PubMed İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397
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Browsing PubMed İndeksli Yayınlar Koleksiyonu by Department "AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü"
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Article Citation - WoS: 11Citation - Scopus: 14Detection of Movement Intention in EEG-Based Brain-Computer Interfaces Using Fourier-Based Synchrosqueezing Transform(World Scientific Publ Co Pte Ltd, 2021) Karakullukcu, Nedime; Yilmaz, BulentPatients with motor impairments need caregivers' help to initiate the operation of brain-computer interfaces (BCI). This study aims to identify and characterize movement intention using multichannel electroencephalography (EEG) signals as a means to initiate BCI systems without extra accessories/methodologies. We propose to discriminate the resting and motor imagery (MI) states with high accuracy using Fourier-based synchrosqueezing transform (FSST) as a feature extractor. FSST has been investigated and compared with other popular approaches in 28 healthy subjects for a total of 6657 trials. The accuracy and f-measure values were obtained as 99.8% and 0.99, respectively, when FSST was used as the feature extractor and singular value decomposition (SVD) as the feature selection method and support vector machines as the classifier. Moreover, this study investigated the use of data that contain certain amount of noise without any preprocessing in addition to the clean counterparts. Furthermore, the statistical analysis of EEG channels with the best discrimination (of resting and MI states) characteristics demonstrated that F4-Fz-C3-Cz-C4-Pz channels and several statistical features had statistical significance levels, p, less than 0.05. This study showed that the preparation of the movement can be detected in real-time employing FSST-SVD combination and several channels with minimal pre-processing effort.Review Aerial Swarms: Recent Applications and Challenges(Springer, 2021) Mohamed Abdelkader; Samet GülerPurpose of review: Currently, there is a large body of research on multi-agent systems addressing their different system theoretic aspects. Aerial swarms as one type of multi-agent robotic systems have recently gained huge interest due to their potential applications. However, aerial robot groups are complex multi-disciplinary systems and usually research works focus on specific system aspects for particular applications. The purpose of this review is to provide an overview of the main motivating applications that drive the majority of research works in this field, and summarize fundamental and common algorithmic components required for their development._x000D_ _x000D_ Recent findings: Most system demonstrations of current aerial swarms are based on simulations, some have shown experiments using few 10 s of robots in controlled indoor environment, and limited number of works have reported outdoor experiments with small number of autonomous aerial vehicles. This indicates scalability issues of current swarm systems in real world environments. This is mainly due to the limited confidence on the individual robot's localization, swarm-level relative localization, and the rate of exchanged information between the robots that is required for planning safe coordinated motions._x000D_ _x000D_ Summary: This paper summarizes the main motivating aerial swarm applications and the associated research works. In addition, the main research findings of the core elements of any aerial swarm system, state estimation and mission planning, are also presented. Finally, this paper presents a proposed abstraction of an aerial swarm system architecture that can help developers understand the main required modules of such systems.
