Duff, S., Miller, A., Quinn, L., Youdan, G., Bishop, L, Ruthrauff, H., and Wade, E., Quantifying Intra- and Interlimb Use During Unimanual and Bimanual Tasks in Persons with Hemiparesis Post-Stroke, Journal of Neuro Engineering and Rehabilitation, 2022, https:doi.org//10.1186/s12984-022-01020-8.
Torriani-Pasin, C., Demers, M., Polese, J.C., Bishop, L., Wade, E., Hempel, S., and Winstein, C. mHealth technologies used to capture walking and arm use behavior in adult stroke survivors: a scoping review beyond measurement properties, Disability and Rehabilitation Engineering, 2021, DOI: https:doi.org//10.1080/09638288.2021.1953623.
Naghavi, N., and Wade, E., Towards Real-time Prediction of Freezing of Gait in Patients with Parkinson's Disease: A Novel Deep One-class Classifier, IEEE Journal of Biomed Health Inform, 2021, DOI: https://doi.org/10.1109/JBHI.2021.3103071.
Miller, A. Wade, E., Classifying Unimanual and Bimanaul Upper Extremity Tasks in Individuals Post-Stroke. In proceedings, 2021 43rd IEEE Engineering in Medicine and Biology Society (EMBC), Oct 2021.
Waters, E. Wade, E., Classification of Task-Specific Confidence from Kinematic Features. In proceedings, 2021 10th IEEE/EMBS Conference on Neural Engineering, May 2021.
Duff, S., Miller, A., Quinn, L., Youdan, G., Bishop, L., Ruthruaff, H., and Wade, E., Novel Method to Assess Interlimb Coordination in Persons with Hemiparesis, Am. Journal of Occupational Therapy, Aug. 2020.
Duff, S., Stevanovic, M., Berggren, J., Sargent, B., Kimbel, A., Rakovski, C., Yaghmaei, E., Pidcoe, P., Leiby, B., Seruya, M., and Wade, E., Rewarding Arm Activity in Infants at Risk: Feasibility of a Home-Based Program, Am. Journal of Occupational Therapy, Aug. 2020.
Miller, A., Quinn, L., Duff, S., Wade, E., Comparison of Machine Learning approaches for Classifying Upper Extremity Tasks in Individuals Post-Stroke. In proceedings, 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Montreal, CA, Jul. 2020.
Naghavi, N., Miller, A., and Wade, E., Towards Real--Time Prediction of Freezing of Gait in Patients with Parkinson's Disease: Addressing the Class Imbalance Problem, MDPI Sensors, 19(18), 2019, DOI: https://doi.org/10.3390/s19183898.
Naghavi, N. and Wade, E., Prediction of Freezing of Gait in Parkinson's Disease Using Statistical Inference and Lower–Limb Acceleration Data, IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE), 27(5), 2019, pp.947--955.