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Proceedings ArticleDOI

Controlling an arduino robot using Brain Computer Interface

TL;DR: This paper establishes an application to control a robot on the Arduino platform by the use of a BCI system, which does not require training for individual users and achieves around 96% accuracy using computationally inexpensive feature extraction and classification techniques.
Abstract: The ability to acquire Electroencephalogram (EEG) signals from the brain has led to the development of Brain Computer Interfaces (BCI), which capture signals generated by the physical processes in the brain and use them to control external devices. In this paper, we establish an application to control a robot on the Arduino platform by the use of a BCI system, which does not require training for individual users. We present the design and development of a BCI processing pipeline built on open-source platforms using the Emotiv EEG headset. Our system achieves around 96% accuracy using computationally inexpensive feature extraction and classification techniques, namely, band power and Support Vector Machines (SVM). We are also able to guide a robot's movement efficiently using multiple intents.
Citations
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Proceedings ArticleDOI
06 Apr 2016
TL;DR: The qualitative approach of this project is to develop a system which minimizes the working cost and also reduces the time for digging operation and seed sowing operation by utilizing solar energy to run the agribot.
Abstract: The Discovery of Agriculture is the first big step towards civilized life, advancement of agricultural tools is the basic trend of agricultural improvement. Now the qualitative approach of this project is to develop a system which minimizes the working cost and also reduces the time for digging operation and seed sowing operation by utilizing solar energy to run the agribot. In this machine, solar panel is used to capture solar energy and then it is converted into electrical energy which is used to charge battery, which then gives the necessary power to a shunt wound DC motor. Ultrasonic Sensor and Digital Compass Sensor are used with the help of Wi-Fi interface operated on Android Application to manoeuvre robot in the field. This brings down labour dependency. Seed sowing and digging robot will move on various ground contours and performs digging, sowing the seed and covers the ground by closing it. The paper spells out the complete installation of the agribot including hardware and software facet.

33 citations


Cites background from "Controlling an arduino robot using ..."

  • ...The future scope for this paper is not only detecting obstacle but also avoiding it successfully without disturbing the main course of the system [9]....

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Posted ContentDOI
14 Jul 2020-bioRxiv
TL;DR: The use of low-cost electroencephalography (EEG) devices has become increasingly available over the last decade as discussed by the authors and one of these devices, Emotiv EPOC, is currently used in a wide variety of settings, including brain-computer interface (BCI) and cognitive neuroscience research.
Abstract: BACKGROUND Commercially-made low-cost electroencephalography (EEG) devices have become increasingly available over the last decade. One of these devices, Emotiv EPOC, is currently used in a wide variety of settings, including brain-computer interface (BCI) and cognitive neuroscience research. PURPOSE The aim of this study was to chart peer-reviewed reports of Emotiv EPOC projects to provide an informed summary on the use of this device for scientific purposes. METHODS We followed a five-stage methodological framework for a scoping review that included a systematic search using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. We searched the following electronic databases: PsychINFO, MEDLINE, Embase, Web of Science, and IEEE Xplore. We charted study data according to application (BCI, clinical, signal processing, experimental research, and validation) and location of use (as indexed by the first author’s address). RESULTS We identified 382 relevant studies. The top five publishing countries were the United States (n = 35), India (n = 25), China (n = 20), Poland (n = 17), and Pakistan (n = 17). The top five publishing cities were Islamabad (n = 11), Singapore (n = 10), Cairo, Sydney, and Bandung (n = 7 each). Most of these studies used Emotiv EPOC for BCI purposes (n = 277), followed by experimental research (n = 51). Thirty-one studies were aimed at validating EPOC as an EEG device and a handful of studies used EPOC for improving EEG signal processing (n = 12) or for clinical purposes (n = 11). CONCLUSIONS In its first 10 years, Emotiv EPOC has been used around the world in diverse applications, from control of robotic limbs and wheelchairs to user authentication in security systems to identification of emotional states. Given the widespread use and breadth of applications, it is clear that researchers are embracing this technology.

15 citations

Proceedings ArticleDOI
01 Nov 2016
TL;DR: The results obtained indicate that the proposed approach is effective for detecting the eye-wink commands with a good rate of accuracy (over 93%) and allowed the development of a Head-Computer Interface that enables complete interaction with a robotic arm.
Abstract: A relative simple approach based on the computation of the area of a parametric curve produced by the 2D space representation of a set of parametric experimental functions defined by the signals of only two active EEG electrodes of a low cost neuroheadset (Emotiv EPOC) is proposed on this paper for the fast recognition of eye winks activity as control commands. This approach together with the use of the signals from the gyroscope available in the EPOC device, allowed the development of a Head-Computer Interface that enables complete interaction with a robotic arm. The results obtained indicate that the proposed approach is effective for detecting the eye-wink commands with a good rate of accuracy (over 93%).

14 citations


Cites background from "Controlling an arduino robot using ..."

  • ...…sense, in recent years, there has been a considerable increase in research approaches about controlling robots by using signals of biological nature such as electroencephalographic (EEG) and electromyographic (EMG) signals, for allowing the human brain to interact with control computers [2] [3]....

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Journal ArticleDOI
01 Jul 2021
TL;DR: The results of testing the value of the ultrasonic sensor distance found different conditions that occur, and the condition of the prototype cleaning robot for the road floor cleaning is obtained, while the distance <15 cm, the condition for the prototype of the street floor cleaning robot has stopped.
Abstract: The entire floor cleaning robot is divided into several parts, namely consisting of an Ultrasonic Sensor, Motor Shield L298, Arduino Uno microcontroller, Servo, and Dc Motor. This tool works when the Arduino Uno microcontroller processes the ultrasonic sensor as a distance detector and a DC motor as a robot driver, then the DC motor is driven by the Motor Shield L298. When an ultrasonic sensor detects a barrier in front of it, the robot will automatically look for a direction that is not a barrier to the floor cleaning robot. The distance value on the sensor has been determined, that is, when the distance read by the ultrasonic sensor is below 15 cm. The results of testing the value of the ultrasonic sensor distance found different conditions that occur. In a distance of> 15 cm, the condition of the prototype cleaning robot for the road floor cleaning is obtained, while the distance <15 cm, the condition for the prototype of the street floor cleaning robot has stopped.

