Relevant bibliographies by topics / OpenBCI

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'OpenBCI'

Author: Grafiati
Published: 4 June 2021
Last updated: 28 May 2022

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Journal articles on the topic "OpenBCI"

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Wu, Na, Hao JIN, Xiachuan Pei, Shurong Dong, Jikui Luo, Ruijian Yan, and Gang Feng. "Gesture recognition system based on CNN-IndRNN and OpenBCI." MATEC Web of Conferences 336 (2021): 06003. http://dx.doi.org/10.1051/matecconf/202133606003.

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Surface electromyography (sEMG), as a key technology of non-invasive muscle computer interface, is an important method of human-computer interaction. We proposed a CNN-IndRNN (Convolutional Neural Network-Independent Recurrent Neural Network) hybrid algorithm to analyse sEMG signals and classify hand gestures. Ninapro’s dataset of 10 volunteers was used to develop the model, and by using only one time-domain feature (root mean square of sEMG), an average accuracy of 87.43% on 18 gestures is achieved. The proposed algorithm obtains a state-of-the-art classification performance with a significantly reduced model. In order to verify the robustness of the CNN-IndRNN model, a compact real¬time recognition system was constructed. The system was based on open-source hardware (OpenBCI) and a custom Python-based software. Results show that the 10-subject rock-paper-scissors gesture recognition accuracy reaches 99.1%.
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Jukiewicz, Marcin, and Anna Cysewska-Sobusiak. "Stimuli design for SSVEP-based brain computer-interface." International Journal of Electronics and Telecommunications 62, no. 2 (June 1, 2016): 109–13. http://dx.doi.org/10.1515/eletel-2016-0014.

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Abstract The paper presents a process of stimuli design for SSVEP-based brain computer-interface. A brain computer-interface can be used in direct communication between a brain and a computer, without using muscles. This device is useful for paralyzed people to communicate with the surrounding environment. Design process should provide high accuracy recognition of presented stimuli and high user comfort. It is widely known how to make stimuli for BCI which are using high-grade EEG. Over recent years cheaper EEGs are becoming more and more popular, for example OpenBCI, which uses ADS1299 amplifier. In this article we review past works of other authors and compare it with our results, obtained using EEG mentioned before. We try to confirm that it is possible to use successfully OpenBCI in BCI projects.
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Xin, Xu, Chen Zan, Li Xiaojian, and Jiang Lan. "Design and Implementation of Brain-Apparatus Conversations Portable EEG Monitoring System based on OpenBCI." International Journal of Performability Engineering 16, no. 10 (2020): 1646. http://dx.doi.org/10.23940/ijpe.20.10.p16.16461654.

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Suryotrisongko, Hatma, and Febriliyan Samopa. "Evaluating OpenBCI Spiderclaw V1 Headwear's Electrodes Placements for Brain-Computer Interface (BCI) Motor Imagery Application." Procedia Computer Science 72 (2015): 398–405. http://dx.doi.org/10.1016/j.procs.2015.12.155.

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Dang, Xin, Bingbing Kang, Xuyang Liu, and Guangyu Cui. "An Interactive Care System Based on a Depth Image and EEG for Aged Patients with Dementia." Journal of Healthcare Engineering 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/4128183.

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Due to the limitations of the body movement and functional decline of the aged with dementia, they can hardly make an efficient communication with nurses by language and gesture language like a normal person. In order to improve the efficiency in the healthcare communication, an intelligent interactive care system is proposed in this paper based on a multimodal deep neural network (DNN). The input vector of the DNN includes motion and mental features and was extracted from a depth image and electroencephalogram that were acquired by Kinect and OpenBCI, respectively. Experimental results show that the proposed algorithm simplified the process of the recognition and achieved 96.5% and 96.4%, respectively, for the shuffled dataset and 90.9% and 92.6%, respectively, for the continuous dataset in terms of accuracy and recall rate.
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Zou, Guoxia. "The Recognition of Action Idea EEG with Deep Learning." Complexity 2022 (January 29, 2022): 1–13. http://dx.doi.org/10.1155/2022/5308885.

