Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/179864
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dc.contributor.advisorGasull Casanova, Xavier-
dc.contributor.authorPonente, Federico-
dc.contributor.otherUniversitat de Barcelona. Facultat de Medicina-
dc.date.accessioned2021-09-07T10:39:27Z-
dc.date.available2021-09-07T10:39:27Z-
dc.date.issued2021-07-08-
dc.identifier.urihttp://hdl.handle.net/2445/179864-
dc.description.abstract[eng] The aim of this work is to investigate the human nociceptive system at the peripheral level. Researchers are still debating how the pain perception arises from this very intricate network. The human perception is the most elusive part of our knowledge since different subsystems are involved. The external information such as noxious stimuli must be processed at the peripheral level and through signal cascades and transduction this signal must reach the brain. At the brain level the information is processed and some decisions are taken, such as the well-known fight-or-flight response. In the introduction, the author describes how the human nociceptive system works and in which way the noxious stimulus is converted into a signal understandable by the brain. Several cortical and subcortical areas are involved in this signal processing and going deeper in this assembly line the information becomes more abstracted. The whole pathway is fundamental for pain perception, however some diseases start at the peripheral level. This in turn makes wrong signals reaching the brain. The brain is then processing information that are not real and the responses do not suit with the needs. Therefore, the peripheral system must be investigated and understood firstly, since some central diseases may have a peripheral component as well. With this purpose in mind the microneurography technique has been used. This technique has got some complexity and a computer-aided system must be implemented. The hardware aims to filter out the noisy signal and perform recording and stimulation of the neural fibers. The software is instead used to make the stimulation and recording as automatic as possible in a way that researchers do not have to deal with a lot of parameters and steps to carry out this powerful but also time consuming technique. Some software are already available in the market however even if they work fine with slow conduction fibers such as C-fibers they cannot cope with faster neurons (e.g. Aδ fibers). The aim of this work is to create a software (i.e. SPiike) able to stimulate and record every type of fibers implementing advanced analysis technique as well. Furthermore, considering that some in vivo experiments have been pursued within the project to check the functionality of the software, more specifically in rats and mice, the comparison between human nociceptors and mouse nociceptors is depicted in this section. In the method section, the experimental approach is described step by step. This is composed by several systems that work together for the stimulation, recording and analysis of the neural fibers. The control and acquisition module is composed by the software and a data acquisition board that trigger the stimulator and record the filtered signal. The stimulation module is composed by a stimulator that can be tuned as wish through dedicated knobs. Then the stimulus is delivered to the animal model (or the human patient) and the signal is recorded though a microelectrode inserted into the sciatic nerve. The amplification module is filtering out the noisy signal and is feeding a audio monitor for helping the researcher during the insertion of the electrode inside the nerve and it provides support during the whole experiment giving insights on fiber discharges. In this section the whole setup is described in details as well as the devices needed for the recording. Furthermore, the software development that is the core of this project is described as well, with all the considerations that must be considered during coding. Indeed, the flow chart must be followed methodically in order to minimize bugs and errors that may arise in the final product. Thus a description of the compiler and the Matlab IDE is given along with system and software requirements for the making of the SPiike software. Eventually the explanation of embedded functionalities and capabilities of SPiike is depicted in the final part of this section. This software is indeed able to stimulate slow conducting fibers as well as faster ones, and enhanced analysis techniques such as supervised machine learning are implemented. In the results section, the graphical user interface of the Spiike software is reveled. It resembles the one of another software already available in the market, with a filtered signal and a raster plot embedded on it. However, this software is more user-friendly and it accounts with icons and drop-down menus that enhance the experience of the users during the use of the tool, making their interactions smooth and intuitive. The SPiike software is subdivide into two different tools, a recording module and a analysis module. The former allows the stimulation and recording of neural fibers with a stimulation frequency up to 1000Hz and some online analysis can be conducted to have insights on fibers type and behavior. The analysis module is instead a more powerful analysis environment that can retrieve the dataset recorded with the other module or with the LabChart software. Advanced analysis techniques are implemented in this module, this is meant to speed up fiber classification and analysis. Conclusion and discussion provide a overview on some results. These will be compared to those obtainable through other software available in the market. In this section, pros and cons of the new implemented software, SPiike, will be described as well.ca
dc.format.extent179 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoengca
dc.publisherUniversitat de Barcelona-
dc.rightscc by-nc-sa (c) Ponente, Federico, 2021-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/*
dc.sourceTesis Doctorals - Facultat - Medicina-
dc.subject.classificationProgramari-
dc.subject.classificationNeurologia-
dc.subject.classificationDolor-
dc.subject.classificationElectrofisiologia-
dc.subject.classificationNeurones-
dc.subject.otherComputer software-
dc.subject.otherNeurology-
dc.subject.otherPain-
dc.subject.otherElectrophysiology-
dc.subject.otherNeurons-
dc.titleEnhanced recording paradigms and advanced analyses of peripheral nerve fibers SPiike softwareca
dc.typeinfo:eu-repo/semantics/doctoralThesisca
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
dc.identifier.tdxhttp://hdl.handle.net/10803/672365-
Appears in Collections:Tesis Doctorals - Facultat - Medicina

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