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7th International Conference on Bio-Inspired systems and Signal Processing, BIOSIGNALS 2014 - Part of 7th International Joint Conference on Biomedical engineering systems and Technologies, BIOSTEC 2014

作者： Ahmad, Malik Anas Majeed, Waqas Khan, Nadeem Ahmad Signal Image and Video Processing Lab SBASSE LUMS Lahore Pakistan Robotics and Intelligent Systems Engineering Lab SMME NUST Islamabad Pakistan

ISBN: (纸本)9789897580116

During the diagnosis of epilepsy, computer aided methods can significantly supplement a neurologist by automatically identifying the epileptic patterns in an EEG. In the last decade immense amount of work has been done in the field of EEG based computer aided diagnosis of epilepsy. Even after so much work these tools are not getting used up to their full potential. In this paper we have very briefly discussed some of the previously used signal processing and machine learning techniques which are proposed for epileptic pattern detection. We have concluded this paper by suggesting some additions in the previous method which can make these systems more helpful, detailed and precise for the neurologist. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

关键词： Electroencephalography

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A Low-Cost Vision-Based System for Displacement Analysis in Earthquake Research

A Low-Cost Vision-Based System for Displacement Analysis in ...

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RSI/ISM International Conference on robotics and Mechatronics

作者： Bijan Binaee Mahyar Khayatkhoei Hadi Moradi Amirhossein Nazemi Abdollah Hosseini Control and Intelligent Processing Center Advanced Robotics and Intelligent Systems Lab School of ECE University of Tehran Intelligent Systems Research Institute SKKU South Korea School of Civil Engineeringg College of Engineering University of Tehran

ISBN: (纸本)9781467372350

Measuring linear and angular displacement with high accuracy requires expensive equipment and may interfere with the measurements due to sensors weight and size. In this paper, we propose a low cost vision based approach for measuring linear & angular displacement that can make the earthquake research more *** keep detecting process as fast as possible and meet real-time demands, a typical marker with a peculiar color inside chooses and all instructions performed by Intel CVLib filters. So according to the tests, if the minimum requirement are met, the proposed method can detect marker up to 25 frames per second. Finally, a prototype software implemented to analysis functionality and accuracy of proposed algorithm. The results shown that this vision-based method can achieve accuracy of 0.1mm, with an off-the-shelf three pixel per millimeter, and it can be perfectly used instead of traditional instruments such as LVDT.

关键词： Rotoray-displacement tracking displacement tracking LVDT instrumentation shaking table seismology image processing

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Classification of left/right hand movement from EEG signal by intelligent algorithms

Classification of left/right hand movement from EEG signal b...

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International Conference on Computer Applications and Industrial Electronics (ICCAIE)

作者： Muhammad Zeeshan Baig Ehtasham Javed Yasar Ayaz Waseem Afzal Syed Omer Gillani Muhammad Naveed Mohsin Jamil Department of Robotics and Artificial Intelligence Robotics and Intelligent Systems Engineering (RISE) Lab Islamabad Pakistan Centre for Intelligent Signal and Imaging Research (CISIR) Universiti Teknologi PETRONAS Malaysia Department of Electronic Engineering Mohammad Ali Jinnah University Islamabad Pakistan

Brain Computer interface (BCI) shown enormous ability to advance the human way of life. Furthermore its application is also targeting the disabled ones. In this research, we have implemented a new approach to classify EEG signals more efficiently. The dataset used for this purpose is from BCI competition-II 2003 named Graz database. Initial processing of the EEG signals has been carried out on 2 electrodes named C3 & C4; after that the bi-orthogonal wavelet coefficients, Welench Power Spectral Density estimates and the average power were used as a feature set for classification. We have given a relative study of currently used classification algorithms along with a new approach for classification i.e. Self-organizing maps (SOM) based neural network technique. It is used to classify the feature vector obtain from the EEG dataset, into their corresponding classes belong to left/right hand movements. Algorithms have been implemented on both unprocessed features and processed reduced feature sets. Principal component Analysis (PCA) has been used for feature reduction. Measured data revealed that the maximum classification accuracy of 84.17% on PCA implemented reduce feature set has been achieved using SOM based classifier. Furthermore, the classification accuracy has been increased about 2% by simply using bi-orthogonal Wavelet transform rather than Daubechies wavelet transform.