13 citations


Cites methods from "Controlling an arduino robot using ..."

  • ...Then an automatic floor cleaning robot was designed using an ultrasonic sensor was studied by gargava [10]....

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Journal ArticleDOI
TL;DR: This review gives an overview of studies found in the recent scientific literature, reporting measurements of biosignals such as ECG, EMG, sweat and other health-related parameters by single circuit boards, showing new possibilities offered by Arduino, Raspberry Pi etc. in the mobile long-term acquisition of biosignedals.
Abstract: To measure biosignals constantly, using textile-integrated or even textile-based electrodes and miniaturized electronics, is ideal to provide maximum comfort for patients or athletes during monitoring. While in former times, this was usually solved by integrating specialized electronics into garments, either connected to a handheld computer or including a wireless data transfer option, nowadays increasingly smaller single circuit boards are available, e.g., single-board computers such as Raspberry Pi or microcontrollers such as Arduino, in various shapes and dimensions. This review gives an overview of studies found in the recent scientific literature, reporting measurements of biosignals such as ECG, EMG, sweat and other health-related parameters by single circuit boards, showing new possibilities offered by Arduino, Raspberry Pi etc. in the mobile long-term acquisition of biosignals. The review concentrates on the electronics, not on textile electrodes about which several review papers are available.

10 citations

References
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Journal ArticleDOI
TL;DR: In this article, the authors look at how insights from some of the pioneers of neuroscience have begun to be integrated with today's technology, so bringing about the dawn of an era of brain and computer interfacing.
Abstract: 'Can the brain understand the brain?Can it understand the mind?'Such questions, here posed by neurophysiologist and 1981 Nobel laureate David Hubel, are under constant debate, but through the investigations of neurobiologists, psychologists, and physiologists, current knowledge and understanding has come a long way since brain exploration began hundreds of years BC. This article looks at how insights from some of the pioneers of neuroscience have begun to be integrated with today's technology, so bringing about the dawn of an era of brain and computer interfacing. One result has been brain–computer interfaces that can liberate the thoughts of those suffering from 'locked in' syndrome, by detection and interpretation of the brain's physiological signals. Also, manipulation of and support for the body's electrical and chemical signalling network has led to a variety of rehabilitation and therapeutic benefits, for example the possibility of giving sight to the blind. Brain–computer interfacing offers...

736 citations


"Controlling an arduino robot using ..." refers methods in this paper

  • ...These EEG signals are processed using signal processing techniques and mapped to intents using machine learning algorithms [14]....

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Journal ArticleDOI
TL;DR: The OpenViBE software platform is described which enables researchers to design, test, and use braincomputer interfaces (BCIs) and its suitability for the design of VR applications controlled with a BCI is shown.
Abstract: This paper describes the OpenViBE software platform which enables researchers to design, test, and use brain--computer interfaces (BCIs). BCIs are communication systems that enable users to send commands to computers solely by means of brain activity. BCIs are gaining interest among the virtual reality (VR) community since they have appeared as promising interaction devices for virtual environments (VEs). The key features of the platform are (1) high modularity, (2) embedded tools for visualization and feedback based on VR and 3D displays, (3) BCI design made available to non-programmers thanks to visual programming, and (4) various tools offered to the different types of users. The platform features are illustrated in this paper with two entertaining VR applications based on a BCI. In the first one, users can move a virtual ball by imagining hand movements, while in the second one, they can control a virtual spaceship using real or imagined foot movements. Online experiments with these applications together with the evaluation of the platform computational performances showed its suitability for the design of VR applications controlled with a BCI. OpenViBE is a free software distributed under an open-source license.

687 citations

Journal ArticleDOI
TL;DR: The results show that subjects can rapidly master the authors' asynchronous EEG-based BCI to control a wheelchair and can autonomously operate the BCI over long periods of time without the need for adaptive algorithms externally tuned by a human operator to minimize the impact of EEG non-stationarities.

644 citations

Journal ArticleDOI
TL;DR: This study reveals weaknesses in BCI studies related to reporting the methods of handling EMG and EOG artifacts and develops automatic methods to handle artifacts or to design BCI systems whose performance is robust to the presence of artifacts.

566 citations


"Controlling an arduino robot using ..." refers background in this paper

  • ...Electrocardiography artifacts which are derived from heartbeats and respiration may also be artifacts to the EEG signal [6]....

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Journal ArticleDOI
01 Jun 2000
TL;DR: This paper describes a research approach to develop a brain-computer interface (BCI) based on recognition of subject-specific EEG patterns using EEG signals recorded from sensorimotor areas during mental imagination of specific movements.
Abstract: Describes a research approach to develop a brain-computer interface (BCI) based on recognition of subject-specific EEG patterns. EEG signals recorded from sensorimotor areas during mental imagination of specific movements are classified on-line and used e.g. for cursor control. In a number of on-line experiments, various methods for EEG feature extraction and classification have been evaluated.

533 citations


"Controlling an arduino robot using ..." refers methods in this paper

  • ...Other known BCI systems include the Graz BCI [15], Berlin Brain Computer Interface [11] and the IDIAP Brain-Computer Interface [7]....

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  • ...Computation of band-power as a feature has been previously used in BCI systems [15, 28, 21]....

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