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W. Affan Kaysa

Bio: W. Affan Kaysa is an academic researcher. The author has contributed to research in topics: Brain–computer interface & Wheelchair. The author has an hindex of 1, co-authored 1 publications receiving 13 citations.

Papers
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Proceedings ArticleDOI
01 Aug 2013
TL;DR: The design of the BCI platform for commanding the electric wheelchair simulator is proposed and an interchangeable classification database that allows drastic modification of the system input, output, user recognition, and even the classification method is proposed.
Abstract: Brain Computer Interface (BCI) research has developed intensively during past years, especially in the assistive technology development for disabled people, e.g. electric wheelchair. This paper will propose our design of the BCI platform for commanding the electric wheelchair simulator. A wireless EEG device is used because of the need for mobile, comfortable, and user-friendly BCI platform. This paper will cover the design process to build the BCI platform prototype, and evaluation about the result achieved. Our BCI platform consists of Emotiv EPOC wireless EEG, and a computer for EEG acquisition, noise filtering, feature extraction, feature classification, and gives control command to wheelchair simulator that is connected via USB. Power spectral density is used as feature extraction of μ rhythm and artificial neural network with multi layer perceptron is used for classifying the idle and movement condition and for classifying between right hand and left hand movement. The first prototype of our BCI system has an interchangeable classification database that allows drastic modification of the system input, output, user recognition, and even the classification method.

13 citations


Cited by
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Journal ArticleDOI
TL;DR: The background of recent studies on wheelchair control based on BCI for disability and map the literature survey into a coherent taxonomy is determined to provide researchers and developers with a clear understanding of this platform and highlight the challenges and gaps in the current and future studies.

84 citations

Journal ArticleDOI
TL;DR: This analysis evaluated WBCI device enables the system to be wireless, handy, portable and reliable and the whole system can be commercialized for immobilized or handicapped people to provide better care and facility at home.
Abstract: The number of aged and disabled people has been increasing worldwide. To look after these people is a big challenge in this era. However, scientists overcome the problems of handicapped people with the help of the latest communication technologies. The smart home and medical systems are a predominant concept in research and development, specially utilizing the brain-computer interface (BCI) technology to control the daily use appliances. BCI acquires the brain signals that transmit to a digital device for analyzing and interpreting into further command or action but this approach limits the communication range between the brain and the system and becomes bulky because of the wired interface of a brain with the system. Therefore, the main purpose of this research was to design and evaluate a system that empowered the immobilized, handicapped or elderly people to carry out their basic routine tasks wirelessly, for instance, operating home appliances and monitoring vital signs without any dependency. In addition, the subject should have a properly functioning brain and controlled with eye muscle movement. In this research work, wireless BCI (WBCI) technology that is a commercial electroencephalogram headset is used to control home and medical appliances such as a light bulb, a fan, a digital blood pressure monitor and an Infrared deep pain therapeutic belt for dependent people. An Android application is developed name “Smart Home Monitor” that monitors the data from the headset. The designed device is tested on younger (50-year-old) and older (> 50-year-old) individuals to achieve an attention level (0–100). The younger male reached attention level 74.78 within 26.20 s; quicker than younger female and older people. Overall, this research work is unique for the reason that it is suitable for all those people, whose brain and eye muscles are functional even if the rest of the body is paralyzed. This analysis evaluated WBCI device enables the system to be wireless, handy, portable and reliable. Thus, the whole system can be commercialized for immobilized or handicapped people to provide better care and facility at home. Especially, the disable people appreciated this system and want to see its implementation as soon as possible.

52 citations

Journal ArticleDOI
TL;DR: This paper provides a comprehensive review of EEG signal processing in robot control, including mobile robots and robotic arms, especially based on noninvasive brain computer interface systems.
Abstract: There is a significant progress in the development of brain-controlled mobile robots and robotic arms in the recent years. New advances in electroencephalography (EEG) technology have led to the possibility of controlling external devices, such as robots, directly via the brain. The development of brain-controlled robotic devices has allowed people with bodily disabilities to enhance their mobility, individuality, and many types of activity. This paper provides a comprehensive review of EEG signal processing in robot control, including mobile robots and robotic arms, especially based on noninvasive brain computer interface systems. Various filtering approaches, feature extraction techniques, and machine learning algorithms for EEG classification are discussed and summarized. Finally, the conditions of the environments in which robots are used and robot types are also discussed.

29 citations

Book ChapterDOI
01 Jan 2019
TL;DR: Several papers focus on the IoT, which provides the opportunity to integrate the physical world and IT systems in an even greater scale, which leads to the enhancement of efficiency, accuracy, and economics by minimal human intervention.
Abstract: Several papers focus on the IoT ranging from consumer oriented to industrial products. The IoT concept has become usual since the beginning of the 21st century and was introduced formally in 2005 [45, 53]. IoT gives the possibility for lots of uniquely addressable “things” to communicate and exchange information with each other over the existing network systems and protocols [1, 10, 15]. The IoT enables to make information detected by these objects transmittable, and the objects themselves controllable, by using the current network infrastructure [13, 18]. This provides the opportunity to integrate the physical world and IT systems in an even greater scale, which leads to the enhancement of efficiency, accuracy, and economics by minimal human intervention.

23 citations

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