2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)最新文献

{"title":"Determining Acceptable Range of Surface Electromyogram Electrode Placement Variation for Deltoid Muscle Using Euclidean Distance Function","authors":"Mohd Saiful Hazam Majid, W. Khairunizam, B. N. Sahyudi, I. Zunaidi, A. Shahriman, M. Zuradzman","doi":"10.1109/ICASSDA.2018.8477631","DOIUrl":"https://doi.org/10.1109/ICASSDA.2018.8477631","url":null,"abstract":"Right electrode placement is very crucial in studying surface Electromyogram (sEMG) signal from any human muscle. The guidelines for electrodes placement as well as skin preparation has been specified by Surface Electromyography for the Noninvasive Assessment of Muscles (SENIAM) project that can be used by sEMG researcher to perform suitable sEMG electrode placement in their experiment setup. According to previous researchers the best position to place electrodes for specified muscle is at the muscle belly. However there is no special instrument to measure or identify the exact location of the muscle belly. The uncertainty of exact location for electrodes placement could be a problem if a signal is expected to be recorded and studied from the same muscle for certain period of time or days where electrodes need to be attach and reattach, since it would record different sEMG values even though subject perform similar muscle contraction. Thus to overcome this problem we set up a range of location where sEMG electrodes could be placed to get right EMG recording from the same muscle. We tested on deltoid lateral muscle, and as result sEMG data that were recorded by the electrodes that we placed 1cm apart from its initial position will still be at least 90% similar to reference data. The comparison between tested sEMG data and reference sEMG deltoid data were accomplished by using Euclidean Distance function.","PeriodicalId":185167,"journal":{"name":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129213867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Objective Evaluation of Freezing of Gait in Patients with Parkinson's Disease through Machine Learning Approaches","authors":"Q. W. Oung, S. Basah, H. Muthusamy, V. Vijean, H. Lee, W. Khairunizam, S. A. Bakar, Z. Razlan, Zunaidi Ibrahim","doi":"10.1109/ICASSDA.2018.8477606","DOIUrl":"https://doi.org/10.1109/ICASSDA.2018.8477606","url":null,"abstract":"Freezing of gait (FoG) is a general and disabling indicator during the severe level of Parkinson's disease (PD) that affects millions of PD patients worldwide. Under episodic condition that cannot be predicted, FoG influences gait in term of delay and sudden inability to perform walking. FoG does not respond well to treatment through medication; therefore effective non-medication assistance is necessary. A wearable assistance system for FoG detection has been developed to assist patients in order to proceed walking. However, current objective evaluations for automated FoG detection are not sufficient as only the standard time-based and frequency-based features were extracted and there are still spaces for improvement in term of FoG detection performance. In this paper, we first attempt to adapt and extend current robust feature extraction and inference techniques in order to include additional features compared to the currently existing features. Then we go a step further by applying feature selection with the purpose of obtaining the maximum recognition results using the current available DAPHNet dataset. This dataset was collected using a wearable health assistive system that consists of 3-axes accelerometer to measure patient's movement. Ten PD patients were chosen to perform several walking tasks under laboratory environment. The overall performance was evaluated via subject-dependent and subject independent using the proposed feature extraction, feature selection and classification algorithms. The outcomes showed that the suggested machine learning methods had the ability in detecting FoG with maximum mean accuracy, sensitivity, specificity and area under curve (AUC) of approximately 99%.","PeriodicalId":185167,"journal":{"name":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117112948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Big Data Applications in Electric Energy Systems","authors":"Nazreen Junaidi, M. Shaaban","doi":"10.1109/ICASSDA.2018.8477607","DOIUrl":"https://doi.org/10.1109/ICASSDA.2018.8477607","url":null,"abstract":"Data-driven management of electric energy systems could provide major returns to system operation and control. This paper explores the potential applications of big data analytics in electricity grids. The primary sources of data in electric utilities are first outlined. These include phasor measurement units (PMUs), smart meters, intelligent electronic devices (IEDs), weather data, geographic information system (GIS), and electricity market data. Potential applications, relating to fault analysis, state estimation, security