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All Journal JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Journal of Electrical and Intelligent Systems (JEIS)
PAULUS SUSETYO WARDANA
Politeknik Elektronika Negeri Surabaya
Computer Science & IT

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Feature Extraction of Multichannel EMG Signals for Shoulder Joint Movement Patterns Paulus Susetyo Wardana; Lince Markis; Rika Rokhana
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 2 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.2.614

Abstract

Electromyography (EMG) signals provide information about muscle activity and can support rehabilitation and prosthetic control systems. This study aims to extract and analyze features of multichannel EMG signals recorded from seven shoulder joint movement patterns. EMG data were acquired using surface electrodes placed on eight dominant muscles associated with shoulder joint motion, namely Deltoid1, Deltoid2, Infraspinatus, Supraspinatus, Teres Major, Latissimus Dorsi, Pectoralis1, and Pectoralis2. The recorded movements included resting, shoulder flexion, shoulder extension, shoulder abduction, shoulder adduction, external rotation, and internal rotation. The proposed processing procedure consisted of signal acquisition, rectification, transformation into the frequency domain using Discrete Fourier Transform, and feature extraction using Linear Envelope, Modified Mean Frequency (MMNF), and Modified Median Frequency (MMDF). The results show that Linear Envelope can describe temporal energy changes in each movement pattern, while MMNF and MMDF can identify groups of similar signal patterns and distinguish several movements through specific muscle channels. Resting movement had very small amplitude changes, while active shoulder movements produced different dominant energy patterns across subjects. MMNF and MMDF produced two main similarity groups, although the distinguishing muscles differed among subjects. These findings indicate that multichannel EMG feature extraction is useful as an initial basis for shoulder movement pattern analysis; however, further development is required to improve online acquisition, automatic gain adjustment, and classification robustness.
Automatic Control of Oxygen Flow for Hypoxemia Therapy Based on Fuzzy Method Rika Rokhana; Santi Anggraini; Retno Sukmaningrum; Hary Oktavianto; Paulus Susetyo Wardana; Agrippina Waya Rahmaning; Moch. Rochmad; Kemalasari; Hendhi Hermawan Efendi; Zainal Arief
Journal of Electrical and Intelligent Systems Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/jeis.v1i1.2

Abstract

Hypoxemia is a serious condition that requires oxygen transfusion. Indiscriminate oxygen administration is a poor strategy that can increase organ damage and even death. This paper describes a system for automatically controlling airflow of an oxygen tubes to a patient based on blood oxygen saturation and respiratory rate measurements. The MAX30102 sensor is used to measure oxygen saturation levels, and the MAX9814 module is used to determine respiratory rate. Both sensor outputs are processed by an STM32F411 microcontroller, and then sent wirelessly to an Arduino Uno microcontroller, which implements the fuzzy logic controller to control oxygen flow. The fuzzy output is used to activate a motor servo that controls the oxygen tube valve opening. The valve opening width (in degrees) is divided into 5 categories. Communication between the microcontroller and the valve actuator uses a 433MHz wireless RF module. The device test results revealed an MAE of 0.40% for oxygen saturation measurements compared to standard hospital measuring instruments and an MAE of 0.47% for respiratory rate measurements compared to manual measurements. Overall system testing produced a valve opening with an MAE of 0.56% compared to simulation results using MATLAB.
Co-Authors Agrippina Waya Rahmaning Hary Oktavianto Hendhi Hermawan Efendi Kemalasari Lince Markis Moch. Rochmad Retno Sukmaningrum Rika Rokhana Santi Anggraini Zainal Arief