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This paper aims at the classification of hand gestures using electromyographic signals (EMG) obtained through a MyoTM armband, which has eight medical grade electrodes. Each electrode provides information regarding muscles contraction performed during the execution of the movement. From these electrodes signals are extracted seven features for each one of eight electrodes. After extraction of the...
Plant recognition from their leaves has become a popular area in the machine learning and image processing. In this study 7 different types of apricot trees were determined and classified by using their leaves. At first leaves images were pre-processed. After than each image was scanned by 5×5 overlapping filter and median values of each filter process were recorded to represent the leaves. After...
In this study, classification of Normal and Extra systolic heart sounds (HS) have been carried out using in PASCAL Heart Sounds (HS) data base. The extrasystole is the HS that is produced by performing an extra beat in each heart cycle, unlike the heartbeat normal cycle. It can be felt by people as palpitations. Occurrence of these sounds in certain age groups may be the indication of tachycardia...
Language or pattern recognition is an ever-growing field in research. The motivation behind this work is the growing importance of foreign languages in everyday life. It is specifically focused on groups who might have to face a foreign language somewhere and can't seem to understand it. This will also be beneficial for partially visually impaired persons. It will help in recognizing the alphabets...
Rapid disability patients increasing over time and need a solution in the future. Hand amputation is one form of disability that common in Indonesian society. A possible solution would be necessary at the moment is the development of prosthetic hand that has the ability as a human hand. The development of neuroscience has now reached the stage of the body's ability to use the signal as an input signal...
Electromyography (EMG) signal can be defined as a measure of electrical activity produced by skeletal muscles. It can be used in handling electronic devices or prosthesis. If we are able recognize the hand gesture captured using EMG signal with greater reliability and classification rate, it could serve a good purpose for handling the prosthesis and to provide the good quality of life to amputees...
This paper describes pattern recognition of electromyography (EMG) signal during load lifting using Artificial Neural Network (ANN). EMG is a method to measure and record the muscle activity when individuals perform certain operation and actions. This research will classify the EMG signal based on force apply to the arm due to the gravity act on it during load lifting. Recognizing pattern based on...
A study of Artificial Neural Networks (ANNs) in the elder falls detection problem is proposed. There are many efforts trying to provide an independent life for the elderly people. Fall event is one of the main problems that affect people in this age group. In order to provide a comfortable solution of this problem for elderly people, this paper presents an implementation of falls detection in mobile...
The proposed work presents the use of Artificial Neural Network (ANN) as a pattern classifier for differential protection of power transformer, which makes the discrimination among normal, magnetizing inrush, over-excitation and internal fault currents. This scheme has been realized through two separate customized Parallel-Hidden Layered ANN architectures which work in Master-slave mode. The Back...
The Electrocardiogram (ECG) is undoubtedly the most used biological signal in the clinical world and it is a means for detection of several cardiac abnormalities. Pattern recognition, diagnostic classification of ECGs constitutes an interesting application of Artificial Neural Networks (ANNs). This paper illustrates the ability of a feed-forward back propagation using Neural Network for classify unknown...
We have developed a portable electronic nose (E-nose) based on eight metal oxide gas sensors for classification and prediction of meat freshness. In this study, the E-nose was applied to predict chicken freshness during different storage days. Principal component analysis (PCA) and artificial neural network (ANN) were used to analyze the experiment data. The PCA method can classify the chicken freshness...
Artificial neural network was a information processing paradigm that took a model from the works of biological neural network in processing information hence it would have an ability which seems like human brain. Artificial neural network was able to solve some problems which contain uncertainty inside, which usually only human who could solve it. It was pattern recognition for example. The objective...
This paper makes an effort to study the causes and effects of permanent magnet demagnetization in permanent magnet machines and hence proposes an exclusive artificial neural network (ANN) based permanent magnet demagnetization detection scheme. A laboratory 2.8 kW line-start permanent magnet synchronous machine (LSPMSM) is used in the numerical investigations for initiating permanent magnet demagnetization...
Electronic nose (e-nose) is a machine used for sensing and recognizing odors by using chemical sensors. E-nose has wide fields of applications and it is used for sensing special odors. Also performance of e-nose depends on choosing correct sensor and choosing correct pattern recognition algorithm according to field of application and kinds of odors. In this study, different n-butanol concentrations...
This paper presents a novel approach to optimize pattern recognition system using genetic algorithm (GA) to identify the type of hand motion employing artificial neural networks (ANNs) with high performance and accuracy suited for practical implementations. To achieve this approach, electromyographic (EMG) signals were obtained from sixteen locations on the forearm of six subjects in ten hand motion...
The present work reports the use of Support Vector Machines (SVMs) as classifier of myoelectric signals. This tool was recently used to analyze data and recognize patterns, but just a few studies report its use in myoelectric registers. The aim of this research is analyze and compare some classification schemes employing Artificial Neural Networks and Linear Discriminant Analysis in order to establish...
The human hand is a complex system, with a large number of degrees of freedom (DoFs), sensors embedded in its structure, actuators and tendons, and a complex hierarchical control. Despite this complexity, the efforts required to the user to carry out the different movements are quite small. On the contrary, prosthetic hands are just a pale replication of the natural hand, with significantly reduced...
Breast cancer is the most frequent cancer and the most frequent cause of cancer induced death in women in the world. Diagnosis and prognosis of this cancer can be done through the radiological, surgical, and pathologic assessments of breast tissue samples. In developing countries, testing for detection of this cancer involves visual microscopic test of cytology samples such as Fine Needle Aspiration...
A brief and historical overview of research and development in the field of artificial neural network based electronic nose system is presented. Electronic-nose devices have received considerable attention in the field of sensor technology during the past twenty years, largely due to the discovery of numerous applications derived from research in diverse fields of applied sciences. Electronic/artificial...
The classification of the sound heart into different valve-physiological heart disease categories is a complex pattern recognition task. This paper will purpose sound heart recognition for diagnosing heart disease with 4 type of Artificial Neural Network (ANN). We develop a simple model for the recognition of heart sounds, and demonstrate its utility in identifying features useful in diagnosis. We...
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