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The recognition in electroencephalogram (EEG) of action idea is to identify what action people want to do by EEG. The significance of this project is to help people who have trouble in movement. Their action ideas are identified by EEG, and then robot hands can assist them to complete the action. This paper, with comparative experiments, used OpenBCI to collect EEG action ideas during static action and dynamic action and used the EEG recognition model Conv1D-GRU to training and recognition action, respectively. The experimental result shows that the brain wave action idea is easier to recognize in static state. The accuracy of brain wave action idea recognition in dynamic state is only 72.27%, and the accuracy of brain wave action idea recognition in static state is 99.98%. The experimental result confirms that the action idea will be of great help to people with mobility difficulties.
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Martínez-Cerveró, Jayro, Majid Khalili Ardali, Andres Jaramillo-Gonzalez, Shizhe Wu, Alessandro Tonin, Niels Birbaumer, and Ujwal Chaudhary. "Open Software/Hardware Platform for Human-Computer Interface Based on Electrooculography (EOG) Signal Classification." Sensors 20, no. 9 (April 25, 2020): 2443. http://dx.doi.org/10.3390/s20092443.

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Electrooculography (EOG) signals have been widely used in Human-Computer Interfaces (HCI). The HCI systems proposed in the literature make use of self-designed or closed environments, which restrict the number of potential users and applications. Here, we present a system for classifying four directions of eye movements employing EOG signals. The system is based on open source ecosystems, the Raspberry Pi single-board computer, the OpenBCI biosignal acquisition device, and an open-source python library. The designed system provides a cheap, compact, and easy to carry system that can be replicated or modified. We used Maximum, Minimum, and Median trial values as features to create a Support Vector Machine (SVM) classifier. A mean of 90% accuracy was obtained from 7 out of 10 subjects for online classification of Up, Down, Left, and Right movements. This classification system can be used as an input for an HCI, i.e., for assisted communication in paralyzed people.
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Md Ahnaf Shariar, Syeda Maliha Monowara, Md. Shafayat Ul Islam, Muhammed Junaid Noor Jawad, and Saifur Rahman Sabuj. "Brainwave assistive system for paralyzed individuals." ITU Journal on Future and Evolving Technologies 2, no. 3 (July 15, 2021): 79–89. http://dx.doi.org/10.52953/ibjp6517.

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The Brain-Computer Interface (BCI) is a system based on brainwaves that can be used to translate and comprehend the innumerable activities of the brain. Brainwave refers to the bioelectric impulses invariably produced in the human brain during neurotransmission, often measured as the action potential. Moreover, BCI essentially uses the widely studied Electroencephalography (EEG) technique to capture brainwave data. Paralysis generally occurs when there is a disturbance in the central nervous system prompted by a neurodegenerative or unforeseen event. To overcome the obstacles associated with paralysis, this paper on the brainwave-assistive system is based on the BCI incorporated with Internet-of-things. BCI can be implemented to achieve control over external devices and applications. For instance, the process of cursor control, motor control, neuroprosthetics and wheelchair control, etc. In this paper, the OpenBCI Cyton-biosensing board has been used for the collection of the EEG data. The accumulated EEG data is executed subsequently to obtain control over the respective systems in real-time. Hence, it can be concluded that the experiments of the paper support the idea of controlling an interfaced system through the real-time application of EEG data.
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Durka, P. J., R. Kuś, J. Żygierewicz, M. Michalska, P. Milanowski, M. Łabęcki, T. Spustek, D. Laszuk, A. Duszyk, and M. Kruszyński. "User-centered design of brain-computer interfaces: OpenBCI.pl and BCI Appliance." Bulletin of the Polish Academy of Sciences: Technical Sciences 60, no. 3 (December 1, 2012): 427–31. http://dx.doi.org/10.2478/v10175-012-0054-1.

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Abstract Brain-Computer Interface (BCI) allows for non-muscular communication with external world, which may be the only way of communication for patients in a locked-in state. This paper presents a complete software framework for BCI, a novel hardware solution for stimuli rendering in BCIs based on Steady State Visual Evoked Potentials (SSVEP), and a univariate algorithm for detection of SSVEP in the EEG time series. OpenBCI is a complete software framework for brain-computer interfaces. Owing to an open license and modular architecture, it allows for flexible implementations of different communication channels in the serial or parallel hybrid mode, minimization of costs and improvements of stability and efficiency. Complete software is freely available from http://openbci.pl. BCI Appliance is a hardware solution that allows for dynamic control of menus with stable generation of stimuli for the SSVEP paradigm. The novelty consists of a design, whereby the LCD screen is illuminated from behind using an array of LEDs. Design pioneers also proposed a new line of thought about the user-centered design of BCI systems: a simple box with one on/off button, minimum embedded software, wireless connections to domotic and EEG acquisition devices, and user-controlled mode switching in a hybrid BCI.
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Castro-García, Juan Antonio, Alberto Jesús Molina-Cantero, Isabel María Gómez-González, Sergio Lafuente-Arroyo, and Manuel Merino-Monge. "Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables." Electronics 11, no. 1 (January 4, 2022): 155. http://dx.doi.org/10.3390/electronics11010155.

