At the Implantable Bionics Laboratory, students have the opportunity to work with experts from various areas of implantable neuroprosthesis, as well as gaining valuable hands-on experience with many state-of-the-art equipment and processes. Students are encouraged to collaborate and innovate here. Many past student projects have been integrated into every-day laboratory operation and manufacturing process. Let your passion turn into the next generation neurostimulation technology and devices!
The United Nations though The Millennium declaration has stated eight development goals with a total of 21 targets. The World Health Organization highlights that access to medical devices is required to improve health as a vehicle to achieve other goals. In this vein, the development of small and inexpensive computers such as Raspberry PI or the ‘Nine-dollar computer’ is boosting access to a wide variety of technological applications. This project aims to provide an open source hardware and software platform for the acquisition of multi-parametric biosignals to serve as an inexpensive patient monitor. We will be testing the design during out preclinical experiments in bionic vision.
The successful candidate will have the chance to work in the laboratory of the Graduate School of Biomedical Engineering with senior and junior staff members. The student will develop its own open source hardware/software platform. Testing of the device can be performed during in vivo experiments at the Graduate School of Biomedical Engineering.
The application of cheap of-the-shelf processors to medical devices is going to transform the medical device market. More portable and cost-effective health technology is becoming accessible to patients and clinicians. This contribution will help reducing manufacturing costs of patient monitors making those affordable for developing countries.
The candidate will transform a list of requirements into a prototype of a functional patient monitor that can be used in preclinical testing activities conducted at the Graduate School of Biomedical Engineering. The student will gain good electronic prototyping and programing (C++/Linux)
More information: RaspberryPi, The World's First Nine Dollar Computer
Contact Person: Dr. Alejandro Barriga-Rivera
The end goal of the bionic eye is to replicate the messages encoded by healthy neurons in normal vision through electrical stimulation of the diseased retina. Amplitude modulated high-count pulse trains (1-7 kHz) have shown in vitro that different functional retinal neurons can be activated independently. However, when these stimuli are delivered in vivo, the induced electrical artefacts and the neural signal overlap. The aim of this project is to develop filtering algorithms that allows for the extraction of neural signals recorded from the visual cortex during electrical stimulation of the retina. Because the power spectrum densities of both, artefact and signal, overlap, there is a need for implementing more advanced filtering techniques. Wavelet filtering has shown to be effective to extract neural spikes. Other techniques include empirical mode decomposition (Hilbert-Huang transform) and adaptive filtering.
The successful candidate will have the chance to work in the laboratory of the Graduate School of Biomedical Engineering with senior and junior staff members. The student will work with signals obtained during in vivo experiments and will implement novel algorithms for spike detection.
The application of these signal processing techniques to current research practices will allow for the validation more complex stimulation paradigms in bionic vision. This is essential as visual percepts, known as phosphenes, elicited by these devices depend on the quality of artificially encoded neural messages; these paradigms will extend our communication repertoire, thus making a better bionic eyes.
The candidate will implement algorithms to obtain mathematical transformations (other than Fourier) of neural signals. The student will then engineer a method to extract the key features that allow for identification of neural spikes. In this process, the candidate will gain programming skills and a deeper understanding of the techniques used in acute electrophysiology.
More information: 1. Mensen, A., Riedner, B., & Tononi, G. (2016). Optimizing detection and analysis of slow waves in sleep EEG. Journal of Neuroscience Methods, 2. Twyford, P., Cai, C., & Fried, S. (2014). Differential responses to high-frequency electrical stimulation in ON and OFF retinal ganglion cells. Journal of neural engineering, 11(2)
Contact Person: Dr. Alejandro Barriga-Rivera
Further information can be found on Moodle.
If you have any ideas, come and talk to us! Do send an email to Prof. Gregg Suaning first so we can arrange the most suitable team to meet with you. The personalised projects are not limited to summer holidays. They can be turned into your thesis or internship research projects and carried out during semesters.