Ultra Low Power Implantable Platform for Next Generation Neural Interfaces
Lead Research Organisation:
University of Leicester
Department Name: Engineering
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Organisations
People |
ORCID iD |
| Rodrigo Quian Quiroga (Principal Investigator) |
Publications
Barsakcioglu DY
(2014)
An analogue front-end model for developing neural spike sorting systems.
in IEEE transactions on biomedical circuits and systems
Franke F
(2015)
Erratum to: Bayes optimal template matching for spike sorting - combining fisher discriminant analysis with optimal filtering.
in Journal of computational neuroscience
Lopes-Dos-Santos V
(2015)
Extracting information in spike time patterns with wavelets and information theory.
in Journal of neurophysiology
Luan S
(2018)
Compact standalone platform for neural recording with real-time spike sorting and data logging.
in Journal of neural engineering
Navajas J
(2014)
Minimum requirements for accurate and efficient real-time on-chip spike sorting.
in Journal of neuroscience methods
Pedreira C
(2012)
How many neurons can we see with current spike sorting algorithms?
in Journal of neuroscience methods
Quiroga RQ
(2012)
Spike sorting.
in Current biology : CB
Rey HG
(2015)
Single trial analysis of field potentials in perception, learning and memory.
in Current opinion in neurobiology
Rey HG
(2015)
Past, present and future of spike sorting techniques.
in Brain research bulletin
Rey HG
(2015)
Single-cell recordings in the human medial temporal lobe.
in Journal of anatomy
| Description | We proposed a new method to process the data recorded from neurons in the brain in a low-power chip that can transmit results wirelessly to external devices. This invention led to a patent application. |
| Exploitation Route | The method we developed for processing and transmitting the neural data wirelessly can be used by other neurophysiology labs doing experiments with animals and humans. |
| Sectors | Digital/Communication/Information Technologies (including Software),Healthcare,Other |
| Description | Our findings led to research articles and an international patent. We developed a system to transmit wirelessly the activity of neurons to external devices. An International patent application was submitted. European patent 15702568.5 - 1206 / 3100138 was granted in September 2019. |
| First Year Of Impact | 2015 |
| Sector | Other |
| Title | SYSTEM FOR A BRAIN-COMPUTER INTERFACE |
| Description | The invention provides a two-step approach to providing a BCI system. In a first step the invention provides a low-power implantable platform for amplifying and filtering the extracellular recording, performing analogue to digital conversion (ADC) and detecting action potentials in real-time, which is connected to a remote device capable of performing the processor-intensive tasks of feature extraction and spike classification, thus generating a plurality of predetermined templates for each neuron to be used in a second processing step. In the second step the low-power implantable platform amplifies and filters the extracellular recording, performs ADC and detects action potentials, which can be matched on-chip to the predetermined templates generated by the external receiver in the first step. This two-step approach exploits the advantages of both offline and online processing, providing an effective and safe method for performing multiple recordings of single-neuron activity, for research or monitoring applications or for control of a remote device. |
| IP Reference | WO2015114347 |
| Protection | Patent application published |
| Year Protection Granted | 2015 |
| Licensed | No |
| Impact | A series of high profile scientific papers, as listed with the project. |