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Detecting stress when performing physical activities is an interesting field that has received relatively little research interest to date. In this paper, we took a first step towards redressing this, through a comprehensive review and the design of a low-cost body area network (BAN) made of a set of wearables that allow physiological signals and human movements to be captured simultaneously. We used four different wearables: OpenBCI and three other open-hardware custom-made designs that communicate via bluetooth low energy (BLE) to an external computer—following the edge-computingconcept—hosting applications for data synchronization and storage. We obtained a large number of physiological signals (electroencephalography (EEG), electrocardiography (ECG), breathing rate (BR), electrodermal activity (EDA), and skin temperature (ST)) with which we analyzed internal states in general, but with a focus on stress. The findings show the reliability and feasibility of the proposed body area network (BAN) according to battery lifetime (greater than 15 h), packet loss rate (0% for our custom-made designs), and signal quality (signal-noise ratio (SNR) of 9.8 dB for the ECG circuit, and 61.6 dB for the EDA). Moreover, we conducted a preliminary experiment to gauge the main ECG features for stress detection during rest.
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Dissertations / Theses on the topic "OpenBCI"

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Заворотний, А. О. "Додаток для моніторингу та аналізу стану психофізіологічного здоров'я користувача." Thesis, Чернігів, 2021. http://ir.stu.cn.ua/123456789/25127.

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Заворотний, А. О. Додаток для моніторингу та аналізу стану психофізіологічного здоров'я користувача : випускна кваліфікаційна робота : 121 "Інженерія програмного забезпечення" / А. О. Заворотний ; керівник роботи А. М. Акименко ; НУ "Чернігівська політехніка", кафедра технологій та програмної інженерії. – Чернігів, 2021. – 75 с.
Об'єктом розробки є додаток для моніторингу та аналізу стану психофізіологічного здоров’я користувача за допомогою методів електроенцефалографії. Результатом роботи є реалізація таких можливостей додатку: – збір даних з пристрою електроенцефалографії у реальному часі; – розпізнавання паттернів активності головного мозку користувача у реальному часі та виділення характеристик станів психофізіологічного здоров’я користувача у реальному часі; – демонстрація статистики зміни станів психофізіологічного здоров’я користувача за довільний проміжок часу у вигляді інтерактивної візуалізації часових рядів; – сповіщення користувача про необхідність перерви та про критичні показники характеристик стану психофізіологічного здоров’я користувача у реальному часі. Для розгортання додатку необхідно встановити на персональному комп'ютері Python версії 3.7+, веб-сервіс Greafana та СУБД RedisTimeSeries. Реалізація додатку була виконана з використанням технологій OpenBCI, BrainFlow, Python, MNE, Timeloop, RedisTimeSeries та Grafana. Для реалізації додатку використовувалося інтегроване середовище розробки Visual Studio Code. Подальша розробка додатку можлива в сторону оптимізації та додання відстежуваних показників. Робота має практичну цінність. Розрахунок економічної цінності не проводився.
The object of development is a software application for monitoring and analysis of the state of psychophysiological health using electroencephalography. The result is an implementation of the following features of the application: – real time data collection from the electroencephalography device; – real-time pattern recognition of user's brain activity; – real-time analysis of a user's psychophysiological health; – interactive visualization of changes in a user's psychophysiological health for any period of time; – informing a user about the need for a break and about critical indicators of a user's brain activity in real time. To deploy the application, you need to install Python version 3.7+, Grafana web service and RedisTimeSeries database. The application was implemented using OpenBCI, BrainFlow, Python, MNE-Python, Timeloop, RedisTimeSeries, Grafana. The integrated development environment Visual Studio Code was used to develop the application. Further development of the application is possible in the direction of optimizing and adding another mental health indicators. The work has practical value. The calculation of economic value was not carried out.
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Persich, Alexandr. "Analýza a klasifikace dat ze snímače mozkové aktivity." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417221.

