Device Development

• D.J.A. Brenneis, M.R. Dawson, P.M. Pilarski, “Development of the HANDi Hand: an inexpensive, multi-articulating, sensorized hand for machine learning research in myoelectric control”, MEC17: Myoelectric Controls Symposium, Fredericton, New Brunswick, August 15-18, 2017.
• Schofield JS, Schoepp KR, Williams HE, Carey JP, Marasco PD, Hebert JS. (2017). “Characterization of interfacial socket pressure in transhumeral prostheses: a case series”, PLOS one. https://doi.org/10.1371
• Schofield JS, Evans KR, Hebert JS, Marasco PD, Carey JP, “The Effect of Biomechanical Variables on Force Sensitive Resistor Error: Implications for Calibration and Improved Accuracy”, Journal of Biomechanics. 2016.
• M.R. Dawson, C. Sherstan, J.P. Carey, J.S. Hebert, P.M. Pilarski, “Development of the Bento Arm: An Improved Robotic Arm for Myoelectric Training and Research,” MEC14: Myoelectric Controls Symposium, Fredericton, New Brunswick, August 18-22, 2014. (PDF)
• G.W. Melenka, J.S. Schofield, M.R. Dawson, J.P. Carey, “Evaluation of Dimensional Accuracy and Material Properties of the MakerBot 3D Desktop Printer,” Rapid Prototyping Journal, Accepted Jan 4^th 2014, in press.
• Dawson MR, Fahimi F, Carey JP. The development of a myoelectric training tool for above-elbow amputees. Open Biomedical Engineering Journal. 2012;6:5–15.
• M.R. Dawson, J. P. Carey, F. Fahimi, “Myoelectric Training Systems,” Expert Reviews of Medical Devices,Vol.8, No.5, Pages 581-589, 2011.

Sensory Motor Integration

• Hebert JS, Chan KM, Dawson MR. Comparing cutaneous sensory outcomes from three transhumeral targeted reinnervation cases. Prosthet Orthot Int. Accepted Dec 2015. In press.
• Schofield JS, Dawson MR, Carey JP, Hebert JS, 2014. “Characterizing the effects of amplitude, frequency and limb position on vibration induced movement illusions: Implications in sensory-motor rehabilitation.”, Technology and Health Care 23 (2015) 129-141. DOI: 10.3233/THC-140879. (Schofield 2015 TechHealthCare.pdf)
• Hebert JS, Chan KM, Dawson MR. “Comparative Sensory Outcomes for Three Transhumeral Targeted Reinnervation Cases”. MEC14: Myoelectric Controls Symposium, Fredericton, New Brunswick, August 18-22, 2014.
• Schofield JS, Evans KR, Carey JP, Hebert JS. Applications of Sensory Feedback in Motorized Upper Extremity Prosthesis: A Review. Expert Review of Medical Devices. vol.11 no.5 pages 499-511. DOI: 10.1586/17434440.2014.929496
• Hebert JS, Elzinga K, Chan KM, Olson JL, Morhart MJ. Updates in Targeted Sensory Reinnervation for Upper Limb Amputation. Current Surgery Reports 2014, vol. 2, no. 3, pages 45-53. DOI: 10.1007/s40137-013-0045-7.
• Hebert JS, Olson JL, Morhart MJ, Dawson MR, Marasco PD, Kuiken TA, Chan KM. Novel Targeted Sensory Reinnervation Technique To Restore Functional Hand Sensation After Transhumeral Amputation. IEEE Transactions on Neural Systems and Rehabilitation Engineering July 2014. Vol 22, No 4, pages 765-773. DOI: 10.1109/TNSRE.2013.2294907.

