiences as a woman in politics, and representing her community’s concerns in Ottawa.
Author (aut): Davies, Libby , Author (aut): Roach, Melissa, Author (aut): Gonzales, Jamie-Leigh
Date created: 2019-05-06
Author (aut): Taylor, Audrey K., Author (aut): Perez, Diane S., Author (aut): Zhang, Xin, Author (aut): Pilapil, Brandy K., Author (aut): Engelhard, Mark H., Author (aut): Gates, Byron D., Author (aut): Rider, David A.
Date created: 2017-09-27
Author (aut): Zhang, Cheng, Author (aut): Zhou, James H.-W., Author (aut): Sameoto, Dan, Author (aut): Zhang, Xin, Author (aut): Li, Yasong, Author (aut): Ng, Him Wai, Author (aut): Menon, Carlo, Author (aut): Gates, Byron D.
Date created: 2012-08-10
The full text of this paper will be available in Mar 2022 due to the embargo policies of Journal of Hazardous Materials. Contact summit@sfu.ca to enquire if the full text of the accepted manuscript can be made available to you.
Author (aut): Belhaj Abdallah, Bouchra, Author (aut): Zhang, Xin, Author (aut): Andreu, Irene, Author (aut): Gates, Byron D., Author (aut): El Mokni, Ridha, Author (aut): Rubino, Stefano, Author (aut): Landoulsi, Ahmed, Author (aut): Chatti, Abdelwaheb
Date created: 2019-11-08
Stroke is one of the leading causes of permanent disability in adults. The literature suggests that rehabilitation is key to early motor recovery. However, conventional therapy is labor and cost intensive. Robotic and functional electrical stimulation (FES) devices can provide a high dose of repetitions and as such may provide an alternative, or an adjunct, to conventional rehabilitation therapy. Brain-computer interfaces (BCI) could augment neuroplasticity by introducing mental training. However, mental training alone is not enough; but combining mental with physical training could boost outcomes. In the current case study, a portable rehabilitative platform and goal-oriented supporting training protocols were introduced and tested with a chronic stroke participant. A novel training method was introduced with the proposed rehabilitative platform. A 37-year old individual with chronic stroke participated in 6-weeks of training (18 sessions in total, 3 sessions a week, and 1 h per session). In this case study, we show that an individual with chronic stroke can tolerate a 6-week training bout with our system and protocol. The participant was actively engaged throughout the training. Changes in the Wolf Motor Function Test (WMFT) suggest that the training positively affected arm motor function (12% improvement in WMFT score).
Author (aut): Zhang, Xin, Author (aut): Elnady, Ahmed M., Author (aut): Randhawa, Bubblepreet K., Author (aut): Boyd, Lara A., Author (aut): Menon, Carlo
Date created: 2018-04-03
Interview for the Below the Radar podcast episode 3. Jamie-Leight Gonzales interviews Ellen Woodsworth.
Author (aut): Woodsworth, Ellen, Author (aut): Gonzales, Jamie-Leigh
Date created: 2018-11-19
Interview for the Below the Radar podcast episode 8. Jamie-Leigh Gonzales interviews Jessica Hannon and Peter Thompson about Megaphone magazine and the Hope in Shadows calendar.
Author (aut): Hannon, Jessica, Author (aut): Thompson, Peter, Author (aut): Gonzales, Jamie-Leigh
Date created: 2019-01-14
Interview for the Below the Radar podcast episode 9. Jamie-Leigh Gonzales interviews Sarah Blyth about the opioid crisis in Vancouver.
Author (aut): Blyth, Sarah, Author (aut): Gonzales, Jamie-Leigh
Date created: 2019-01-28
Author (aut): Zhang, Xin, Author (aut): Park, Hyeong-Ho, Author (aut): Choi, Yong-June, Author (aut): Park, Hyung-Ho , Author (aut): Hill, Ross
Date created: 2011
The full text of this paper will be available in July, 2021 due to the embargo policies of Advanced Optical Materials for works funded by Natural Sciences and Engineering Research Council of Canada (NSERC). Contact summit@sfu.ca to enquire if the full text of the accepted manuscript can be made available to you.
Author (aut): Zhang, Xin, Author (aut): Ali, Rana Faryad , Author (aut): Boyer, John‐Christopher , Author (aut): Branda, Neil R., Author (aut): Gates, Byron D.
Date created: 2020-07-26
Electroencephalography (EEG) has recently been considered for use in rehabilitation of people with motor deficits. EEG data from the motor imagery of different body movements have been used, for instance, as an EEG-based control method to send commands to rehabilitation devices that assist people to perform a variety of different motor tasks. However, it is both time and effort consuming to go through data collection and model training for every rehabilitation task. In this paper, we investigate the possibility of using an EEG model from one type of motor imagery (e.g.: elbow extension and flexion) to classify EEG from other types of motor imagery activities (e.g.: open a drawer). In order to study the problem, we focused on the elbow joint. Specifically, nine kinesthetic motor imagery tasks involving the elbow were investigated in twelve healthy individuals who participated in the study. While results reported that models from goal-oriented motor imagery tasks had higher accuracy than models from the simple joint tasks in intra-task testing (e.g., model from elbow extension and flexion task was tested on EEG data collected from elbow extension and flexion task), models from simple joint tasks had higher accuracies than the others in inter-task testing (e.g., model from elbow extension and flexion task tested on EEG data collected from drawer opening task). Simple single joint motor imagery tasks could, therefore, be considered for training models to potentially reduce the number of repetitive data acquisitions and model training in rehabilitation applications.
Author (aut): Zhang, Xin, Author (aut): Yong, Xinyi, Author (aut): Menon, Carlo
Date created: 2017-11-29
Author (aut): Paul, Michael T.Y., Author (aut): Yee, Brenden B., Author (aut): Zhang, Xin, Author (aut): Alford, Eiji H., Author (aut): Pilapil, Brandy K., Author (aut): Gates, Byron D.
Date created: 2019-01-01
Fulltext of the document is not available until March 2025 due to the journal embargo policies of the American Chemical Society. If you need fulltext access please email summit@sfu.ca.
Author (aut): Rea, Alex, Author (aut): Zhang, Xin, Author (aut): Mobrhan-Shafiee, Nazanin, Author (aut): Wang, Michael C.P., Author (aut): Proulx, Howard, Author (aut): Gates, Byron
Date created: 2024-03-26