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This thesis describes recording, processing and classifying brain activity which is being captured by a brain-computer interface (BCI) device manufactured by OpenBCI company. Possibility of use of such a device for controlling an application with brain activity, specifically with thinking of left or right hand movement, is discussed. To solve this task methods of signal processing and machine learning are used. As a result a program that is capable of recording, processing and classifying brain activity using an artificial neural network is created. An average accuracy of classification of synthetic data is 99.156%. An average accuracy of classification of real data is 73.71%.
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Mikalsen, Magnus Alvestad. "OpenACC-based Snow Simulation." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-23000.

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In recent years, the GPU platform has risen in popularity in high performance com-puting due to its cost effectiveness and high computing power offered through its manyparallel cores. The GPUs computing power can be harnessed using the low-level GPGPUprogramming APIs CUDA and OpenCL. While both CUDA and OpenCL gives the pro-grammer fine-grained control of a GPUs resources, they are both generally considereddifficult to use and can potentially lead to complicated software design. To simplifyGPGPU programming and gain more mainstream usage of GPUs, there is an increasedinterest in moving the complexity of GPGPU programming over to the compiler. Thishas lead to the development of the directive-based standard for heterogeneous computingcalled OpenACC, supported by NVIDIA, Cray, PGI, CAPS and others.In this thesis, we explore using OpenACC on a high performance snow simulator code de-veloped by the HPC-Lab at NTNU. The snow simulator consists of two main simulationcomponents; the simulation of wind, and the simulation of snow particle movement.The OpenACC version of the snow simulator is made by first updating the currentCUDA version, porting it to a sequential CPU implementation, and applying OpenACCdirectives to accelerate compute intensive regions in the code. The OpenACC port isalso optimized by reducing datamovement between host and device using OpenACClibrary routines.Due to the heterogeneous nature of OpenACC, we show that the inability to explicitlyuse shared memory as temporary storage and not being able to use texture memory forhardware based interpolation and 3D caching, are the largest performance bottleneckswhen comparing to the CUDA version.This is supported by the benchmarks of the OpenACC implementation which is shown togive only 40.6% performance of the CUDA version with an average speedup of 3.2x whenscaling the amount of snow particles simulated and using a balanced windfield dimension.When scaling the windfield with constant snow particles 58% of the CUDA performanceis reached with an average speedup of 4.84x. The best real-time performance is found atabout 1.5M snow particles when using a balanced windfield with about 524K grid cells.Using OpenACC for accelerating high performance graphical simulations can be a viableoption if the goal is high code portability, however, when the goal is to achieve the best possible performance, our experience show that it is still better to use the more low-level alternatives CUDA or OpenCL.
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Muller, Bjørn Christian. "Implementering av openBIM i kalkulasjonsprosessen." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for bygg, anlegg og transport, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-18463.