assessment, variable renewable energy, and power market operation are further described.","PeriodicalId":185167,"journal":{"name":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123424896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling of Crutch Walk Training System with Falling Sensation Device","authors":"Rio Sugiyama, N. Tsuda, N. Kato, Y. Nomura","doi":"10.1109/ICASSDA.2018.8477623","DOIUrl":"https://doi.org/10.1109/ICASSDA.2018.8477623","url":null,"abstract":"A crutch is used by a patient who cannot put weight on the lower limb due to a sudden injury. In this research, a training device for the crutch walk was proposed. A falling sensation device (FSD) was modeled for the crutch walk training. By using this device, an untrained patient would be able to get used to walk properly with crutches. In this paper, firstly, the equations of motion of the crutch and the proposed FSD were derived by the Lagrange method. Secondly, the applicability of the derived equations of motion was confirmed through experiments. Finally, the motions of the crutch were simulated and the effects of FSD were confirmed.","PeriodicalId":185167,"journal":{"name":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123524073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Webcam Based Lux Meter Using Grid-Based Image Processing","authors":"M.A. Yusuf, M. S. Azmi, A. H. Ismail, I. I. Ibrahim, M. Hashim, N. S. Kamarrudin","doi":"10.1109/ICASSDA.2018.8477632","DOIUrl":"https://doi.org/10.1109/ICASSDA.2018.8477632","url":null,"abstract":"The need for constant lighting monitoring especially in the high-risk areas are in significant demand due to the lighting inefficiency. However, the use of conventional handheld lux meter does not suffice the requirements of lighting monitoring since the measured lux cannot be fed into the lighting control system for automation process. Hence, the paper proposes an image processing-based technique by correlating the brightness level of image with the actual lux value. The image is divided into four main grids, and the correlation is made prior to four light sources, respectively.","PeriodicalId":185167,"journal":{"name":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121993740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Upper Limb Muscle Strength Analysis For Movement Sequence Based on Maximum Voluntary Contraction Using EMG Signal","authors":"B. N. Cahyadi, I. Zunaidi, S. A. Bakar, W. Khairunizam, S. Majid, Z. Razlan, M. Muhammad, M. Rudzuan, W. Mustafa","doi":"10.1109/ICASSDA.2018.8477638","DOIUrl":"https://doi.org/10.1109/ICASSDA.2018.8477638","url":null,"abstract":"This paper presents the studies of analysis upper limb muscle strength during arm movement sequence for the purpose of upper limb rehabilitation after stroke. The recovery of the arm could be optimized if the rehabilitation therapy is in a right manner. Upper limb weakness after stroke is prevalent in rehabilitation, many factors that can deficit muscle strength there are neural, muscle structure and function change after stroke. Maximum Voluntary Contraction (MVC) is one of the methods to rescale per cent of a reference value unique and standardized for all subjects within a study, This allows to compare of electromyography signal findings between subjects directly and quantitative. The objective of this research to evaluate muscle strength fatigue for movement sequence rehabilitation after stroke. 5 healthy subjects including both male and female performed a functional movement and a fundamental movement. Electromyography device is used to measure and record movement arm involving deltoid, biceps and flexor carpum ulnaris (FCU). A signal processing technique is employed to analyze the upper limb movement signals and several movement features are determined, which is the root mean square (RMS) and mean absolute value (MAV). By referring to the information from the previous research frequency domain (FD) feature is usually used in the assessing muscle strength fatigue. The experiment results show that for the highest value of movement sequence contraction based of MVC for deltoid muscle is 96% (RMS) and 93% (MAV) by subject #1 and the highest value for biceps is 90% (RMS) and 93% (MAV) by subject #4. The highest value for FCU muscle is 78% (RMS) and 82% (MAV) by subject #5. And the highest power contraction for movement sequence based MVC is deltoid muscle with 88% (RMS) and 90% (MAV) and the lowest power contraction for movement sequence based MVC is 49% (RMS) and 58% (MAV). The benefit of maximum voluntary contraction (MVC) is important to rescaling to a per cent of a reference value unique and standardized for all subjects. Maximum voluntary contraction is important because it can be used to rescaling value of EMG signal, to be a reference value for analysis and investigation of muscle contraction and can be used to classification subject or patient based muscle contraction. Differences in muscle strength