Konstantinos P. Michmizos
Konstantinos P. Michmizos
Professor of Computer Science, Rutgers University
Verified email at - Homepage
Cited by
Cited by
Somatosensory cortex functional connectivity abnormalities in autism show opposite trends, depending on direction and spatial scale
S Khan, K Michmizos, M Tommerdahl, S Ganesan, MG Kitzbichler, ...
Brain 138 (5), 1394-409, 2015
Robot-aided neurorehabilitation: a pediatric robot for ankle rehabilitation
KP Michmizos, S Rossi, E Castelli, P Cappa, HI Krebs
IEEE Transactions on Neural Systems and Rehabilitation Engineering 23 (6 …, 2015
Spiking neural network on neuromorphic hardware for energy-efficient unidimensional SLAM
G Tang, A Shah, KP Michmizos
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019
Reinforcement co-learning of deep and spiking neural networks for energy-efficient mapless navigation with neuromorphic hardware
G Tang, N Kumar, KP Michmizos
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020
Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control
G Tang, N Kumar, R Yoo, KP Michmizos
2020 Conference on Robot Learning (CoRL), 1-14, 2020
Maturation trajectories of cortical resting-state networks depend on the mediating frequency band
S Khan, JA Hashmi, F Mamashli, K Michmizos, MG Kitzbichler, ...
NeuroImage 174, 57-68, 2018
Auditory processing in noise is associated with complex patterns of disrupted functional connectivity in autism spectrum disorder
F Mamashli, S Khan, H Bharadwaj, K Michmizos, S Ganesan, KLA Garel, ...
Autism Research 10 (4), 631-647, 2017
Classification and Prediction of Clinical Improvement in Deep Brain Stimulation from Intraoperative Microelectrode Recordings
K Kostoglou, KP Michmizos, P Stathis, D Sakas, KS Nikita, GD Mitsis
IEEE Transactions on Biomedical Engineering, 2016
Gridbot: An autonomous robot controlled by a spiking neural network mimicking the brain's navigational system
G Tang, KP Michmizos
Proceedings of the International Conference on Neuromorphic Systems, 1-8, 2018
Assist-as-needed in lower extremity robotic therapy for children with cerebral palsy
KP Michmizos, HI Krebs
2012 4th IEEE RAS & EMBS international conference on biomedical robotics and …, 2012
Serious games for the pediatric anklebot
KP Michmizos, HI Krebs
2012 4th IEEE RAS & EMBS international conference on biomedical robotics and …, 2012
Virtual reality for pediatric neuro-rehabilitation: adaptive visual feedback of movement to engage the mirror neuron system
R Kommalapati, KP Michmizos
2016 38th Annual International Conference of the IEEE Engineering in …, 2016
Prediction of the timing and the rhythm of the parkinsonian subthalamic nucleus neural spikes using the local field potentials
KP Michmizos, D Sakas, KS Nikita
IEEE Transactions on Information Technology in Biomedicine 16 (2), 190-197, 2011
Handbook of research on biomedical engineering education and advanced bioengineering learning: interdisciplinary concepts: interdisciplinary concepts
ZO Abu-Faraj
IGI Global, 2012
Increasing liquid state machine performance with edge-of-chaos dynamics organized by astrocyte-modulated plasticity
V Ivanov, K Michmizos
Advances in neural information processing systems 34, 25703-25719, 2021
Pediatric robotic rehabilitation: Current knowledge and future trends in treating children with sensorimotor impairments
KP Michmizos, HI Krebs
NeuroRehabilitation, 1-8, 2017
Beta-band frequency peaks inside the subthalamic nucleus as a biomarker for motor improvement after deep brain stimulation in Parkinson's disease
KP Michmizos, P Frangou, P Stathis, D Sakas, KS Nikita
IEEE Journal of Biomedical and Health Informatics 19 (1), 174-180, 2015
An Astrocyte-Modulated Neuromorphic Central Pattern Generator for Hexapod Robot Locomotion on Intel's Loihi
I Polykretis, KP Michmizos
Proceedings of the International Conference on Neuromorphic Systems (ICONS), 1-8, 2020
Pointing with the ankle: the speed-accuracy trade-off
KP Michmizos, HI Krebs
Experimental Brain Research 232 (2), 647-657, 2014
A neurophysiologically interpretable deep neural network predicts complex movement components from brain activity
N Kumar, KP Michmizos
Scientific reports 12 (1), 1101, 2022
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