关键词： Feature extraction Electroencephalography Wavelet transforms Classification algorithms Support vector machine classification Electrodes

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Opening remarks

2016 International Conference on Advances in Human Machine I...

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2016 International Conference on Advances in Human Machine Interaction, HMI 2016 2016年

作者： Nagaraja, Ch. Swamy, J. Nagendra Rajendra, J. Khan, M.S. Vishwanath Reddy, D.S. Manjunath, N. Dillmann, Ruediger Tarn, Tzyh Jong Zhao, Qianchuan Ammi, Mehdi Zuberek, Wlodek M. Sandhu, P.S. Patthira Newman, K. De Silva Liyanage, Chandratilak Hassan, Sohair Aly Aly Sun, Kien Wen Rahman, Md. Moshiur Ordoño, E. Evangelista Sharma, R.K. Mishra, Preeti Chandel, B.S. Singla, Ekta Petric, Tadej Zhong, Yu Jiglar, Janson Alemzadeh, Kazem Asokan, T. Tripathi, Animesh Tripathi, Manoj Ram, Swaminath Shrma, M.K. Panday, P.N. Kumar, Devendra Hinchey, Mike Stilman, Boris Suraj, Zbigniew Pal, Sankar K. Sasi, Sreela Rajan, Deepu Marshall, Roger G. Abraham, Ajith Peter S, David Paul, Vargheese Gopakumar, V. Dustdar, Schahram Soto, Sebastián Ventura Rausch, Andreas Angelis, Lefteris Nelson, Andrew L. Botzheim, Janos Bernardino, Heder Soares Zboril, Frantisek Ane, Bernadetta Kwintiana Maeda, Toshiyuki Sakalauskas, Virgilijus Hann, Garenth Lim King Samek, Jan Romero Salguero, José Raúl Varghese, Kuruvilla Kriksciuniene, Dalia Mathew, Jimson Reif, Wolfgang Mauri, Giancarlo Cabrerizo Lorite, Francisco Javier Özcan, Ender Cho, Sung-Bae Paily, Roy P. Rezankova, Hana Tudjarov, Boris Hong, Wei-Chiang De Oliveira, José Valente Flores Romero, Juan Jose Oskouei, Rozita Jamili Cicchetti, Antonio Roy, Chanchal Segura, Sergio Samuel, C. Mallet, Frédéric Mernik, Marjan Punnekkat, Sasikumar Waseemulla, A. Sri Devaraj Urs Educational Trust Bangalore India R. L. Jalappa Institute of Technology Doddaballapur Bangalore India Humanoids and Intelligence Systems Lab Kalsruhe Germany Electrical and Systems Engineering Washington University in St. Louis United States Deputy Director of Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing China Department of Computer Science CNRS/LIMSI Lab AMI Group France Memorial University St. John'sNL Canada RBIT and Bio-Technology India LR University Thailand University of Colorado at Boulder Boulder United States Faculty of Science University of Brunei Brunei University of Kuala Lumpur Malaysia National Chiao Tung University Taiwan EPR Centre Bangladesh Mapua Institute of Technology Philippines ARO CWC Lucknow India Mpec Kanpur India DSC DBS Kanpu India Indian Institute of Technology Ropar India Jozaf Stefan Institute Department of Automation Biocyernetics and Robotics Ljubljana Slovenia Robotics Institute Carnegie Mellon University Pittsburgh United States Faculty of Engineering University of Bristol United Kingdom Department of Engineering Design Indian Institute of Technology Madras India Lucknow Uni Lucknow India CSJM Uni Kanpur India UPPCB Lucknow India PCB Roorkee India Awadh Uni Faijabad India Agra Uni Agra India Lero University of Limerick Ireland University of Colorado Denver United States University of Rzeszow Poland Indian Statistical Institute Kolkata India Gannon University PA United States Nanyang Technical University Singapore Singapore Plymouth State University NH United States MIR Labs United States Cochin University of Science and Technology India State Project Facilitation Unit TEQIP Kerala India Technical University of Vienna Austria University of Cordoba Spain Clausthal University of Technology Germany Aristotle University of Thessaloniki Greece Androtics LLC TucsonAZ United States Tokyo Metropolitan University Japan Federal Unive

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Control of robotic arm manipulator with haptic feedback using programmable system on chip

Control of robotic arm manipulator with haptic feedback usin...

