Implementasi Metode Support Vector Machine Pada Sistem Monitoring Kelelahan Otot Berdasarkan Fitur Root Mean Square
Kata Kunci:
Kelelahan otot, Support Vector Machine, Root Mean Square, Electromyography, Biceps brachiiAbstrak
Naskah ini akan diterbitkan di SIET 2024
Referensi
Ayaz, M., Ayub, M.A., Qureshi, I.A. (2020). Arduino Based Fatigue Level Measurement in Muscular Activity using RMS Technique. The 8th IEEE International Conference on E-Health and Bioengineering - EHB 2020.
Bawa, A. & Banitsas, K. (2022). Design Validation of a Low-Cost EMG Sensor Compared to a Commercial-Based System for Measuring Muscle Activity and Fatigue. Sensors 2022, 22(5799), pp. 1-14.
Daffa, A.Z., Widasari, E.R., Syauqy, D. (2023). Analisis Perbandingan Metode Ekstraksi Fitur Mean Absolute Value, Root Mean Square, dan Variance untuk Deteksi Kelelahan Otot Biceps Brachii. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 7(7), pp. 3434-3440.
Ebied, A., et al. 2020. Upper Limb Muscle Fatigue Analysis Using Multi-channel Surface EMG. Proceedings of NILES2020: 2nd Novel Intelligent and Leading Emerging Sciences Conference.
Farago, E., et al. (2019). Development of an EMG-Based Muscle Health Model for Elbow Trauma Patients. Sensors 2019, 19(3309), pp. 1-15.
Girhepunje, A., et al. (2020). Automated Muscle Fatigue Diagnosis using EMG Signal. International Journal of Scientific Research in Science and Technology, 5(7), pp. 677-681.
Kundu, B. (2021). Classification and Feature Extraction of Different Hand Movements from the EMG Signal using Machine Leaning based Algorithms. A thesis.
Myoware. (2022). Advanced Guide. URL: https://myoware.com/learn/tutorials-guides/. Diakses pada 11 Juli 2024.
Raharjo, A.B., Fatkhurrozi, B., Nawawi, I. (2020). ANALISIS SINYAL ELECTROMYOGRAPHY (EMG) PADA OTOT BICEPS BRACHII UNTUK MENDETEKSI KELELAHAN OTOT DENGAN METODE MEDIAN FREKUENSI. THETA OMEGA: JOURNAL OF ELECTRICAL ENGINEERING, COMPUTER AND INFORMATION TECHNOLOGY, 1(1).
Sulistyawati, I.N., (2019). RANCANG BANGUN ELEKTROMIOGRAF (EMG) BERBASIS MIKROKONTROLER UNTUK MENDETEKSI CEDERA OTOT PADA PERGELANGAN KAKI (ANKLE). Jurnal Teknik Elektro, 8(3), pp. 557-562.
Szewczyk, B., et al. (2022). Anatomical variations of the biceps brachii insertion: a proposal for a new classification. Folia Morphol, 82(2), pp. 359-367.
Tiwana, M.S., Charlick, M., Varacallo, M. (2024). Anatomy, Shoulder and Upper Limb, Biceps Muscle. [Updated 2024 Jan 30]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK519538/
Wang, S., et al. (2023). A Novel Approach to Detecting Muscle Fatigue Based on sEMG by Using Neural Architecture Search Framework. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 34(8), pp. 4932-4943.
Wang, X., et al. (2021). Muscle Fatigue Classification and The Effect of Electrical Stimulation on Muscle Fatigue Recovery. Journal of Physics: Conference Series 1924, pp. 1-8.
Widasari, E.R., et al. A Wireless Surface Electromyogram Monitoring System Using Smartphone and Its Application to Maintain Biceps Muscle. 2015 IEEE International Conference on Systems, Man, and Cybernetics, Hong Kong, China, 2015, pp. 2378-2383.
Yuliansyah, D. (2017). DETEKSI KELELAHAN OTOT MENGGUNAKAN SINYAL EMG DAN DETEKTOR GAYA PADA GERAK EKSTENSI DAN FLEKSI KNEE-JOINT UNTUK EVALUASI PENGGUNAAN FUNCTIONAL ELECTRICAL STIMULATION PADA SISTEM REHABILITASI LOWER LIMB. Undergraduate Thesis, Institut Teknologi Sepuluh November.
