| 1/2019 - 5 |
A Novel Approach for Activity Recognition with Down-Sampling 1D Local Binary Pattern FeaturesKUNCAN, F.   , KAYA, Y. , KUNCAN, M. |
Extra paper information in    |
| Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science |
Download PDF  (1,829 KB) | Citation | Downloads: 1,728 | Views: 3,750 |
Author keywords
digital signal processing, feature extraction, machine learning, pattern recognition, wearable sensors
References keywords
activity(24), recognition(20), human(20), learning(12), applications(11), sensors(10), classification(10), wearable(9), systems(9), machine(9)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2019-02-28
Volume 19, Issue 1, Year 2019, On page(s): 35 - 44
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.01005
Web of Science Accession Number: 000459986900005
SCOPUS ID: 85064195416
Abstract
The sensors on the mobile devices directly reflect the physical and demographic characteristics of the user. Sensor signals may contain information about the gender and movement of the person. Automatic recognition of physical activities often referred to as human activity recognition (HAR). In this study, a novel feature extraction approach for the HAR system using the mobile sensor signals, the Down Sampling One Dimensional Local Binary Pattern (DS-1D-LBP) method is proposed. Feature extraction from signals is one of the most critical stages of HAR because the success of the HAR system depends on the features extraction. The proposed HAR system consists of two stages. In the first stage, DS-1D-LBP conversion was applied to the sensor signals in order to extract statistical features from the newly formed signals. In the last stage, classification with Extreme Learning Machine (ELM) was performed using these features. The highest success rate was 96.87 percent in the experimental results according to the different parameters of DS-1D-LBP and ELM. As a result of this study, the novel approach demonstrated that the proposed model performed with a high success rate using mobile sensor signals for the HAR system. |
| References | | | Cited By |
Web of Science® Times Cited: 30 [View]
View record in Web of Science® [View]
View Related Records® [View]
Updated today
SCOPUS® Times Cited: 32
View record in SCOPUS® [Free preview]
View citations in SCOPUS® [Free preview]
Updated today
[1] Exploring Frontal Lobe Brain Activity and Cardiovascular Health Benefits of Reusi Dat Ton: A Neurophysiological and Cardiovascular Assessment, Tharawadeepimuk, Kittichai, Nanbancha, Ampika, Limroongreungrat, Weerawat, Leelawapa, Nuchanath, Wongsawat, Yodchanan, Sroykham, Watchara, IEEE Access, ISSN 2169-3536, Issue , 2024.
Digital Object Identifier: 10.1109/ACCESS.2024.3471642 [CrossRef]
[2] A novel sub-windowing local binary pattern approach for dorsal finger creases based biometric classification system, Riaz, Imran, Nazri Ali, Ahmad, Ibrahim, Haidi, Engineering Science and Technology, an International Journal, ISSN 2215-0986, Issue , 2024.
Digital Object Identifier: 10.1016/j.jestch.2024.101882 [CrossRef]
[3] Cryptographic Algorithm Designed by Extracting Brainwave Patterns, Dragu, Marius-Alin, Nicolae, Irina-Emilia, Frunzete, Mădălin-Corneliu, Mathematics, ISSN 2227-7390, Issue 13, Volume 12, 2024.
Digital Object Identifier: 10.3390/math12131971 [CrossRef]
[4] A gear fault diagnosis method based on improved accommodative random weighting algorithm and BB-1D-TP, Meng, Zong, Huo, Hanbing, Pan, Zuozhou, Cao, Lixiao, Li, Jimeng, Fan, Fengjie, Measurement, ISSN 0263-2241, Issue , 2022.
Digital Object Identifier: 10.1016/j.measurement.2022.111169 [CrossRef]
[5] Fractional Integration Based Feature Extractor for EMG Signals, SAÇU, İbrahim Ethem, Balkan Journal of Electrical and Computer Engineering, ISSN 2147-284X, Issue 2, Volume 10, 2022.
Digital Object Identifier: 10.17694/bajece.899088 [CrossRef]
[6] Human Activity Recognition from Accelerometry, Based on a Radius of Curvature Feature, Cavita-Huerta, Elizabeth, Reyes-Reyes, Juan, Romero-Ugalde, Héctor M., Osorio-Gordillo, Gloria L., Escobar-Jiménez, Ricardo F., Alvarado-Martínez, Victor M., Mathematical and Computational Applications, ISSN 2297-8747, Issue 5, Volume 29, 2024.
