The algorithm developed by Velásquez and Ph. D. (Automatic Research Line), allows obtaining real-time data of the neurological activity, turning the university into a pioneer in Colombia in neural engineering research.
“Neural engineering is a tool which allows analyzing the response of the brain and based on the data obtained, apply it in response analysis both for diseases as for treatment, helping physicians to identify how neurons are impacted by different pathologies and from there formulate a better treatment,” said Velásquez.
One of the areas of neural engineering is focused is on developing brain-computer interfaces, which consists of extracting information from the brain and placing it in an external device without direct intervention.
The motivation of the researcher is to provide people that have lost mobility for different reasons, such as lateral amyotrophic sclerosis, the capability to communicate and interact, through wheelchairs, prosthetics, robotic arms, and other devices, using brain connections.
To carry out this process it is necessary to begin by collecting real-time data of how brain neuronal relationships work and then with mathematical, statistical, and computer programming processing, among other techniques, produce an algorithm that will allow to turn information into action, which can be like identifying the development of brain pathologies with behavior pattern forecasting or handling devices.
Concretely, the research focused on three elements, the first consisted in extracting discriminating patterns produced when a person is imagining movement and the form the brain interprets these relationships.
“The main issue in measuring brain activity is its variability, as things do not repeat exactly the same, therefore it is very difficult to extract patterns and assess them with time,” said Velazquez.
Furthermore, data mining varies from person the person, as although physiologically the brain is the same, there are differentiating elements such as brain mass –determined by nutrition during growth–, how problems are solved, academic formation, and how different capacities are learned, among others.
The second element is related to discovering pattern variability, creating study subject characterization, and from there, classifying them into different groups with similar motor response behaviors for an action.
And finally, the third element was directed to predicting –based on the data obtained –how the motor response will be in face of an action with the execution of the person involved. From this data they can infer if a person is capable of performing an action or not with a success percentage and from this, not only classify people in different groups but also calibrate computer systems to adapt to the needs of each individual.
“In the future, the applications for these types of processes will be focused on developing longitudinal analysis, which consists of producing previous assessments on patients, they applying treatment and then assessing the response and in case of requiring adjustment, indicating the new treatment with the purposes of monitoring efficacy,” said Velásquez
As a result of her research, three factors are highlighted: 1) extraction of brain activation patterns in response to motor tasks and the application of algorithms to identify said patterns; 2) Designing a descriptor for motor responses; 3) Engineering a new algorithm to predict the capability of a person to carry out imaginary movement tasks and with these predictions, adapt different devices to support people with neuronal diseases or paralyzed.
The Digital Signal Processing and Control Research Group have assessed their response to drugs in an inter-operative manner, establishing the degree of consciousness of the patient during surgery. Another of the projects highlighted is assessing cognitive deterioration in adults to develop a method to identify the possible appearance of early-stage Alzheimer’s disease.
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