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Implementering av openBIM i kalkulasjonsprosessen vil åpne for helt andre muligheter i tilnærmingen til et nytt prosjekt. Med det menes at informasjonen tilknyttet en åpen BIM vil bidra til å gi et bedre grunnlag for konseptvalg og alternative løsninger gjennom gode visualiseringsegenskaper i modellen og en høyere informasjonsgrad i en tidligere fase sammenlignet med en tradisjonell 2D-basert kalkulasjonsprosess. OpenBIM baserer seg i hovedsak på de tre ulike og åpne standardene IFC, IFD og IDM. Når man setter de tre aspektene av openBIM i sammenheng omtaler man åpen BIM som å ha et omforent lagringsformat med enighet om terminologi der BIM-modellen kan kobles opp mot veletablerte forretningsprosesser. Åpen BIM vil dermed fungere som en universell tilnærming til samarbeid, realisering og drift av bygninger basert på åpne standarder og god informasjonsutveksling.En openBIM-basert kalkulasjonsprosess består i å integrere objektene og deres tilhørende attributter/informasjon fra prosjektets ulike BIM-modeller inn i entreprenørens kostnadsdatabase som inneholder prisinformasjon til hvert enkelt objekt eller delobjekt. En slik prosess kan deles inn i tre delprosesser som beskriver arbeidet fra entreprenørens mottakelse av en BIM til ferdig utarbeidet kalkyle. De tre prosessene er; organisering av modellen, oppbygning av objektenes resepter og selve kalkulasjonen av kalkylen.Mengdeberegning sees ofte på som det første steget innenfor kalkulasjonsprosessen og i tradisjonelle kalkulasjonsprosesser utgjør mengdeberegning mellom 50-80 prosent av kalkulatørenes tidsbruk. OpenBIM vil tilrettelegge for en tilnærmet automatisk mengdeberegningsprosess, noe som vil frigjøre mye tid og ressurser hos kalkulatørene der de heller kan fokusere på nøyere vurdering av prosjektets konsept og tilhørende alternative løsninger. På bakgrunn av dette er mengdeberegningsprosessen en av de prosessene som har størst potensial til forbedring ved implementering av openBIM. Selv om åpen BIM tillater automatiske mengdeberegninger vil behovet for kalkulatører i en kalkulasjonsprosess aldri endre seg. Deres arbeidsoppgaver, ved å besitte gode kalkulasjonsegenskaper og samtidig ta hånd om og strukturere informasjonen i en BIM, er helt nødvendig for å utvikle et godt anbud. Dagens kalkulasjonspraksis i MajaTeknobygg framstår i dag som en mindre integrert prosess enn den ville gjort ved full utnyttelse av BIM. Calcus tas i bruk i tidligfasen for å få et hurtig kostnadsestimat av prosjektet. Mengdene hentes ut ved hjelp av et 2D-basert mengdeberegningsprogram for så å implementeres inn i ressurskalkyleverktøyet ByggOffice. Prosessene har lite eller ingen integrasjon mellom seg og nå som både ByggOffice og Calcus har fått innført egen BIM-modul med bedre integrasjon seg imellom vil det å se på samhandlingen mellom programvarene være viktig å gjøre for MajaTeknobygg. Fordelene ved å ta i bruk IFC-formatet i kalkulasjonsprosessen vil helt klart være en bedre samspillprosess og en mer komprimert prosjektering der informasjonsflyten på tvers av ulike fag vil fungere på en god måte. I en slik prosess må kalkulatørene etablere leveringskrav til de ulike aktørene under modelleringsprosessen slik at nødvendig modellinformasjon ligger tilgjengelig til riktig tidspunkt. Det må også avklares og bestemmes et system for objektenes rolle i en BIM. Ofte modelleres det objekt i en BIM uten at det videre er avklart om dets plassering og oppbygning er bestemt eller om det kun brukes til visualisering i modellen. Calcus har lenge vært et godt kalkulasjonsverktøy for vurderinger av kostnadsbildet i tidligfasen av et prosjekt. Med programmets nyetablerte BIM-modul for import/eksport av IFC-modeller vil prosjektet fremstå med blant annet større sporbarhet, (delvis) automatisk mengdeberegning og et bedre produkt for konseptvalg med tilhørende alternative løsninger. Kalkulasjonsverktøyet har i dag en god struktur med kontoplan oppbygd etter NS3451 og integrerte prislinjer basert på NS 3420. Ved standardisert bruk av BIM vil Calcus etter hvert få implementert et standard objektbibliotek som blir viktig i en kalkulasjonsprosess med openBIM.
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Sundholm, Erik. "Distance Fields Acceleratedwith OpenCL." Thesis, Umeå University, Department of Computing Science, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-34953.

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An important task in any graphical simulation is the collision detection between the objects in the simulation. It is desirable to have a good general method for collision detection with high performance. This thesis describes an implementation of a collision detection method that uses distance fields to detect collisions. This method is quite robust and able to detect collisions between most possible shapes. It is also capable of computing contact data for collisions. A problem with distance fields is that the performance cost for making a distance field is quite extensive. It is therefore customary to have some way of accelerating the computation of the distance field (usually by only computing select parts of the field). The application implemented in this thesis solves this performance problem by using the parallel framework OpenCL for accelerating the construction of the field.OpenCL enables programmers to execute code on the GPU. The GPU is highly data parallel and a huge increase in performance can be obtained by letting the GPU handle the computations associated with the initiation of the field.

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Bremseth, Morten. "Om implementering av frekvenshopping i OpenBTS." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for elektronikk og telekommunikasjon, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-16348.

