Pseudo-Online Classification of Walking Terrain Using an Ensemble of Support Vector Machines
TBD
TBD
K. North, S. T. Jones, G. M. Simpson, and A. N. Dalrymple, “Personalized gait rehabilitation with spinal cord stimulation and machine learning: Recent advances and promising applications,” Current Opinion in Biomedical Engineering, vol. 34, p. 100579, Jun. 2025.
S. T. Jones, G. M. Simpson, P. M. Pilarski, and A. N. Dalrymple, “Hierarchical reinforcement learning framework for adaptive walking control using general value functions of lower-limb sensor signals,” arXiv preprint arXiv:2507.16983, 2025. [Online]. Available: https://arxiv.org/abs/2507.16983
G. M. Simpson, K. North, S. T. Jones and A. N. Dalrymple, "A Novel Template-Matching Method for Extracting Gait Cycles from Underfoot Pressure Data," 2025 International Conference On Rehabilitation Robotics (ICORR), Chicago, IL, USA, 2025, pp. 1787-1792, doi: 10.1109/ICORR66766.2025.11063134.
S. T. Jones, G. M. Simpson, W. M. J. Young, K. North, P. M. Pilarski and A. N. Dalrymple, "Comparative Analysis of Temporal Difference Learning Methods to Learn General Value Functions of Lower-Limb Signals," 2025 International Conference On Rehabilitation Robotics (ICORR), Chicago, IL, USA, 2025, pp. 1209-1214, doi: 10.1109/ICORR66766.2025.11063114.
A. N. Dalrymple, S. T. Jones, J. B. Fallon, R. K. Shepherd, and D. J. Weber, “Overcoming failure: improving acceptance and success of implanted neural interfaces,” Bioelectron Med, vol. 11, no. 1, p. 6, Mar. 2025.
M. D. Paskett et al., “Improving Upper-limb Prosthesis Usability: Cognitive Workload Measures Quantify Task Difficulty,” Aug. 03, 2022.
Talk at IEEE International Consortium on Rehabilitation Robotics (ICORR), Chicago, IL, USA