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International Conference on robotics and Emerging Allied Technologies in engineering (iCREATE)

作者： Muhammad Yaqoob Sardar Rushan Qaisrani Muhammad Waqas Yasar Ayaz Sohail Iqbal Sajid Nisar Department of Electrical Engineering National University of Sciences and Technology (NUST) Islamabad Pakistan Robotics & Intelligent Systems Engineering (RISE) Lab. National University of Sciences and Technology (NUST) Islamabad Pakistan

Programmable system on chip (PSoC) is used to control six degree of freedom robotic arm manipulator with haptic or force feedback system. Polar coordinates system is used to cover three dimensional space by robotic arm manipulator. Primarily use of this system is in intelligent industrial manufacturing, gaming industry and most importantly robots assisted surgery. Master-slave control topology is used along with 2-way feedback. PSoC is used to monitor state of force sensors and digital encoders mounted on robotic manipulator. Along with monitoring it also used to manipulate these values according to 2-way feedback between master-slave control topology. Experimental results representing force feedback are shown in the graphical userinterface.

关键词： Robot kinematics Haptic interfaces Grippers Force Hardware Robot sensing systems

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Determining mood via emotions observed in face by induction

Determining mood via emotions observed in face by induction

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Mojgan Hashemian Hadi Moradi Maryam S Mirian Mehdi Tehrani-doost Advanced Robotics and Intelligent Systems Lab University of Tehran Iran School of Electrical and Computer Engineering University of Tehran Iran Department of Psychiatry Tehran University of Medical Science Iran

Determining the mood of a person is an important step in the Human-Robot interaction. In this paper, we propose a human-inspired approach in which the changes in emotions, done using emotion induction, can be used to determine the mood of a person. The emotion induction, which can be done through robot actions or through showing video clips, stimulates changes in the emotions of the person, reducing the observation time needed to estimate mood. Consequently, the changes in the emotions, which are biased by his/her mood can be used by a robot to determine the mood of a person. To do so, we induced happy emotions by showing a comical clip and measured the intensity of each happy and sad emotions, and also the intensity of the neutral state. Then we extracted a feature set, including both time and frequency domain features, which is used to determine the mood of the person. The approach has been implemented and compared to no-emotion-induction approach and shows better results. Based on the classification results, the approach is able to distinguish between good vs. bad moods with the accuracy of 91.5% with 0.1 mean absolute error. But the neutral state was not distinguishable well.

关键词： Mood Robots Accuracy Feature extraction Face Educational institutions Human-robot interaction

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Determining mood using emotional features

Determining mood using emotional features

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International Symposium on Telecommunications, IST

作者： Mojgan Hashemian Amin Nikoukaran Hadi Moradi Maryam S Mirian Mehdi Tehrani-doost Advanced Robotics and Intelligent Systems Lab University of Tehran Iran School of Electrical and Computer Engineering University of Tehran Iran Department of Psychiatry Tehran University of Medical Science Iran

The ability to determine mood is one of fundamental challenges in affective computing. In this paper, we present a novel approach for mood detection via emotional variations. In this approach, the mood is considered as a low magnitude and more stable, i.e. low frequency, emotion that can be detected using emotion detection approaches. A Bayes classification is applied on a feature vector composed of statistical aspects of the intensity of the emotions. The approach has been implemented in which two emotions, i.e. happiness and sadness, and also neutral state, have been targeted to determine the good, bad, and neutral, mood of subjects respectively. A Bayes classification is applied on a feature vector containing statistical aspects of the intensity of the emotions. The obtained Correct Classification Rate (CCR) is 91.1, with 0.09 mean error and variance of 4.9 discriminating good mood vs. neutral.

