Muhammad Hilman Fatoni, S.T., M.T.

Nama : Muhammad Hilman Fatoni, S.T., M.T.
NIP : 199103252015041001
NIDN : 0025039101
Email : hilmanfatoni[at] / mhilman.fatoni[at]
Pendidikan : S1: ITS, Teknik Elektro – Elektronika (2008-2012)
  S2: ITS, Teknik Elektro – Elektronika (2011-2014)
Bidang Keahlian :
Perolehan HKI :
Profil : Curiculum Vitae | Sinta | Google Scholar | Scopus


  • 2019, Development of Detection and Measurement Systems of Fetal Biometry from Ultrasonographic Image for Fetal Development Monitoring and Growth
  • 2019, wearaBLE: Open Source Hardware Platform for Development of Wearable Wireless Body Area Networks based on Bluetooth Low Energy (BLE)
  • 2019, Development of Vibration Control of Electromyogram Based Hands-Free Electrolarynx
  • 2018, Development of Subject Training System to Increase Success Rate in Electric Wheelchair Control Based on Brain Computer Interface
  • 2018, Feasibility Study Design of 12-channel Internetconnected ECG for Screening of Coronary Heart Disease in Public Health Center
  • 2017, Design of Telecardiac System for extracting temporal parameters of heart signals and sending them via radio channels
  • 2017, Application of Brain Computer Interface Based on Sensorymotor Rhythms Activity as an Electric Wheelchair Controller Interface
  • 2016, Spatial Filter Application in Computer Brain Interface System Using Lower Limb Motor Information
  • 2013, Analisa Sinyal EEG Saat Menggerakkan Kedua Kaki Sebagai FES Control Command Pada Proses Rehabilitasi Pasien Pasca Stroke
  • 2012, Identification of Motor Imagery on EEG Signals when Giving Command to Upper Limb Segment

Conference Proceedings

Tahun 2017

[1] Aliansyah; Achmad Nur, Arifin; Achmad, Purwanto; Djoko , Fatoni; Muhammad Hilman, “Extraction of Brain Signal during Motor Imagery Task for Wheelchair Control Command”, International Conference on Research & Innovation in Computer, Electronics and Manufacturing Engineering (RICEME-17), Feb. 2-3, 2017. Bali (Indonesia). pp. 25.

Abstract—Paralysis is a disease that causes loss of function from one or more muscle. When someone is paralyzed, the brain still works to obtain information about body activities. While doing or imagining movement, the similar response occurs in the brain. The purpose of this study was to detect any change the value of Event Related Desynchronization/Event Related Synchronization (ERD/ERS) during event. Time-frequency domain analysis was used to determine the frequency dominant when it occurred. This
information would be used as a Band Pass Filter for calculating the value of ERD/ERS. In this research, EEG signals were acquired from channel C3, C3-F3, C4, and C4-F4 base on international system
10/20 from EEG. The findings show that the range of frequency dominant from selected channels on all subject is 8-12Hz. The value of ERD/ERS was changed 64.43% in channel C3 and 60% in channel
C3-F3 whereas in channel C4 was 64.43% and 66.67% in channel C4-F4. The change of value of ERD/ERS would be used as control command for wheelchair in the next research topic.

[2] Seminar Nasional Bioteknologi 2014 UBAYA, “Analisa Sinyal EEG Saat Menggerakkan Kedua Kaki Sebagai FES Control Command Pada Proses Rehabilitasi Pasien Pasca Stroke”, Surabaya, 27 -28 Februari 2014.