D
Dejan B. Popovic
Researcher at Serbian Academy of Sciences and Arts
Publications - 291
Citations - 6570
Dejan B. Popovic is an academic researcher from Serbian Academy of Sciences and Arts. The author has contributed to research in topics: Functional electrical stimulation & Gait (human). The author has an hindex of 45, co-authored 287 publications receiving 6041 citations. Previous affiliations of Dejan B. Popovic include Aalborg University & Miami Project to Cure Paralysis.
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Automatic recognition of alertness and drowsiness from EEG by an artificial neural network.
TL;DR: The LVQ neural network gives the best classification compared with the linear network that uses WH algorithm (the worst), and the non-linear network trained with the LM rule, and it is shown that the automatic recognition algorithm is applicable for distinguishing between alert and drowsy state in recordings that have not been used for the training.
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Clinical evaluation of Functional Electrical Therapy in acute hemiplegic subjects
TL;DR: The speed of recovery in FET groups was substantially faster compared with the recovery rate in control groups during the first 3 weeks (treatment), and the LFG subjects showed less improvement than the HFG in both the FET and control groups.
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Machine learning in control of functional electrical stimulation systems for locomotion
TL;DR: Two machine learning techniques were evaluated for automatic design of a rule-based control of functional electrical stimulation for locomotion of spinal cord injured humans to learn the invariant characteristics of the relationship between sensory information and the FES-control signal by using off-line supervised training.
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Sensory nerve recording for closed-loop control to restore motor functions
TL;DR: The adaptive logic network used for this study is effective in mapping transfer functions and therefore applicable for determination of gait invariants to be used for closed loop control in an FES system.
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Neuroprostheses for grasping.
TL;DR: The FES technology is briefly explained and a typical population of subjects that can benefit from this technology is indicated as well as the methodology to select and train these subjects to apply the neuroprosthesis in daily living activities.