Machine Learning

• Edwards AL, Dawson MR, Hebert JS, Sherstan C, Sutton RS, Chan KM, Pilarski PM. Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching. Prosthetics and Orthotics International. Published online before print September 30, 2015, doi: 10.1177/0309364615605373
• Sherstan, C. (2015), “Towards prosthetic arms as wearable intelligent robots”, MSc Thesis, University of Alberta, Department of Computing Science, pp. 131 (publication link)
• Sherstan, C., Modayil, J. and Pilarski, P. M. (August 11-14, 2015), “A collaborative approach to the simultaneous multi-joint control of a prosthetic arm”, International Conference on Rehabilitation Robotics, Singapore, pp. 13-18. (publication link) (supplementary video)
• Sherstan, C. and P.M. Pilarski, “Multilayer General Value Functions for Robotic Prediction and Control,” IROS 2014 Workshop on AI and Robotics, IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, Illinois, September 14-18, 2014 (PDF)
• C. Castellini, P. Artemiadis, M. Wininger, A. Ajoudani, M. Alimusaj, A. Bicchi, B. Caputo, W. Craelius, S. Dosen, K. Englehart, D. Farina, A. Gijsberts, S. Godfrey, L. Hargrove, M. Ison, T. A. Kuiken, M. Markovic, P.M. Pilarski, R. Rupp, E.J. Scheme, “Proceedings of the First Workshop on Peripheral Machine Interfaces: going beyond traditional surface electromyography,” Frontiers in Neurorobotics, vol. 8, no. 22, Aug. 2014. doi: 10.3389/fnbot.2014.00022. (PDF) (Read Online)
• A.S.R. Parker, A.L. Edwards, P.M. Pilarski, “Using Learned Predictions as Feedback to Improve Control and Communication with an Artificial Limb: Preliminary Findings,” arXiv:1408.1913 [cs.AI], 7 pages, 2014. (PDF)(arXiv)
• A.J. Koop, A. Kearney, M. Bowling, P.M. Pilarski, “Dealing with Changing Contexts in Myoelectric Control,” MEC14: Myoelectric Controls Symposium, Fredericton, New Brunswick, August 18-22, 2014. (PDF)
• A.L. Edwards, M.R. Dawson, J.S. Hebert, R.S. Sutton, K.M. Chan, P.M. Pilarski, “Adaptive Switching in Practice: Improving Myoelectric Prosthesis Performance through Reinforcement Learning,”  MEC14: Myoelectric Controls Symposium, Fredericton, New Brunswick, August 18-22, 2014. (PDF)
• A.L. Edwards, A. Kearney, M.R. Dawson, R.S. Sutton, and P.M. Pilarski, “Temporal-Difference Learning to Assist Human Decision Making during the Control of an Artificial Limb,” 1st Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM), Oct. 25–27, Princeton, New Jersey, USA, 2013. 5 pages. (PDF)(arXiv:1309.4714)
• P.M. Pilarski, T.B. Dick, and R.S. Sutton, “Real-time Prediction Learning for the Simultaneous Actuation of Multiple Prosthetic Joints,” Proc. of the 2013 IEEE International Conference on Rehabilitation Robotics (ICORR), Seattle, USA, June 24–26, 2013. 8 pages. (PDF)
• P.M. Pilarski, L. Qi, M. Ferguson-Pell, and S. Grange, “Determining the Time until Muscle Fatigue using Temporally Extended Prediction Learning,” Proc. 18th International Functional Electrical Stimulation Society Conference (IFESS), Donostia-San Sebastian, Spain, June 6–8, pp. 37–40, 2013. (PDF)
• P.M. Pilarski, M.R. Dawson, T. Degris, J.P. Carey, K.M. Chan, J.S. Hebert, and R.S. Sutton, “Adaptive Artificial Limbs: A Real-time Approach to Prediction and Anticipation,” IEEE Robotics & Automation Magazine, Vol. 20(1): 53–64, March 2013. (Postprint PDF) (Published Version) DOI: 10.1109/MRA.2012.2229948
• P.M. Pilarski and R.S. Sutton, “Between instruction and reward: human-prompted switching,” AAAI 2012 Fall Symposium on Robots Learning Interactively from Human Teachers (RLIHT), Nov. 2-4, Arlington, VA, USA, AAAI Technical Report FS-12-07, pp. 46–52, 2012. (PDF)
• P.M. Pilarski, M.R. Dawson, T. Degris, J.P. Carey, K.M. Chan, J.S. Hebert, and R.S. Sutton, “Towards Prediction-Based Prosthetic Control,” Proc. of the 17th International Functional Electrical Stimulation Society Conference 2012 (IFESS), Sept. 9-12, Banff, Canada, pp. 26–29, 2012. (PDF)
• P.M. Pilarski, M.R. Dawson, T. Degris, J.P. Carey, and R.S. Sutton, “Dynamic Switching and Real-time Machine Learning for Improved Human Control of Assistive Biomedical Robots,” Proc. of the 4th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob), June 24-27, Roma, Italy, pp. 296–302, 2012. (PDF)
• P.M. Pilarski, M.R. Dawson, T. Degris, F. Fahimi, J.P. Carey, and R.S. Sutton, “Online Human Training of a Myoelectric Prosthesis Controller via Actor-Critic Reinforcement Learning,” Proc. of the 2011 IEEE International Conference on Rehabilitation Robotics (ICORR), June 29-July 1, Zurich, Switzerland, pp. 134-140, 2011. (PDF)

