Suprijanto

Bio: Suprijanto is an academic researcher from Bandung Institute of Technology. The author has contributed to research in topics: Brain–computer interface & Wheelchair. The author has an hindex of 7, co-authored 81 publications receiving 229 citations. Previous affiliations of Suprijanto include Delft University of Technology.

Image contrast enhancement for film-based dental panoramic radiography

Abstract: The dental panoramic radiography is one of dental imaging that used to visualize the entirety of the maxilla and mandible jaws on the one image planes. Although the direct digital panoramic radiography has been available, however film-based panoramic radiography is still used on the mostly dental clinic and laboratory in Indonesia. The quality of film-based image has significant limitation due to chemical processing and image enhancement cannot be done if required. Therefore, digitized film-based image to digital image was required to allow image enhancements in order to improve the interpretability quality of information in the image. Digitized film-based image is performed using a flatbed scanner on transmission and reflection mode. In this paper, the contrast quality of digital image that scanned using both mode is evaluated based on statistic image characteristic. The results showed that the quality of digitized image using transmission mode is better than using reflection mode. However, if direct digital imaging is used as a gold standard, image enhancement on digitized image is still required. Four methods, i.e. contrast stretching, HE, AHE, and CLAHE are used to attempt improve the quality digitized image. Evaluation of the preference image quality is performed based on objective criterion. The preference image quality for digitized panoramic image can be obtained by using image enhancement based on CLAHE-Rayleigh method, that indicated by the lowest value of mean, standard deviation, RMSE, and average difference and the higher value of NAE and SAE.

A collaborative control of brain computer interface and robotic wheelchair

Abstract: This paper presents a new scheme in collaborating non-invasive brain computer interface (BCI) and a wheelchair equipped with robotic systems. The BCI system implements steady state visual evoked potential (SSVEP) method that extracts features from electro-encephalography (EEG) signals in determining the intentions or commands from human-brain. The classification of EEG signals utilizes filter-bank in accordance with frequency of the stimuli visual. The user intentions, which are to move “left”, “right”, and “forward”, and “stop” are collaborated with an intelligent robotic system of a wheelchair. The wheelchair system is equipped with environment recognition sensors. The collaborative control is to manage the motion of the wheelchair based upon the intention of the user and the condition of the environment. The scenario is limited to the collaboration of BCI-robotic wheelchair in a corridor environment with walls on both sides. The user intention is set to “forward”. The intelligent robotic wheelchair perform wall following and obstacle avoidance motions while receiving the command “forward”. Also, it performs emergency-stop if the extracted intentions from the BCI put the user in dangerous situation. Experimental results are conducted to show the effectiveness of the proposed method.

Effects of Colour towards Underwear Choice Based on Electroencephalography (EEG)

Abstract: The purpose of this paper is to investigate whether colours as stimuli can affect underwear choice based on consumers’ EEG recording as biological response to elicit preferences towards underwear p...

Design of Brain-computer interface platform for semi real-time commanding electrical wheelchair simulator movement

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.

Identification of alertness state based on EEG signal using wavelet extraction and neural networks

Abstract: This research proposed identification of alertness state using wavelet transformation and neural networks. Wavelet extracted three wave components of an electroencephalogram (EEG) signal, namely alpha, beta and theta as input of neural networks, so that reduce 256 Hz recording into 28 data each second. It also used a asymmetric of the channel that improved recognition. EEG signals was obtained from four subject as training data which was tested to other four subjects. Each subject recorded with blue light stimulation during eight minutes and continued no stimulation in last eight minutes. It was sit position. Light stimulation was intended to increase alertness the subject. This research focused on develop identification of alertness state system. Based on the results of testing the system on the new data showed that C3 and C4 channel made best classification with 81% recognition accuracy. From all data, less alert state gave recognition more than other. Characteristic of data was significant factor of the result.

Principles of Neural Science

Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Sleep and wakefulness

Abstract: sleep-wake cycle: its physiology and impact on health the evolutionary theory of sleep and wakefulness sleep and wakefulness browserfame how the circadian rhythm affects sleep, inside this issue maintenance of wakefulness test as a predictor of sleep sleep in the unresponsive wakefulness syndrome and neurochemistry of sleep and wakefulness assets maintenance for wakefulness testing (mwt) sleep and wakefulness disturbances in parkinson’s disease sleep wakefulness ncpdev practice parameters for clinical use of the multiple sleep the neurobiology of sleep and wakefulness neuropharmacology of sleep and wakefulness the clinics sniffing in infant rats during sleep and wakefulness the regulation of sleep and wakefulness by the sleep and wakefulness wenyen the international journal of sleepand wakefulness sleep and wakefulness pwcgba swallowing in sleep and wakefulness in adult cats central mechanisms of the sleep–wakefulness cycle control sleep and wakefulness vivoce sleep/wakefulness management in continuous/sustained wakefulness (not sleep) promotes generalization of word neuroendocrine correlates of sleep/wakefulness wakefulness and sleep explorable sleep and wakefulness during holy month of ramadan shining light on wakefulness and arousal the de lecea lab neuropharmacology of sleep and wakefulness sleep wakefulness 1st edition niraj to eat or to sleep? orexin in the regulation of feeding brain control of wakefulness and sleep brain control of neural correlates of wakefulness, sleep, and general the clinical use of the mslt and mwt sleep and wakefulness kugauk sleep and wakefulness guyver sleep and wakefulness justinshingles sleep and wakefulness correction in different seasons from sleep and wakefulness neppco lsd and tryptamine effects on sleep/wakefulness and circadian and wakefulness-sleep modulation of cognition in neural circuitry of wakefulness and sleep cell hypothalamic regulation of sleep and circadian rhythms sleep and wakefulness faheds functional anatomy of the sleep wakefulness cycle wakefulness sleep and wakefulness agmr arousal and regulatory systems: workshop proceedings june modeling sleep and wakefulness in the thalamocortical system wordsworthian wakefulness project muse sleep and wakefulness healthline

Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

Abstract: Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices through the utilization of brain waves. It is worth noting that the application of BCI is not limited to medical applications, and hence, the research in this field has gained due attention. Moreover, the significant number of related publications over the past two decades further indicates the consistent improvements and breakthroughs that have been made in this particular field. Nonetheless, it is also worth mentioning that with these improvements, new challenges are constantly discovered. This article provides a comprehensive review of the state-of-the-art of a complete BCI system. First, a brief overview of electroencephalogram (EEG)-based BCI systems is given. Secondly, a considerable number of popular BCI applications are reviewed in terms of electrophysiological control signals, feature extraction, classification algorithms, and performance evaluation metrics. Finally, the challenges to the recent BCI systems are discussed, and possible solutions to mitigate the issues are recommended.

A Comprehensive Review of Smart Wheelchairs: Past, Present, and Future

Abstract: A smart wheelchair (SW) is a power wheelchair (PW) to which computers, sensors, and assistive technology are attached. In the past decade, there has been little effort to provide a systematic review of SW research. This paper aims to provide a complete state-of-the-art overview of SW research trends. We expect that the information gathered in this study will enhance awareness of the status of contemporary PW as well as SW technology and increase the functional mobility of people who use PWs. We systematically present the international SW research effort, starting with an introduction to PWs and the communities they serve. Then, we discuss in detail the SW and associated technological innovations with an emphasis on the most researched areas, generating the most interest for future research and development. We conclude with our vision for the future of SW research and how to best serve people with all types of disabilities.