30 research outputs found

    Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review

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    © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).The automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities are used in the analyzed studies, including facial expressions, prosody of speech, and physiological signals. Regarding representation models, the basic emotions are the most frequently recognized, especially happiness, fear, and sadness. Both single-channel and multichannel approaches are applied, with a preference for the first one. For multimodal recognition, early fusion was the most frequently applied. SVM and neural networks were the most popular for building classifiers. Qualitative analysis revealed important clues on participant group construction and the most common combinations of modalities and methods. All channels are reported to be prone to some disturbance, and as a result, information on a specific symptoms of emotions might be temporarily or permanently unavailable. The challenges of proper stimuli, labelling methods, and the creation of open datasets were also identified.Peer reviewedFinal Published versio

    A physiological signal database of children with different special needs for stress recognition

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    This study presents a new dataset AKTIVES for evaluating the methods for stress detection and game reaction using physiological signals. We collected data from 25 children with obstetric brachial plexus injury, dyslexia, and intellectual disabilities, and typically developed children during game therapy. A wristband was used to record physiological data (blood volume pulse (BVP), electrodermal activity (EDA), and skin temperature (ST)). Furthermore, the facial expressions of children were recorded. Three experts watched the children's videos, and physiological data is labeled "Stress/No Stress" and "Reaction/No Reaction", according to the videos. The technical validation supported high-quality signals and showed consistency between the experts.Scientific and Technological Research Council of Turkey Technology and Innovation Funding Programmes Directorat

    Development of a cognitive robotic system for simple surgical tasks

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    The introduction of robotic surgery within the operating rooms has significantly improved the quality of many surgical procedures. Recently, the research on medical robotic systems focused on increasing the level of autonomy in order to give them the possibility to carry out simple surgical actions autonomously. This paper reports on the development of technologies for introducing automation within the surgical workflow. The results have been obtained during the ongoing FP7 European funded project Intelligent Surgical Robotics (I-SUR). The main goal of the project is to demonstrate that autonomous robotic surgical systems can carry out simple surgical tasks effectively and without major intervention by surgeons. To fulfil this goal, we have developed innovative solutions (both in terms of technologies and algorithms) for the following aspects: fabrication of soft organ models starting from CT images, surgical planning and execution of movement of robot arms in contact with a deformable environment, designing a surgical interface minimizing the cognitive load of the surgeon supervising the actions, intra-operative sensing and reasoning to detect normal transitions and unexpected events. All these technologies have been integrated using a component-based software architecture to control a novel robot designed to perform the surgical actions under study. In this work we provide an overview of our system and report on preliminary results of the automatic execution of needle insertion for the cryoablation of kidney tumours

    Design and Implementation of an Assistive Controller for Rehabilitation Robotic Systems

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    The goal of our research is to develop an assistive controller for robotic rehabilitation of the upper extremity after stroke. The controller is used to provide robotic assistance to participants to help them to track a desired motion trajectory required for the rehabilitation task in an accurate and concentrated manner. This rehabilitation task is designed to ensure concentrated repetitive motion that requires cognitive processing. Experimental results on unimpaired participants are presented to demonstrate the effectiveness and feasibility of the proposed controller

    A New Method of Force Control for Unknown Environments

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    Current robotic systems are expected to interact with unknown environment where controlling the interaction forces becomes an important issue. We propose a new control technique for force control on unknown environments that tunes the force controller based on online estimation of the environment parameters. However, the proposed approach overcomes the need for precise estimation of environment parameters, which are needed in many system identification-based force control approaches. This framework uses an artificial neural network (ANN)-based proportional-integral (PI)-gain scheduling force controller to track the desired force by adjusting control gains such that error in parameter estimation can be accommodated. Experimental results are presented to demonstrate the efficacy of the proposed control framework. Finally, the advantages and limitations of the proposed controller are discussed

    Near-constant beamwidth quadruple bandwidth double-ridged horn antenna design

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    Barkana, Duygun Erol/0000-0002-8929-0459WOS: 000490490300022It is well known that the beamwidths of horn antennas are inversely proportional to frequency. Previous studies point to minimum +/- 12% beamwidth stability within a maximum of 2.5:1 bandwidth (BW) ratio. To extend this BW, a design methodology for broadband double-ridged horn antenna (DRHA) is proposed and applied to 4.5-18 GHz frequency band. Firstly, a conventional DRHA is designed and studied to compare the beamwidth variation of wideband horn antennas. By explicitly addressing the shortcomings of conventional DRHA, DRHA is redesigned and near-constant beamwidth DRHA is proposed using the modifications implemented on the sidewalls. the antenna utilises ridges to extend the frequency band, unlike other wideband constant beamwidth horns. the authors show that ridged horns, whose dimensions are appropriately designed and modified, can have stable beamwidths. Then, properly positioned curved pinwalls are designed to provide considerable improvement in H-plane beamwidth constancy. Broadband double-ridged waveguide-to-coaxial adapter is also designed for 50 omega reference. the prototype is manufactured, and the measured antenna exhibits wideband characteristics with 30.9 degrees +/- 2.7 degrees half power beamwidth in H-plane over 4:1 BW ratio. This variation corresponds to +/- 8.7% beamwidth stability along with the target frequency band
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