Biography
Mayela Zamora received a B.Sc. degree in Electronic Engineering from Simón Bolívar University, Venezuela, a M.Sc. in Electric Engineering from Universidad Central de Venezuela, and a D.Phil. from the Department of Engineering Science at Oxford University. Mayela's D.Phil. thesis was on the analysis of the electroencephalogram during sleep and vigilance, using machine learning, in particular neural networks.
She has worked on hardware and software design for many applications, including SCADA systems, industrial mass flow meters, and most recently, in implantable medical devices. Mayela worked as a full-time lecturer and researcher at the Universidad Central de Venezuela, and has also taught undergraduates at Oxford University. She has authored many publications and patents from her work on industrial sensors.
Mayela joined Professor Tim Denison’s Group in 2019, to work on interfaces to the central nervous system for research and treatment of several pathologies.
Most Recent Publications
Computationally efficient neural network classifiers for next generation closed loop neuromodulation therapy - a case study in epilepsy
Computationally efficient neural network classifiers for next generation closed loop neuromodulation therapy - a case study in epilepsy
DyNeuMo Mk-1: Design and pilot validation of an investigational motion-adaptive neurostimulator with integrated chronotherapy.
DyNeuMo Mk-1: Design and pilot validation of an investigational motion-adaptive neurostimulator with integrated chronotherapy.
Circadian and infradian rhythms and deep brain stimulation in status epilepticus - a canine case study
Circadian and infradian rhythms and deep brain stimulation in status epilepticus - a canine case study
Case report: Embedding "digital chronotherapy" into medical devices -- A canine validation for controlling status epilepticus through multi-scale rhythmic brain stimulation
Case report: Embedding "digital chronotherapy" into medical devices -- A canine validation for controlling status epilepticus through multi-scale rhythmic brain stimulation
Field experience of well testing using a coriolis-based three-phase flow meter
Field experience of well testing using a coriolis-based three-phase flow meter
Research Interests
- Implantable medical devices
- Embedded firmware/software development
- Digital signal processing
- Circadian rhythms
- Remote health monitoring
- Global health
Current Projects
- Implantable closed-loop neurostimulator with integrated chronotherapy
Research Groups
Related Academics
Most Recent Publications
Computationally efficient neural network classifiers for next generation closed loop neuromodulation therapy - a case study in epilepsy
Computationally efficient neural network classifiers for next generation closed loop neuromodulation therapy - a case study in epilepsy
DyNeuMo Mk-1: Design and pilot validation of an investigational motion-adaptive neurostimulator with integrated chronotherapy.
DyNeuMo Mk-1: Design and pilot validation of an investigational motion-adaptive neurostimulator with integrated chronotherapy.
Circadian and infradian rhythms and deep brain stimulation in status epilepticus - a canine case study
Circadian and infradian rhythms and deep brain stimulation in status epilepticus - a canine case study
Case report: Embedding "digital chronotherapy" into medical devices -- A canine validation for controlling status epilepticus through multi-scale rhythmic brain stimulation
Case report: Embedding "digital chronotherapy" into medical devices -- A canine validation for controlling status epilepticus through multi-scale rhythmic brain stimulation
Field experience of well testing using a coriolis-based three-phase flow meter
Field experience of well testing using a coriolis-based three-phase flow meter
Publications
Most Recent Publications
Computationally efficient neural network classifiers for next generation closed loop neuromodulation therapy - a case study in epilepsy
Computationally efficient neural network classifiers for next generation closed loop neuromodulation therapy - a case study in epilepsy
DyNeuMo Mk-1: Design and pilot validation of an investigational motion-adaptive neurostimulator with integrated chronotherapy.
DyNeuMo Mk-1: Design and pilot validation of an investigational motion-adaptive neurostimulator with integrated chronotherapy.
Circadian and infradian rhythms and deep brain stimulation in status epilepticus - a canine case study
Circadian and infradian rhythms and deep brain stimulation in status epilepticus - a canine case study
Case report: Embedding "digital chronotherapy" into medical devices -- A canine validation for controlling status epilepticus through multi-scale rhythmic brain stimulation
Case report: Embedding "digital chronotherapy" into medical devices -- A canine validation for controlling status epilepticus through multi-scale rhythmic brain stimulation
Field experience of well testing using a coriolis-based three-phase flow meter
Field experience of well testing using a coriolis-based three-phase flow meter
