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A Prosthesis Control System Based on the Combination of Speech and sEMG Signals and Its Performance Assessment

A Prosthesis Control System Based on the Combination of Spee...

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3rd international conference on Health Information Science (HIS)

作者： Wei, Zheng Fang, Peng Tian, Lan Zhuo, Qifang Li, Guanglin Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China

ISBN: (纸本)9783319062693;9783319062686

Surface electromyographic (sEMG) signals from the residual limb muscles after amputation have been widely used for prosthesis control. However, for the amputees with high-level amputations, there usually exists a dilemma that the sEMG signal sources for prosthesis control are limited but more limb motions need to be recovered, which strongly limits the practicality of the current myoelectric prostheses. In order to operate prostheses with multiple degrees of freedom (DOF) of movements, several control protocols have been suggested in some previous studies to deal with this dilemma. In this paper, a prosthesis control system based on the combination of speech and sEMG signals (Strategy 1) was built up in laboratory conditions, where speech commands were applied for the prosthesis joint-mode switching and sEMG signals were applied to determine the motion-class and execute the target movement. The control performance of the developed system was evaluated and compared with that of the traditional control strategy based on the pattern recognition of sEMG signals (Strategy 2). The experimental results showed that the difference between Strategy 1 and Strategy 2 was insignificant for the control of a 2-DOF prosthesis, but Strategy 1 was much better in the control of a prosthesis with more DOFs in comparison to Strategy 2. In addition, the positive user experience also demonstrated the reliability and practicality of Strategy 1.

关键词： sEMG Speech Prosthesis control pattern recognition Limb Amputee

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Monitoring moods in elderly people through voice processing

Monitoring moods in elderly people through voice processing

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6th international Work-conference on Ambient Assisted Living, IWAAL 2014

作者： Rojas, Víctor Ochoa, Sergio F. Hervás, Ramón Computer Science Department Universidad de Chile Av. Blanco Encalada 2120 3rd Floor Santiago Chile Castilla-La Mancha University Ciudad Real Spain

ISBN: (纸本)9783319131047

Depression is a mental illness that is difficult to diagnose and treat. This mental disorder affects many older adults due several reasons, for instance because of their physical limitations and the natural reduction of their social circle. This article presents a system for monitoring the mood of the elderly through voice processing. The system is particularly focused on detecting sadness, which allows caregivers of family members to react on-time in supporting the person in need. The sadness recognition is done by classifying emotions in groups, according to the Circumflex Model of Affect. After evaluating the system using several emotion databases, the obtained results indicate that this solution is able to recognize 94% of the cases in men and 79% in women. This solution can be embedded in ubiquitous systems that monitor the mood of people in several scenarios. © Springer international Publishing Switzerland 2014.

关键词： Emotion recognition

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3rd international conference on Information Technology and Management Innovation, ICITMI 2014

3rd International Conference on Information Technology and M...

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3rd international conference on Information Technology and Management Innovation, ICITMI 2014

ISBN: (纸本)9783038352396

The proceedings contain 294 papers. The special focus in this conference is on Information Technology and Management Innovation. The topics include: A composite model via proportional intensity function and additive hazard function;a research using correlation coefficient to make Bayesian classification data mining;grey target decision model of hesitant three-parameter interval grey number;trust calculation model in knowledge community;one fault diagnosis method based on fuzzy equal relationship and rough set theory;cloud computing application pattern library;the design and implementation of cloud computing model and platform;research of crop production system based on the CPS framework;application of data mining in sports in the consumer market segmentation;the design for zero emission greenhouse system;body recognition based on depth image;online tracking via stabilizer and attractor;a framework for stream data mining over wireless sensor network;design of a pipeline leak detection system;methods of path identification and processing in freescale intelligence car;design and implementation of an intelligent home control system;the design and analysis of control system applied in artificial grass tufting machine;the vector control system of induction motor based on fuzzy control;intelligent track guide control for hearth negative pressure;a polarization stabilization control system based on DSP;design of communication for commodity trading system;a well modularized computer network architecture;security protection and solving procedures of university network;design and implement of commodity client electronic trading system;predicting the shelf-life of single base propellants and the application of multimedia technology in mathematics teaching.

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Approaches in pattern recognition and classification based on coin images

Approaches in pattern recognition and classification based o...

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3rd international conference on Manufacturing Engineering and Process, ICMEP 2014

作者： Wong, Chee Kong bin Mohd. Shukran, Mohd. Afizi Lee, Fong Yee SEGi University No. 9 JalanTeknologi Taman Sains Selangor PJU 5 Kota Damansara 47810 Petaling Jaya Selangor Malaysia Universiti PertahananNasionalMalaysia Kem Sungai Besi 57000 Kuala Lumpur Malaysia

ISBN: (纸本)9783038350842

This paper discusses the various texture-based and vector-based approaches to classify *** two types of approaches are common for software-based coin sorting systems. Many researchers have applied algorithms known in artificial intelligence research for feature extraction, selection and classification of coin images. However, without a common benchmark, it is difficult to assess the accuracy, robustness and efficiency of the coin sorting systems across the different approaches. It is proposed that the use of a standard benchmark image databank such as the CIS Benchmark will allow a more objective and accurate comparison of the performance of these coin classification approaches. © (2014) Trans Tech Publications, Switzerland.