Digital Object Identifier: 10.3390/mca29050080 [CrossRef]
[7] A new feature extraction approach based on one dimensional gray level co-occurrence matrices for bearing fault classification, Kaya, Yılmaz, Kuncan, Melih, Kaplan, Kaplan, Minaz, Mehmet Recep, Ertunç, H.Metin, Journal of Experimental & Theoretical Artificial Intelligence, ISSN 0952-813X, Issue 1, Volume 33, 2021.
Digital Object Identifier: 10.1080/0952813X.2020.1735530 [CrossRef]
[8] An Effective Method for Detection of Demagnetization Fault in Axial Flux Coreless PMSG With Texture-Based Analysis, Minaz, Mehmet Recep, Akcan, Eyyup, IEEE Access, ISSN 2169-3536, Issue , 2021.
Digital Object Identifier: 10.1109/ACCESS.2021.3050418 [CrossRef]
[9] Synchronization of Measurement Data with the Reference System, Nalepa, B, Gwiazda, A, IOP Conference Series: Materials Science and Engineering, ISSN 1757-8981, Issue 1, Volume 1182, 2021.
Digital Object Identifier: 10.1088/1757-899X/1182/1/012052 [CrossRef]
[10] Brain tumor classification using modified local binary patterns (LBP) feature extraction methods, Kaplan, Kaplan, Kaya, Yılmaz, Kuncan, Melih, Ertunç, H. Metin, Medical Hypotheses, ISSN 0306-9877, Issue , 2020.
Digital Object Identifier: 10.1016/j.mehy.2020.109696 [CrossRef]
[11] An improved feature extraction method using texture analysis with LBP for bearing fault diagnosis, Kaplan, Kaplan, Kaya, Yılmaz, Kuncan, Melih, Mi̇naz, Mehmet Recep, Ertunç, H. Metin, Applied Soft Computing, ISSN 1568-4946, Issue , 2020.
Digital Object Identifier: 10.1016/j.asoc.2019.106019 [CrossRef]
[12] Yeraltı Metro Hatlarında Video Analiz Yöntemiyle Olay Algılama Kontrolünün Gerçekleştirilmesi, ÇEKEREK, Emre, KANDİLLİ, İsmet, KUNCAN, Melih, El-Cezeri Fen ve Mühendislik Dergisi, ISSN 2148-3736, 2020.
Digital Object Identifier: 10.31202/ecjse.727104 [CrossRef]
[13] A new approach for physical human activity recognition based on co-occurrence matrices, Kuncan, Fatma, Kaya, Yılmaz, Tekin, Ramazan, Kuncan, Melih, The Journal of Supercomputing, ISSN 0920-8542, Issue 1, Volume 78, 2022.
Digital Object Identifier: 10.1007/s11227-021-03921-2 [CrossRef]
[14] A New Ensemble Approach for Congestive Heart Failure and Arrhythmia Classification Using Shifted One-Dimensional Local Binary Patterns with Long Short-Term Memory, Çalışkan, Abidin, The Computer Journal, ISSN 0010-4620, Issue 9, Volume 65, 2022.
Digital Object Identifier: 10.1093/comjnl/bxac087 [CrossRef]
[15] Fault diagnosis of driving gear in rack and pinion drives based on multi-scale local binary pattern extraction and sparse representation, Yuan, Hang, Lei, Zhenxing, You, Xianglong, Dong, Zhe, Zhang, Huijuan, Zhang, Chi, Zhao, Yubin, Liu, Jianjuan, Measurement Science and Technology, ISSN 0957-0233, Issue 5, Volume 34, 2023.
Digital Object Identifier: 10.1088/1361-6501/acbab4 [CrossRef]
[16] Brain tumor classification: a novel approach integrating GLCM, LBP and composite features, Dheepak, G., J., Anita Christaline, Vaishali, D., Frontiers in Oncology, ISSN 2234-943X, Issue , 2024.
Digital Object Identifier: 10.3389/fonc.2023.1248452 [CrossRef]
[17] Multi-head CNN-based activity recognition and its application on chest-mounted sensor-belt, Verma, Updesh, Tyagi, Pratibha, Aneja, Manpreet Kaur, Engineering Research Express, ISSN 2631-8695, Issue 2, Volume 6, 2024.
Digital Object Identifier: 10.1088/2631-8695/ad43b9 [CrossRef]
[18] A novel feature extraction method for bearing fault classification with one dimensional ternary patterns, Kuncan, Melih, Kaplan, Kaplan, Mi̇naz, Mehmet Recep, Kaya, Yılmaz, Ertunç, H. Metin, ISA Transactions, ISSN 0019-0578, Issue , 2020.
