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
Kavoosi A, Toth R, Benjaber M, Zamora M, Valentin A et al. (2022), 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
DyNeuMo Mk-1: Design and pilot validation of an investigational motion-adaptive neurostimulator with integrated chronotherapy.
Zamora M, Toth R, Morgante F, Ottaway J, Gillbe T et al. (2022), Experimental Neurology, 351
Circadian and infradian rhythms and deep brain stimulation in status epilepticus - a canine case study
Meller S, Zamora M, Toth R, Wendt K, Kajin F et al. (2021), EPILEPSIA, 62, 262-263
Case report: Embedding "digital chronotherapy" into medical devices -- A canine validation for controlling status epilepticus through multi-scale rhythmic brain stimulation
Zamora M, Meller S, Kajin F, Sermon JJ, Toth R et al. (2021), Frontiers in Neuroscience, 15
Field experience of well testing using a coriolis-based three-phase flow meter
Henry M, Tombs , Zhou FB & Zamora ME (2015), International Flow Measurement Conference
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
Related Academics
Most Recent Publications
Computationally efficient neural network classifiers for next generation closed loop neuromodulation therapy - a case study in epilepsy
Kavoosi A, Toth R, Benjaber M, Zamora M, Valentin A et al. (2022), 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
DyNeuMo Mk-1: Design and pilot validation of an investigational motion-adaptive neurostimulator with integrated chronotherapy.
Zamora M, Toth R, Morgante F, Ottaway J, Gillbe T et al. (2022), Experimental Neurology, 351
Circadian and infradian rhythms and deep brain stimulation in status epilepticus - a canine case study
Meller S, Zamora M, Toth R, Wendt K, Kajin F et al. (2021), EPILEPSIA, 62, 262-263
Case report: Embedding "digital chronotherapy" into medical devices -- A canine validation for controlling status epilepticus through multi-scale rhythmic brain stimulation
Zamora M, Meller S, Kajin F, Sermon JJ, Toth R et al. (2021), Frontiers in Neuroscience, 15
Field experience of well testing using a coriolis-based three-phase flow meter
Henry M, Tombs , Zhou FB & Zamora ME (2015), International Flow Measurement Conference
Publications
Most Recent Publications
Computationally efficient neural network classifiers for next generation closed loop neuromodulation therapy - a case study in epilepsy
Kavoosi A, Toth R, Benjaber M, Zamora M, Valentin A et al. (2022), 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
DyNeuMo Mk-1: Design and pilot validation of an investigational motion-adaptive neurostimulator with integrated chronotherapy.
Zamora M, Toth R, Morgante F, Ottaway J, Gillbe T et al. (2022), Experimental Neurology, 351
Circadian and infradian rhythms and deep brain stimulation in status epilepticus - a canine case study
Meller S, Zamora M, Toth R, Wendt K, Kajin F et al. (2021), EPILEPSIA, 62, 262-263
Case report: Embedding "digital chronotherapy" into medical devices -- A canine validation for controlling status epilepticus through multi-scale rhythmic brain stimulation
Zamora M, Meller S, Kajin F, Sermon JJ, Toth R et al. (2021), Frontiers in Neuroscience, 15
Field experience of well testing using a coriolis-based three-phase flow meter
Henry M, Tombs , Zhou FB & Zamora ME (2015), International Flow Measurement Conference