关键词： Mood Educational institutions Face Videos Computers Mice Accuracy

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Terrain identification on a one-legged hopping robot using high-resolution pressure images

Terrain identification on a one-legged hopping robot using h...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jacob J. Shill Emmanuel G. Collins Eric Coyle Jonathan Clark Department of Mechanical Engineering Center for Intelligent Systems Control. and Robotics (CISCOR) Tallahassee FL USA Department of Mechanical Engineering Embry-Riddle Aeron University Daytona Beach FL USA Department of Mechanical Engineering Scansorial and Terrestrial Robotics and Integrated Design Lab (STRIDe) Tallahassee FL USA

For efficient and safe locomotion the gaits of legged robots should vary with the type of terrain. Hence, terrain surface classification is an important problem for this class of mobile robots. Prior research has developed approaches to proprioceptive terrain classification for both wheeled and limbed robots that use sensor measurements dependent upon the dynamics of the robot, which ultimately requires the classification system to be trained at a large number of operating conditions (e.g., vehicle speeds and loads). This research develops an approach to terrain identification based on pressure images generated through direct surface contact using a robot skin constructed around a high-resolution pressure sensing array. Terrain signatures for classification are formulated from the magnitude frequency responses of the pressure images. The methodology is used to train and test a classifier using dynamically measured pressure images from a one-legged hopping robot. Experimental tests yield high classification accuracies, which are independent with respect to changing robot dynamics (i.e., different leg gaits). The findings of this paper suggest the methodology can be extended to autonomous field robots, providing the robot with crucial information about the environment that can be used to aid stability over rough terrains and enhance motion planning over varying terrains.

关键词： Robot sensing systems Skin Legged locomotion Vectors Foot Accuracy

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A blind user-centered navigation system with crowdsourced situation awareness

A blind user-centered navigation system with crowdsourced si...

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IEEE International Conference on Cyber Technology in Automation, Control, and intelligent systems

作者： Samleo L. Joseph Jizhong Xiao Bhupesh Chawda Kanika Narang Padmashri Janarthanam EE dept. Robotics and Intelligent Systems Lab N.Y. USA IBM - India Research Lab New Delhi India IT dept. R.M.D. Engineering College T.N. India

This article presents a novel approach of utilizing the Internet of things (IoT) to create situational awareness to the blind user. Our previous work uses wearable sensors in the physical world to estimate the user location based on metric and landmark localization. Currently, we augment our system with streaming data from the cyber world to provide situational awareness by summarizing the events around the user based on the proposed crowdsourced localization. Our localization algorithm quickly gauge the relevant aspects of an event and renders a positional-audio feedback in a virtual 3D space around the user. This enhances the user to actively participate in an interesting social event by navigating towards them or avoid any mishaps on their path. Our results shown that it is feasible to make a blind user to travel independently by integrating our real-time localization technologies with the fusion of wearable sensors and social sensors.

关键词： Real-time systems Navigation Measurement Three-dimensional displays Wearable sensors Twitter

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Triangular Geometry based Optimal Motion Planning using RRT*-Motion Planner

Triangular Geometry based Optimal Motion Planning using RRT*...

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International Workshop on Advanced Motion Control

作者： Ahmed Hussain Qureshi Saba Mumtaz Khawaja Fahad Iqbal Yasar Ayaz Mannan Saeed Muhammad Osman Hasan Whoi Yul Kim Moonsoo Ra Robotics And Intelligent Systems Engineering (RISE) Lab SMMENational University of Sciences And Technology. Islamabad Pakistan Department of Electronic Engineering College of Engineering Hanyang University Seoul South Korea School of Electrical Engineering And Computer Sciences (SEECS) National University of Sciences And Technology. Islamabad Pakistan

ISBN: (纸本)9781479957637

RRT* is a recent and improved variant of the RRT path finding algorithm. While RRT concentrates on simply finding an initial obstacle-free path, RRT* guarantees eventual convergence to an optimum, collision-free path for any given geometrical environment. On the other hand, the main limitations of RRT* include its slow processing rate and high memory utilization due to the large number of iterations required to achieve optimal path solution. This paper presents Triangular Geometerised-RRT* (TG-RRT*) which incorporates Triangular geometrical methods in the RRT* algorithm and improves its processing time by decreasing the number of iterations required for optimal solution. Simulation results under different environments demonstrate an improved convergence rate of TG-RRT*, in comparison with RRT*.

关键词： RRT Sampling based Optimal Motion Planning Directed Sampling

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