关键词： Image classification

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An Integrated Approach to Content Based Image Retrieval 3

An Integrated Approach to Content Based Image Retrieval

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3rd international conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Choudhary, Roshi Raina, Nikita Chaudhary, Neeshu Chauhan, Rashmi Goudar, R. H. Graph Era Univ Dehra Dun 248001 India

ISBN: (纸本)9781479930807

Content based image retrieval, in the last few years has received a wide attention. Content Based Image Retrieval (CBIR) basically is a technique to perform retrieval of the images from a large database which are similar to image given as query. CBIR is closer to human semantics, in the context of image retrieval process. CBIR technique has its application in different domains such as crime prevention, medical images, weather forecasting, surveillance, historical research and remote sensing. Here content refers to the visual information of images such as texture, shape and color. Contents of image are richer in information for an efficient retrieval in comparison to text based image retrieval. In this paper, we have pro posed a content based image retrieval integrated technique which extracts both the color and texture feature. To extract the color feature, color moment (CM) is used on color images and to extract the texture feature, local binary pattern (LBP) is performed on the grayscale image. Then both color and texture feature of image are combined to form a single feature vector. In the end similarity matching is performed by Euclidian distance which compares feature vector of database images with query images. LBP mainly used for face recognition. But we are going to use LBP for natural images. This combined approach provides accurate, efficient, less complex retrieval system.

关键词： Content based image retrieval (CBIR) Local Binary pattern (LBP) Color moment (CM) Euclidian Distance

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Fault diagnosis method for the train axle box bearing based on KPCA and GA-SVM

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3rd international conference on Machinery Electronics and Control Engineering (ICMECE 2013)

作者： Wang, Ci Jia, Limin Li, Xiaofeng Beijng Jiaotong Univ Sch Traff & Transportat 3 Shangyuan Cun Beijing 100044 Peoples R China Beijng Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China

ISBN: (纸本)9783037859032

Online fault diagnosis for the train axle box bearings is a wide and important study topic since it plays a critical role in train safety. Due to the vibration signals' nonlinear and non-stationary characteristics, accuracies of the methods such as neural network and hierarchical clustering are less than 90% which are not satisfying. In this paper, kernel principal component analysis (KPCA), a nonlinear process technique, was to tackle each signal's 18 feature parameters for extracting the main features to reflect the signal characteristics. Then, in fault pattern recognition, support vector machine (SVM) based on genetic algorithm (GA) was used to identify the current fault type of the bearings, including normal, outer ring fault, inner ring fault and rolling element fault. The results show that the prediction accuracy of GA-SVM method reaches to 96.33%, which is quite effective.

关键词： fault diagnosis axle box bearings KPCA SVM GA feature parameters

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Pectoral muscle detection in digital breast tomosynthesis and mammography

Pectoral muscle detection in digital breast tomosynthesis an...

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3rd international MICCAI Workshop on Medical Computer Vision, MCV 2013

作者： Ghesu, Florin C. Wels, Michael Jerebko, Anna Sühling, Michael Hornegger, Joachim Kelm, B. Michael Siemens Corporate Technology Imaging and Computer Vision Erlangen Germany Pattern Recognition Department Friedrich Alexander University Erlangen Germany Siemens AG Healthcare Erlangen Germany

ISBN: (纸本)9783319055299

Screening and diagnosis of breast cancer with Digital Breast Tomosynthesis (DBT) and Mammography are increasingly supported by algorithms for automatic post-processing. The pectoral muscle, which dorsally delineates the breast tissue towards the chest wall, is an important anatomical structure for navigation. Along with the nipple and the skin, the pectoral muscle boundary is often used for reporting the location of breast lesions. It is visible in mediolateral oblique (MLO) views where it is well approximated by a straight line. Here, we propose two machine learning-based algorithms to robustly detect the pectoral muscle in MLO views from DBT and mammography. Embedded into the Marginal Space Learning framework, the algorithms involve the evaluation of multiple candidate boundaries in a hierarchical manner. To this end, we propose a novel method for candidate generation using a Hough-based approach. Experiments were performed on a set of 100 DBT volumes and 95 mammograms from different clinical cases. Our novel combined approach achieves competitive accuracy and robustness. In particular, for the DBT data, we achieve significantly lower deviation angle error and mean distance error than the standard approach. The proposed algorithms run within a few seconds. © 2014 Springer international Publishing Switzerland.