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Denne Rapporten gir en forklaring på hva programvaredefinert radio er generelt. Den omtaler en konkret realisering ved hjelp av programvaren GNU Radio og den universale radioenheten USRP (Universal Software Radio Peripheral). GSM forklares slik at leseren får den nødvendige oversikten som trengs for å forstå resten av rapporten. Frekvenshopping forklares generelt og hvordan det er gjort i GSM. Det fremstilles en mulig realisering av frekvenshopping med USRP. Programvaren som benyttes for å opprette et GSM-nettverk presenteres. Programvaren som trengs er OpenBTS, GNU Radio og Asterisk. Den fysiske oppkoblingen av USRP når OpenBTS benyttes i programvare GSM blir forklart og hvilket testmiljø eksperimentene ble utført i beskrives. Delvis vellykkede resultater presenteres og rapporten konkluderer med at det skal være mulig å implementere frekvenshopping i OpenBTS med USRP som RF-maskinvare.
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Fagerlund, Olav Aanes. "Multi-core programming with OpenCL: performance and portability : OpenCL in a memory bound scenario." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11119.

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With the advent of multi-core processors desktop computers have become multiprocessors requiring parallel programming to be utilized efficiently. Efficient and portable parallel programming of future multi-core processors and GPUs is one of today’s most important challenges within computer science. Okuda Laboratory at The University of Tokyo in Japan focuses on solving engineering challenges with parallel machines. A multi-core FEM solver package is under development within this laboratory that utilizes both standard CPUs and GPUs.This student project, given by Department of Computer and Information Science (IDI) at NTNU in cooperation with Okuda Laboratory at The University of Tokyo, seeks to explore the promising path towards more platform independent parallel programming given by the OpenCL library, runtime system and language. And, in doing so, contributing to their FEM solver software CUKr by making it utilize OpenCL.
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Belgiovine, Mauro. "Accelerare l'algebra lineare con OpenCL." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amslaurea.unibo.it/5079/.

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Sundholm, Erik. "Distance Fields Accelerated with OpenCL." Thesis, Umeå universitet, Institutionen för datavetenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-34953.

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An important task in any graphical simulation is the collision detection between the objects in the simulation. It is desirable to have a good general method for collision detection with high performance. This thesis describes an implementation of a collision detection method that uses distance fields to detect collisions. This method is quite robust and able to detect collisions between most possible shapes. It is also capable of computing contact data for collisions. A problem with distance fields is that the performance cost for making a distance field is quite extensive. It is therefore customary to have some way of accelerating the computation of the distance field (usually by only computing select parts of the field). The application implemented in this thesis solves this performance problem by using the parallel framework OpenCL for accelerating the construction of the field.OpenCL enables programmers to execute code on the GPU. The GPU is highly data parallel and a huge increase in performance can be obtained by letting the GPU handle the computations associated with the initiation of the field.
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Rogeiro, João Pedro Martins. "Geometry based visualization with OpenCL." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/7951.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
This work targets the design and implementation of an isosurface extraction solution capable of handling large datasets. The Marching Cubes algorithm is the method used to extract the isosurfaces. These are graphical representations of points with a constant value (e.g. matter density) within volumetric datasets. A very useful approach to visualize particular regions of such data. One of the major goals of this work is to get a significant performance improvement, compared to the currently available CPU solutions. The OpenCL framework is used to accelerate the solution. This framework is an open standard for parallel programming of heterogeneous systems recently proposed. Unlike previous programming frameworks for GPUs such as CUDA, with OpenCL the workload can be distributed among CPUs, GPUs, DSPs, and other similar microprocessors.
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Books on the topic "OpenBCI"

1

Soma, Śobhana. Openṭi bāiskopa. Kalakātā: Kyāmpa, 1993.

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Brahmbhatt, Samarth. Practical OpenCV. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-6080-6.

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Soma, Śobhana. Openṭi bāiskopa. Kalakātā: Kyāmpa, 1993.

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OpenCL programming guide. Upper Saddle River, NJ: Addison-Wesley, 2012.

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Sonnenreich, Wes. Building Linux and OpenBSD firewalls. New York: Wiley, 2000.

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The OpenBSD 4.0 crash course. Sebastopol, Calif: O'Reilly, 2007.

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Paco, Hope, and Potter Bruce, eds. Mastering FreeBSD and OpenBSD Security. Sebastopol, CA: O'Reilly, 2005.

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Heterogeneous computing with OpenCL. Waltham, MA: Morgan Kaufmann, 2012.

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Gollapudi, Sunila. Learn Computer Vision Using OpenCV. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4261-2.

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Kowalik, Janusz S. Using OpenCL: Programming massively parallel computers. Amsterdam: IOS Press, 2012.