each human are caused by several factors including age, muscle sizes, muscle conditions and body conditions.","PeriodicalId":185167,"journal":{"name":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122637753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Background Color on Rice Seed Image Segmentation Using Machine Vision","authors":"R. Ruslan, M. Ibrahim, S. Khairunniza-Bejo, A. Aznan, I. H. Rukunudin, F. A. Azizan","doi":"10.1109/ICASSDA.2018.8477614","DOIUrl":"https://doi.org/10.1109/ICASSDA.2018.8477614","url":null,"abstract":"One of the crucial part in the development of machine vision for rice seed identification are the design of the seed holder itself. In this project, seed holder was designed to hold rice seed for image acquisition purposes. Four different colors such as black, blue, green and red was painted on the seed holder. Effect of background colors on rice seeds image segmentation were tested under machine vision setup. Simple rice seed parameters such as seed length and width were measured using image processing technique programmed in LabVIEW software. Percentage error for each background color was calculated based on the actual legth and width of the rice seed. Blue background color was found to provide good contrast for estimation of length and width with accuracy less than 2% and 5%, respectively.","PeriodicalId":185167,"journal":{"name":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123273016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human 3D Reconstruction and Identification Using Kinect Sensor","authors":"Chai Joon Lip, A. S. Ali Yeon, L. Kamarudin, K. Kamarudin, R. Visvanathan, Ahmad Firdaus Ahmad Zaidi, S. M. Mamduh, A. Zakaria, W. M. Nooriman","doi":"10.1109/ICASSDA.2018.8477609","DOIUrl":"https://doi.org/10.1109/ICASSDA.2018.8477609","url":null,"abstract":"3D model of human body has been widely used in many applications including medical, health and security, since it is able to provide information on human body shape. This paper proposes a method to identify human based on the 3D model of the body and the depth data form the Kinect. The system firstly utilizes the coordinate points from the 3D model to calculate the selected anthropometry features of human body. Then, the features are compared with real time Kinect's depth acquisition to perform pose recognition and human identification. Eight candidates were involved in the reliability test of the system with each of them performed 6 trials, making a total of 48 trials. The overall reliability of the system in identifying the correct candidate was found to be 79.167%.","PeriodicalId":185167,"journal":{"name":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","volume":"86 20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126288040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Swarm Rules for Autonomous Vehicles in a Parking Lot","authors":"Y. Tabata, H. Matsui, N. Kato","doi":"10.1109/ICASSDA.2018.8477630","DOIUrl":"https://doi.org/10.1109/ICASSDA.2018.8477630","url":null,"abstract":"In this research, we aim at acquiring the moving behavior of each vehicle in a parking lot only for entering vehicles. The behaviors of each vehicle are desired based on the neighborhood environment of the vehicle, and they are not desired based on the whole environment in the parking lot with depending on the other vehicles' decision. Therefore, this research is a kind of studies about swarm robots. In this paper, vehicles are modeled in the parking lot for simulation. We confirm that the vehicle can reach the exit in the parking lot in simulation.","PeriodicalId":185167,"journal":{"name":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","volume":"340 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124309885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two Proposed Indoor Multi-Cameras Positioning Systems Compared to Classical Geometry System","authors":"Adnan Saood, N. Salman, Ali Alreyahi, I. Hatem","doi":"10.1109/ICASSDA.2018.8477636","DOIUrl":"https://doi.org/10.1109/ICASSDA.2018.8477636","url":null,"abstract":"Positioning systems in indoor environments are of a great concern in automation and robotics domains where performing critical tasks requires precision. However, to make these systems widely applicable they must be cost-effective. The objective of this paper is to develop two different 3D positioning systems based on neural networks and adaptive neuro-fuzzy techniques. Sample images of a recognizable object were taken using three low-cost cameras as training and testing data for these systems. Positioning results of the proposed systems are compared with results of the classical geometrical method. The results show positioning errors on the scale of millimeters and the neural network system produces the smallest error.","PeriodicalId":185167,"journal":{"name":"2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114309719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}