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Prototype Development of Myoelectrics Signal-Based Exoskeleton Anggrian Riska Amelia Shabrine; Pujiyanto Pujiyanto; Akif Rahmatillah
Indonesian Applied Physics Letters Vol. 2 No. 1 (2021): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v2i1.28296

Abstract

Diffable is incompleteness or abnormality accompanied by consequences for specific functions. The method used is tapping on the hamstring and hamstring muscles quadriceps to determine the resulting voltage—muscle signal tapping using Electromyograph (EMG) and Ag-AgCl electrodes. Average current-voltage contraction and relaxation are used as threshold values to drive the servo motor. This study indicates the tension when the muscle contracts are in the range of 4 volts while the relaxation time is 0.4 volts. Then it can be concluded that the voltage when the muscle is contracted is more significant than when it is relaxed. Using different tension during contraction and relaxation in normal subjects showed that the different tension could drive the prototype exoskeleton.
Pelatihan Otomasi Media Cuci Tangan untuk Mencegah Penularan Virus SARS-CoV-2 Pada Siswa SMA dan MA di Kab. Gresik Imam Sapuan; Franky Chandra; Akif Rahmatillah
PROSIDING SEMINAR NASIONAL PENGABDIAN KEPADA MASYARAKAT UNIVERSITAS NAHDLATUL ULAMA SURABAYA Vol. 1 No. 1 (2022): Prosiding Seminar Nasional Pengabdian Kepada Masyarakat : Perguruan Tinggi Meng
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.035 KB) | DOI: 10.33086/snpm.v1i1.883

Abstract

Kebutuhan sistem otomatis untuk media cuci tangan sangat tinggi karena cuci tangan dengan sabun mempunyai efektifitas yang baik demi pencegahan penyebaran virus SARS-CoV-2. Selain itu media cuci tangan otomatis juga dapat menghindarkan penyebaran virus ini secara tidak langsung melalui sentuhan tangan dengan permukaan benda seperti kran air. Rangkaian elektronika berupa sensor cahaya (LDR), rangkaian komparator, rangkaian transistor sebagai saklar elektronik dan logika relay dapat digunakan sebagai sistem otomasi bagi media cuci tangan. Konsep sistem ini berbasis pengetahuan dasar Fisika terutama pada bidang listrik dan magnet sehingga dengan mempelajari dan menerapkan sistem otomasi berbasis rangkain elektronika ini dapat pula menjadi terapan dari teori–teori Fisika yang dipelajari di Sekolah Menengah Atas maupun sederajat. Melalui program pelatihan otomasi media pencuci tangan berbasis rangkaian elektronika pada siswa SMA dan MA ini maka para siswa dapat menerapkan secara riil teori Fisika listrik dan magnet untuk memecahkan permasalahan dalam masyarakat secara langsung yaitu pencegahan penyebaran virus SARS-CoV-2 sehingga dapat meningkatkan motivasi dalam mempelajari Fisika.
EMG Based HCI Device to Support Computer Operation Firman Isma Isma Serdana; Akif Rahmatillah; Soegianto Soelistiono
ROTASI Vol 25, No 2 (2023): VOLUME 25, NOMOR 2, APRIL 2023
Publisher : Departemen Teknik Mesin, Fakultas Teknik, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/rotasi.25.2.30-36

Abstract

The human computer interface is a method of interaction between a person and a computer that utilizes a human interface device. One example of this is using hand movements to control a computer pointer, which produces a unique electromyography signal for each basic movement direction (up, down, right, and left). This project utilized an artificial neural network with a structure of seven inputs, ten hidden layer nodes, and four outputs to classify electromyography signals from the brachioradialis and flexor carpum ulnaris muscles into four basic movement categories within an Arduino Uno. The artificial neural network was trained offline using a high-capacity machine for efficiency since the Arduino Uno has low raw processing capability. The Sparkfun Pro Micro's HID function and the mouse.move() library were used to translate the classification results into pointer movement on a PC. The classification rate for the prerequisites setting resulted in an average of 93.7375%, with individual classification rates of 96.55% for up movement, 93.4% for down movement, 90.85% for right movement, and 91.95% for left movement.
Application of ANFIS-based Non-Linear Regression Modelling to Predict Concentration Level in Concentration Grid Test as Early Detection of ADHD in Children Sayyidul Istighfar Ittaqillah; Delfina Amarissa Sumanang; Quinolina Thifal; Akila Firdausi Harahap; Akif Rahmatillah; Alfian Pramudita Putra; Riries Rulaningtyas; Osmalina Nur Rahma, S.T., M.Si.
Indonesian Applied Physics Letters Vol. 4 No. 1 (2023): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v4i1.48153