Outcome Metrics

• Williams HE, Chapman CS, Pilarski PM, Vette AH, Hebert JS. “Gaze and Movement Assessment (GaMA): Inter-site validation of a visuomotor upper limb functional protocol”. bioRxiv. January 2019:681437. doi:10.1101/681437.
• Valevicius AM, Boser QA, Lavoie EB, Chapman CS, Pilarski PM, Hebert JS, Vette AH. Characterization of normative angular joint kinematics during two functional upper limb tasks. Gait & Posture. 2019, Jan; 69: 176–186. https://doi.org/10.1016/j.gaitpost.2019.01.037.
• Lavoie EB, Valevicius AM, Boser QA, Kovic O, Vette AH, Pilarski PM, Hebert JS, Chapman CS. Using synchronized eye and motion tracking to determine high-precision eye movement patterns during object interaction tasks. Journal of Vision. 2018, Jun; 18(6): 1–20. https://doi.org/10.1167/18.6.18.
• Valevicius AM, Boser QA, Lavoie EB, Murgatroyd G, Chapman CS, Pilarski PM, Vette AH, Hebert JS. Characterization of normative hand movements during two functional upper limb tasks. PLoS ONE. 2018, Jun; 13(6): e0199549. https://doi.org/10.1371/journal.pone.0199549.
• Boser QA, Valevicius AM, Lavoie EB, Chapman CS, Pilarski PM, Hebert JS, Vette AH. Cluster-Based Upper Body Marker Models for Three-Dimensional Kinematic Analysis: Comparison with an Anatomical Model and Reliability Analysis. Journal of Biomechanics. 2018, Apr; 72: 228–34. https://doi.org/10.1016/j.jbiomech.2018.02.028.
• Hebert JS, Vette AH, Lewicke J. “Kinematic Data For Modified Box And Blocks Test: Normative And Prosthetic Comparisons”, MEC14: Myoelectric Controls Symposium, Fredericton, New Brunswick, August 18-22, 2014.
• Hebert JS, Lewicke J, Williams TR, Vette AH. Normative data for a modified Box and Blocks test measuring upper limb function via motion capture. Journal of Rehabilitation Research and Development. 2014, Vol 51, No 6. (In press; accepted March 2014). 
• Hebert JS, Lewicke J. Case report of a modified Box and Blocks test with motion capture to measure prosthetic function. Journal of Rehabilitation Research and Development 2012, Vol 49, No 8, pages 1163-1174. PMID 23341309
• Hebert JS, Wolfe DL, Miller WC, Deathe AB, Devlin M, Pallaveshi L. Outcome measures in amputation rehabilitation: ICF Body Functions. Disability and Rehabilitation 2009, Vol. 31, No. 19: Pages 1541-1554. PMID 19479495
• Deathe AB, Wolfe DL, Devlin M, Hebert JS, Miller WC, Pallaveshi L. Selection of outcome measures in lower extremity amputation rehabilitation: ICF Activities. Disability and Rehabilitation 2009, Volume: 31, Issue: 18, Pages: 1455-1473. PMID 19479574