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Book chapters on the topic "OpenBCI"

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Samson, V. R. R., B. Praveen Kitti, S. Pradeep Kumar, D. Suresh Babu, and Ch Monica. "Electroencephalogram-Based OpenBCI Devices for Disabled People." In Proceedings of 2nd International Conference on Micro-Electronics, Electromagnetics and Telecommunications, 229–38. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4280-5_24.

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Reyes, Ruymán, Iván López-Rodríguez, Juan J. Fumero, and Francisco de Sande. "accULL: An OpenACC Implementation with CUDA and OpenCL Support." In Euro-Par 2012 Parallel Processing, 871–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32820-6_86.

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Singh, Deshanand, and Peter Yiannacouras. "OpenCL." In FPGAs for Software Programmers, 97–114. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-26408-0_6.

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Brahmbhatt, Samarth. "Introduction to Computer Vision and OpenCV." In Practical OpenCV, 3–5. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-6080-6_1.

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Brahmbhatt, Samarth. "3D Geometry and Stereo Vision." In Practical OpenCV, 173–200. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-6080-6_10.

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Brahmbhatt, Samarth. "Embedded Computer Vision: Running OpenCV Programs on the Raspberry Pi." In Practical OpenCV, 201–18. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-6080-6_11.

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Brahmbhatt, Samarth. "Setting up OpenCV on Your Computer." In Practical OpenCV, 7–12. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-6080-6_2.

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Brahmbhatt, Samarth. "CV Bling—OpenCV Inbuilt Demos." In Practical OpenCV, 13–22. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-6080-6_3.

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Brahmbhatt, Samarth. "Basic Operations on Images and GUI Windows." In Practical OpenCV, 23–37. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-6080-6_4.

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Brahmbhatt, Samarth. "Image Filtering." In Practical OpenCV, 41–65. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-6080-6_5.

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Conference papers on the topic "OpenBCI"

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Gunawardane, P. D. S. H., C. W. de Silva, and Mu Chiao. "An Oculomotor Sensing Technique for Saccade Isolation of Eye Movements using OpenBCI." In 2019 IEEE SENSORS. IEEE, 2019. http://dx.doi.org/10.1109/sensors43011.2019.8956542.

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Bermeo, David, Daniel Urgilés, Génesis Vásquez, Diego Almeida, and Omar Alvarado. "Implementation of a Low-Cost Electroencephalography System for the Analysis of Neurological Biosignals for Neuropsychological Studies." In Intelligent Human Systems Integration (IHSI 2022) Integrating People and Intelligent Systems. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe100993.

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Brain Computer Interface (BCI) have developed applications to identify different degrees of cortical activation in different circumstances in humans. This study implemented a BCI system for the analysis of neurological biosignals for studies in Neuropsychology. The acquired information used OpenBCI hardware elements and software to visualize in real time the brain electrical activity set in voltage and frequency parameters. The web application developed allowed visual monitoring of the brain electrical activity of each electrode, the different frequency bands, the averages between cerebral hemispheres and the activation of a servomotor. The distribution of the channels made it possible to obtain the Theta, Alpha, Beta and Gamma brain rhythms in alert and relaxed states with eyes open as well as closed.
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Wang, Xinyue, Shaohui Hou, Li Zhang, Linling Li, Zhen Liang, Zhiguo Zhang, and Gan Huang. "The Real Time EEG Phase Locked Feedback Control for Alpha Amplitude and Frequency Regulation: An OpenBCI Implementation." In ICBBS '20: 2020 9th International Conference on Bioinformatics and Biomedical Science. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3431943.3432284.

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Albawardi, Hessa, Aljohara Almoaibed, Noor Al Abbas, Sarah Alsayed, Tarfa Almaghlouth, and Saleh Alzahrani. "Design of Low-Cost Steady State Visually Evoked Potential-Based Brain Computer Interface Using OpenBCI and Neuromore." In 2021 4th International Conference on Bio-Engineering for Smart Technologies (BioSMART). IEEE, 2021. http://dx.doi.org/10.1109/biosmart54244.2021.9677782.

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De Araújo, Gabriell Alves, Dalvan Griebler, and Luiz Gustavo Leão Fernandes. "Implementação CUDA dos Kernels NPB." In Escola Regional de Alto Desempenho da Região Sul. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/eradrs.2020.10762.