关键词： Learning algorithms

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Research on Xilamuren Desert-steppe Rainfall Experiment Segmentation Regular pattern - Based on Rainfall Simulation Experiment

Research on Xilamuren Desert-steppe Rainfall Experiment Segm...

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3rd international conference on Material Engineering, Chemistry, bioinformatics (MECB 2013)

作者： Zhang, Min Zhang, Rui-qiang Qi, Te Xie, Yun-hu Cheng, Congcong Hai, Chun-xing Inner Mongolia Normal Univ Coll Geog Sci Hohhot 010022 Peoples R China Inner Mongolia Normal Univ Coll Econ & Management Hohhot 010022 Peoples R China Inst Water Resources Pastoral Area Hohhot 010022 Peoples R China

ISBN: (纸本)9783037859148

The rainfall is the main soil water supply to the soil of desert-steppe. It divides into three parts, evaporation, infiltration and runoff, after falling on to the surface. Those three parts are affected by many factors. Studies of rainfall division in desert-steppe were rare, the proportions of evaporation, infiltration and runoff are uncertain. So Under the condition of different vegetation, we conduct six times rainfall simulation experiment under different rainfall intensity. Simulation shows that rainfall process, the surface coverage and soil condition affect division. The evaporation section of rainfall accounted for 1/2 similar to 2/3. Infiltration section accounted for 30% similar to 50%. Runoff is the smallest. The rainfall intensity plays a decisive role on the runoff. Different vegetation coverage, division proportion is different. The interception and delay function of vegetation main effect evaporation and runoff, it can make the evaporation increased to more than 70%, reduce runoff to a third. Water content of soil profile before rainfall is the main factors affecting infiltration volume. The soil moisture before rain affects the infiltration rate at the beginning of rainfall. If rainfall duration is long enough, infiltration capacity is almost a constant.

关键词： Desert-steppe division of rainfall infiltration runoff evaporation

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Fundamental Study for Verbalization of Embodied Expertise based on pattern recognition

Fundamental Study for Verbalization of Embodied Expertise ba...

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IIAI international conference on Advanced Applied Informatics (IIAIAAI)

作者： Hiroki Hojo Nozomi Nomachi Yutaro Tomoto Tsuyoshi Nakamura Masayoshi Kanoh Koji Yamada Nagoya Institute of Technology Nagoya Aichi Japan Chukyo University Nagoya Aichi Japan Institute of Advanced Media Arts and Sciences Ogaki Gifu Japan

Embodied expertise, which expresses skills of experts, is a kind of tacit knowledge that is difficult to transfer from one person to another by writing it down or verbalizing it. The aim of our study is to translate embodied expertise into explicit knowledge, i.e. onomatopoeias. We call the onomatopoeias "embodied expertise onomatopoeias", which can enable people to understand the skills intuitively and easily. Acquiring embodied expertise onomatopoeias is considered as a problem of pattern recognition. Our study focused on the skills of Japanese penmanship, Pen Shodo, which is Japanese calligraphy using a pen, to translate tacit knowledge into onomatopoeias and investigated the possibility of constructing a training system for these skills.

关键词： Writing Intelligent systems Electronic mail pattern recognition Sports equipment Training

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A Time Effective Approach for Vector Similarity Measurement Based on Vector Addition

A Time Effective Approach for Vector Similarity Measurement ...

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3rd international conference on Civil and Architecture Engineering (ICCAE’2014);3rd international conference on Automation, Robotics and Mechanical Engineering (ICAMR’2014);3rd international conference on Machine Learning and Computer Science (IMLCS’2014);3rd international conference on Management, Humanity and Economics (ICMHE’2014);3rd international conference on Power, Control and VLSI Engineering (ICPCVE’2014)

作者： Wasiq Khan Ping Jiang Mohammed Bilal Speech Signal Processing University of Bradford Department of computer science intelligent systemsUniversity of HullUnited Kingdom Data Mining University of LeedsUnited Kingdom

pattern matching is one of the principal methodologies in speech signal processing and isolated word recognition. There are a number of similarity measures to find the similarity between the target words in an acquired speech by matching with template. The retrieved similarity result is dependent both on the feature vectors extraction technique and the distance metric produced by similarity measure. Short Time Fourier Transform is used for spectrogram re- trieval which is used for performance comparison of different simi- larity measures. In this paper, a novel similarity measure is proposed which is based on vector addition. It outperforms in terms of execu- tion time as compared to other similarity measures. We have done a detailed study of the performance of different similarity measurement techniques for a number of spectrograms on a large database of speech recordings. Manhattan distance, Euclidean distance, vector cosine angle distance, Bhattacharyya coefficients and posterior prob- ability measure are used for the performance comparison. The results show that this similarity measure outperforms as compare to all above similarity measures in terms of time complexity and similarity performance.

关键词： Signal Processing Speech recognition pattern Matching PPM Word Identification.

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