Abstract

Concentration is the main asset for students and serves as an indicator of successful learning implementation. One of the abnormal disturbances that can occur in a child's concentration development is attention deficit hyperactivity disorder (ADHD). The prevalence of ADHD in Indonesia in 2014 reached 12.81 million people due to delayed management in addressing ADHD. Therefore, early detection of ADHD is necessary for prevention. ADHD detection can be done by testing the level of concentration using a concentration grid. However, a method is needed that can be applied to uncooperative young children who are not familiar with numbers. Therefore, research was conducted with an innovative approach using a combination of EEG-ECG to classify concentration levels. The data used in this study were primary data from 4 participants with 5 repetitions. The data were processed in the preprocessing stage, which involved noise filtering and Butterworth filtering. The features used in this study were BPM (beats per minute), alpha, theta, and beta EEG signals, which would later become inputs for the Adaptive Neuro-Fuzzy Inference System (ANFIS). The output shows that the combination of EEG-ECG has the potential to predict concentration test results. Using BPM, alpha, theta, and beta signals can serve as parameters for predicting the concentration grid test values using ANFIS effectively. In the ANFIS model with 4 features, an accuracy of 99.997% was obtained for the training data and 80.2142% for the testing data. This result could be developed for early detection of ADHD based on concentration levels so the learning implementation could be more effective.
Electronic Nose (E-Nose) for Quality Detection of Tuna (Thunnus thynnus) Contaminated Bacteria Astuti, Suryani Dyah; Muhamad, Alfian Baggraf; Rahmatillah, Akif; Yaqubi, Ahmad Khalil; Susilo, Yunus; Aji , Angger Krisna
Indonesian Journal of Tropical and Infectious Disease Vol. 11 No. 1 (2023)
Publisher : Institute of Topical Disease Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/ijtid.v11i1.39206

Abstract

Tuna (Thunnus thynnus) is a food that is often consumed raw to support raw food diet activities, so it has the potential to be contaminated with Salmonella typhi bacteria. Fish can be contaminated by bacteria due to their high water and protein content. Indonesia is the world's main tuna producer. Salmonella typhi detection in fresh tuna in Indonesia must be negative for Salmonella microbial contamination in order to meet food safety requirements. Microbial testing has drawbacks, such as long delays. An electronic nose was used to detect Salmonella typhi bacteria in tuna fish. The sample used consisted of 3 kinds of samples: Salmonella typhi bacteria, tuna, and tuna with Salmonella typhi contamination. The research was conducted with a shelf life of 48 hours and a sensing period every 6 hours with a sensor array of 8 sensors. The sensor output data is processed using the PCA (Principal Component Analysis) method. Through the PCA method, each variation of bacterial treatment can be classified. The result of the cumulative percentage variance of the two main components (PC) in the classification test between Salmonella typhi, tuna, and tuna with Salmonella typhi bacteria contamination was 90.5%. The most influential sensors in this study are TGS 825 for PC1 with a loading value of 0.625 and TGS 826 for PC2 with a loading value of -0.753. Therefore, it can be concluded that an electronic nose can classify between pure tuna and tuna contaminated with Salmonella typhi bacteria.
Online PID-neural network for tracking lower limb rehabilitation exoskeleton angular position Hanifah, Ummi; Adinda, Aura; Rahmatillah, Akif; Sapuan, Imam; Ain, Khusnul; Septanto, Harry; Chai, Rifai
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9395

Abstract

Gait trajectory tracking control is an essential component of a lower limb rehabilitation exoskeleton (LLRE). Meanwhile, the proportional-integral-derivative (PID) controller remains popular for a variety of applications, including LLRE. Nonetheless, employing PID presents a significant issue, namely determining how to choose or tune the parameters. This paper addresses the LLRE’s hipknee angular position tracking system based on an online PID-NN controller, i.e., a PID controller, whose parameters are online modified by a trained neural network (NN). A proposed framework for designing the PID-NN controller is elaborated. Numerical verifications are carried out by comparing the performance of the PID-based control system, whose parameters have been tuned using Ziegler-Nichols (ZN), without and using NN. Performance comparisons involving the presence of external disturbance are also carried out. The simulation results show that the proposed PID-NN-based control system provides better performance with lower mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE) values.