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NAS Parallel Benchmarks (NPB) é um conjunto de benchmarks utilizado para avaliar hardware e software, que ao longo dos anos foi portado para diferentes frameworks. Concernente a GPUs, atualmente existem apenas versões OpenCL e OpenACC. Este trabalho contribui com a literatura provendo a primeira implementação CUDA completa dos kernels do NPB, realizando experimentos com carga de trabalho inédita e revelando novos fatos sobre o NPB.
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Memeti, Suejb, Lu Li, Sabri Pllana, Joanna Kołodziej, and Christoph Kessler. "Benchmarking OpenCL, OpenACC, OpenMP, and CUDA." In the 2017 Workshop. New York, New York, USA: ACM Press, 2017. http://dx.doi.org/10.1145/3110355.3110356.

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Vanderbruggen, Tristan, and John Cavazos. "Generating OpenCL C kernels from OpenACC." In the International Workshop. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2664666.2664675.

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Herdman, J. A., W. P. Gaudin, S. McIntosh-Smith, M. Boulton, D. A. Beckingsale, A. C. Mallinson, and S. A. Jarvis. "Accelerating Hydrocodes with OpenACC, OpenCL and CUDA." In 2012 SC Companion: High-Performance Computing, Networking, Storage and Analysis (SCC). IEEE, 2012. http://dx.doi.org/10.1109/sc.companion.2012.66.

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Gasparakis, Harris. "Heterogeneous compute in computer vision: OpenCL in OpenCV." In IS&T/SPIE Electronic Imaging, edited by Amir Said, Onur G. Guleryuz, and Robert L. Stevenson. SPIE, 2014. http://dx.doi.org/10.1117/12.2054961.

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Sugawara, Makoto, Shoichi Hirasawa, Kazuhiko Komatsu, Hiroyuki Takizawa, and Hiroaki Kobayashi. "A Comparison of Performance Tunabilities between OpenCL and OpenACC." In 2013 IEEE 7th International Symposium on Embedded Multicore Socs (MCSoC). IEEE, 2013. http://dx.doi.org/10.1109/mcsoc.2013.31.

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Reports on the topic "OpenBCI"

1

Tam, Wai Cheong, and Walter W. Yuen. OpenSC :. Gaithersburg, MD: National Institute of Standards and Technology, September 2019. http://dx.doi.org/10.6028/nist.tn.2064.

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Pritchard Jr., Howard. Los Alamos OpenMPI Activities. Office of Scientific and Technical Information (OSTI), November 2020. http://dx.doi.org/10.2172/1726144.

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Hjelm, Nathan Thomas, and Howard Porter Pritchard. OpenMPI and ExxonMobil Topics. Office of Scientific and Technical Information (OSTI), September 2016. http://dx.doi.org/10.2172/1324562.

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Scott, III, and John M. Open Component Portability Infrastructure (OPENCPI). Fort Belvoir, VA: Defense Technical Information Center, November 2009. http://dx.doi.org/10.21236/ada510918.

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Kulp, James, Shepard Siegel, and John Miller. Open Component Portability Infrastructure (OPENCPI). Fort Belvoir, VA: Defense Technical Information Center, March 2013. http://dx.doi.org/10.21236/ada580701.

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Jin, Zheming, Kazutomo Yoshii, Hal Finkel, and Franck Cappello. Evaluation of the OpenCL AES Kernel using the Intel FPGA SDK for OpenCL. Office of Scientific and Technical Information (OSTI), April 2017. http://dx.doi.org/10.2172/1357909.

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Aldrich, Garrett Allen, Soumya Dutta, and Jonathan Lee Woodring. OpenMC In Situ Source Convergence Detection. Office of Scientific and Technical Information (OSTI), May 2016. http://dx.doi.org/10.2172/1253484.

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Dodge, Catherine, Cynthia Irvine, and Thuy Nguyen. A Study of Initialization in Linux and OpenBSD. Fort Belvoir, VA: Defense Technical Information Center, February 2005. http://dx.doi.org/10.21236/ada435220.

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He, Jim, Andrew Spencer, and Eric Chu. OpenCV and TYZX : video surveillance for tracking. Office of Scientific and Technical Information (OSTI), August 2008. http://dx.doi.org/10.2172/942060.

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Lund, Amanda L., and Paul K. Romano. Implementation and Validation of Photon Transport in OpenMC. Office of Scientific and Technical Information (OSTI), December 2018. http://dx.doi.org/10.2172/1490825.

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