Ayaz, M., Ayub, M.A., Qureshi, I.A. (2020). Arduino Based Fatigue Level Measurement in Muscular Activity using RMS Technique. The 8th IEEE International Conference on E-Health and Bioengineering - EHB 2020.
Bawa, A. & Banitsas, K. (2022). Design Validation of a Low-Cost EMG Sensor Compared to a Commercial-Based System for Measuring Muscle Activity and Fatigue. Sensors 2022, 22(5799), pp. 1-14.
Daffa, A.Z., Widasari, E.R., Syauqy, D. (2023). Analisis Perbandingan Metode Ekstraksi Fitur Mean Absolute Value, Root Mean Square, dan Variance untuk Deteksi Kelelahan Otot Biceps Brachii. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 7(7), pp. 3434-3440.
Ebied, A., et al. 2020. Upper Limb Muscle Fatigue Analysis Using Multi-channel Surface EMG. Proceedings of NILES2020: 2nd Novel Intelligent and Leading Emerging Sciences Conference.
Farago, E., et al. (2019). Development of an EMG-Based Muscle Health Model for Elbow Trauma Patients. Sensors 2019, 19(3309), pp. 1-15.
Girhepunje, A., et al. (2020). Automated Muscle Fatigue Diagnosis using EMG Signal. International Journal of Scientific Research in Science and Technology, 5(7), pp. 677-681.
Kundu, B. (2021). Classification and Feature Extraction of Different Hand Movements from the EMG Signal using Machine Leaning based Algorithms. A thesis.
Myoware. (2022). Advanced Guide. URL: https://myoware.com/learn/tutorials-guides/. Diakses pada 11 Juli 2024.
Raharjo, A.B., Fatkhurrozi, B., Nawawi, I. (2020). ANALISIS SINYAL ELECTROMYOGRAPHY (EMG) PADA OTOT BICEPS BRACHII UNTUK MENDETEKSI KELELAHAN OTOT DENGAN METODE MEDIAN FREKUENSI. THETA OMEGA: JOURNAL OF ELECTRICAL ENGINEERING, COMPUTER AND INFORMATION TECHNOLOGY, 1(1).
Sulistyawati, I.N., (2019). RANCANG BANGUN ELEKTROMIOGRAF (EMG) BERBASIS MIKROKONTROLER UNTUK MENDETEKSI CEDERA OTOT PADA PERGELANGAN KAKI (ANKLE). Jurnal Teknik Elektro, 8(3), pp. 557-562.
Szewczyk, B., et al. (2022). Anatomical variations of the biceps brachii insertion: a proposal for a new classification. Folia Morphol, 82(2), pp. 359-367.
Tiwana, M.S., Charlick, M., Varacallo, M. (2024). Anatomy, Shoulder and Upper Limb, Biceps Muscle. [Updated 2024 Jan 30]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK519538/
Wang, S., et al. (2023). A Novel Approach to Detecting Muscle Fatigue Based on sEMG by Using Neural Architecture Search Framework. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 34(8), pp. 4932-4943.
Wang, X., et al. (2021). Muscle Fatigue Classification and The Effect of Electrical Stimulation on Muscle Fatigue Recovery. Journal of Physics: Conference Series 1924, pp. 1-8.
Widasari, E.R., et al. A Wireless Surface Electromyogram Monitoring System Using Smartphone and Its Application to Maintain Biceps Muscle. 2015 IEEE International Conference on Systems, Man, and Cybernetics, Hong Kong, China, 2015, pp. 2378-2383.
Yuliansyah, D. (2017). DETEKSI KELELAHAN OTOT MENGGUNAKAN SINYAL EMG DAN DETEKTOR GAYA PADA GERAK EKSTENSI DAN FLEKSI KNEE-JOINT UNTUK EVALUASI PENGGUNAAN FUNCTIONAL ELECTRICAL STIMULATION PADA SISTEM REHABILITASI LOWER LIMB. Undergraduate Thesis, Institut Teknologi Sepuluh November.
Diterbitkan
Cara Mengutip
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2024 Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Artikel ini berlisensiCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