Digital Object Identifier: 10.1016/j.isatra.2019.11.006 [CrossRef]
[19] A Template Matching Based Feature Extraction for Activity Recognition, Hameed Siddiqi, Muhammad, Alshammari, Helal, Ali, Amjad, Alruwaili, Madallah, Alhwaiti, Yousef, Alanazi, Saad, M. Kamruzzaman, M., Computers, Materials & Continua, ISSN 1546-2226, Issue 1, Volume 72, 2022.
Digital Object Identifier: 10.32604/cmc.2022.024760 [CrossRef]
[20] A new approach for physical human activity recognition from sensor signals based on motif patterns and long-short term memory, Kuncan, Fatma, Kaya, Yılmaz, Yiner, Züleyha, Kaya, Mahmut, Biomedical Signal Processing and Control, ISSN 1746-8094, Issue , 2022.
Digital Object Identifier: 10.1016/j.bspc.2022.103963 [CrossRef]
[21] Classification of bearing vibration speeds under 1D-LBP based on eight local directional filters, Kaya, Yılmaz, Kuncan, Melih, Kaplan, Kaplan, Minaz, Mehmet Recep, Ertunç, H. Metin, Soft Computing, ISSN 1432-7643, Issue 16, Volume 24, 2020.
Digital Object Identifier: 10.1007/s00500-019-04656-2 [CrossRef]
[22] A New Approach for Human Recognition Through Wearable Sensor Signals, Kılıç, Şafak, Kaya, Yılmaz, Askerbeyli, İman, Arabian Journal for Science and Engineering, ISSN 2193-567X, Issue 4, Volume 46, 2021.
Digital Object Identifier: 10.1007/s13369-021-05391-3 [CrossRef]
[23] A Gear Fault Diagnosis Method Based on Improved Accommodative Random Weighting Algorithm and Bb-1d-Tp, Meng, Zong, Huo, Hanbing, Pan, Zuozhou, Cao, Lixiao, Li, Jimeng, Fan, Fengjie, SSRN Electronic Journal, ISSN 1556-5068, 2022.
Digital Object Identifier: 10.2139/ssrn.4016182 [CrossRef]
[24] An effective method for detection of stator fault in PMSM with 1D-LBP, Mi̇naz, Mehmet Recep, ISA Transactions, ISSN 0019-0578, Issue , 2020.
Digital Object Identifier: 10.1016/j.isatra.2020.07.013 [CrossRef]
[25] Fault diagnosis of rolling bearing based on multiscale one-dimensional hybrid binary pattern, Cao, Susheng, Xu, Feiyu, Ma, Tianchi, Measurement, ISSN 0263-2241, Issue , 2021.
Digital Object Identifier: 10.1016/j.measurement.2021.109552 [CrossRef]
[26] An Intelligent Approach for Bearing Fault Diagnosis: Combination of 1D-LBP and GRA, Kuncan, Melih, IEEE Access, ISSN 2169-3536, Issue , 2020.
Digital Object Identifier: 10.1109/ACCESS.2020.3011980 [CrossRef]
[27] Turkish handwriting recognition system using multi-layer perceptron, Kuncan, Melih, Vardar, Enes, Kaplan, Kaplan, Ertunç, H. Metin, Journal of Mechatronics and Artificial Intelligence in Engineering, ISSN 2669-1116, Issue 2, Volume 1, 2020.
Digital Object Identifier: 10.21595/jmai.2020.21502 [CrossRef]
[28] Sports activity recognition with UWB and inertial sensors using deep learning approach, Pajak, Iwona, Krutz, Pascal, Patalas-Maliszewska, Justyna, Rehm, Matthias, Pajak, Grezgorz, Schlegel, Holger, Dix, Martin, 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), ISBN 978-1-6654-6710-0, 2022.
Digital Object Identifier: 10.1109/FUZZ-IEEE55066.2022.9882654 [CrossRef]
Updated today
Disclaimer: All information displayed above was retrieved by using remote connections to respective databases. For the best user experience, we update all data by using background processes, and use caches in order to reduce the load on the servers we retrieve the information from. As we have no control on the availability of the database servers and sometimes the Internet connectivity may be affected, we do not guarantee the information is correct or complete. For the most accurate data, please always consult the database sites directly. Some external links require authentication or an institutional subscription.
Web of Science® is a registered trademark of Clarivate Analytics, Scopus® is a registered trademark of Elsevier B.V., other product names, company names, brand names, trademarks and logos are the property of their respective owners.
Copyright ©2001-2024
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
