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Journal : Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control

Development of Digital Ventilator with Internet of Things for Preparation of the Next Outbreak in Indonesia Dimas Adiputra; Isa Hafidz; Billy Montolalu; Fauzan Rasyid
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vo. 6, No. 3, August 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i3.1281

Abstract

The emergency of the healthcare device unit, such as a ventilator, has been experienced during the COVID-19 pandemic in 2020. Therefore, ventilator usage is not hard suggested anymore for COVID-19 patients compared to the outbreak beginning. Despite that, it is still essential to have the ventilator ready, if possible, in each house, for the upcoming respiratory syndrome outbreak. Therefore, in this paper, a digital ventilator development is presented. The digital ventilator is comprised of three main parts, such as respiration mechanism (I), controller Internet of Things (IoT) module (II), and website application (III). The developed digital ventilator has been tested by comparing the measurement of respiratory data between the developed digital ventilator and gas flow analyzer. Results show that the respiratory data, such as Pressure Peak (PPeak), Positive End Respiratory Pressure (PEEP), Inspiratory Expiratory Ratio (IE Ratio), Breath per Minute (BPM), and Tidal Volume can be monitored and controlled both directly and online via website application consistently (standard deviation around 10%) with PPeak absolute error of 1.35 mbar, the PEEP absolute error of 0.16 mbar. Furthermore, the average time response of the digital ventilator to the input command from the website application is 0.23 s. Therefore, it is safe to assume that the doctor can use the website application to control the digital ventilator remotely.
Robot Ankle Foot Orthosis with Auto Flexion Mode for Foot Drop Training on Post-Stroke Patient in Indonesia Dimas Adiputra; Ubaidillah; Ully Asfari; Hari Sulistiyo Budi Waspada; Reza Humaidi; Bagas Wahyu Prakoso; Andi Nur Halisyah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 4, November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i4.1533

Abstract

Robot Ankle Foot Orthosis (AFO) has been proven to assist the gait impairment, such as the foot drop. However, development challenge is still remains, such as the trade-off between complexity, functionality and cost. High functionality resulted in high cost, bulky, and complex device. But affordability and simplicity may decrease functionality. Therefore, this research proposed a robot AFO, which has the necessary function of auto dorsi-plantarflexion so it can keep the affordability and simplicity. The robot AFO consists of structure, electronics part and algorithm. The structure is custom made according to the user’s anatomy. A brushless DC (BLDC) motor, Force-Sensing Resistor (FSR) and microcontroller builds the electronic parts. The BLDC motor actuates the flexion, while the FSR detects the gait phase to determine the action. Both are integrated by the microcontroller with the P control algorithm that commands the BLDC motor to generate necessary torque so it rotates in a constant speed. A functionality test has been carried out on the robot AFO, where the robot AFO perform a dorsi-plantarflexion continuously in three conditions, such as no load, 1 Kg load, and foot load. The robot AFO successfully performed a constant velocity rotation in both directions, in all conditions. In the case of 1 Kg load, the maximum angular speed is 0.7 rad/s dorsiflexion and -1.8 rad/s plantarflexion. The torque keeps increasing and decreasing from -0.3 Nm to 4 Nm to keep the angular velocity. The result shows that the robot AFO can perform the necessary function to assist the foot drop training. Functionality test on the gait detection has also been done where it shows that the robot AFO can detect the four gait phases accurately. The robot AFO has been tested and future study should test the robot on a real post-stroke patient to see the effect of the gait control in reality.
Co-Authors Abduh Sayid Albana Abdulloh Hamid Nushfi Aditya Yudhistira Afandi, Mas Aly Ahmad Habibi Aldo Juan Widodo Aliffah Rizkianingtyas, Nur Aliffah Rizkiningtyas, Nur Andi Nur Halisyah Anifatul Faricha Annisa'ul Baroroh Ardiansyah Al Farouq Arif, Rangga R. Arif, Rangga Roospratama Aris Kusumawati Arthur Silitonga Bagas Wahyu Prakoso Christian Jose Anto Kurniawan Christian Jose Anto Kurniawan Daffaldi, Rafly Dimas Bagas Wicaksono Dony Setiawan, Ananda Eka Sari Oktarina Era Anzha Naelil Munna Faiz Fanani, Ahmad Fatahillah, Aditya M. Fauzan Rasyid Firmansyah, Ryan Gilbert Wednestwo Samuel Gilbert Wednestwo Samuel Halisyah, Andi Nur Hari Sulistiyo Budi Waspada Hazel Dimas Prayogi, Mohammad Helmy Widyantara Humaidi, Reza Isa Hafidz Khodijah Amiroh Lora Khaula Amifia Lubis, Muhammad Rafli Ramadhan Moch. Bagus Indrastata Moch. Fauzan Rasyid Moch. Iskandar Riansyah Mohammad Yanuar Hariyawan Montolalu, Billy Nadia Dinda Pratama Putri Nathalia, Vita Ayu Nisa Isrofi Nismara, Radithya Anjar Nursyahjaya Ramadaniputra Pangestu Widodo, Pangestu Putra, Aldhitiansyah Putranto, Rifki Dwi Putranto, Rifky Dwi Ramadaniputra, Nursyahjaya Reza Humaidi Rizkianingtyas, Nur Aliffah Robin Addwiyansyah Alfaro Samrat SALSABILA, ANNISA Satria Fajar Rachmadianto Satrio, Kensora Bintang Panji Selamet, Sheila Shelvia Sevia Indah Purnama Shinvalraus Sains Raihan Kanzu Syakira Andriyani Syakira Andriyani Teks, Johnson G. A. Titus Kristanto Tri Rasmana, Susijanto Trisnawati, Azzahra Rizki Sulardi tsani, naufal tsani firjatulloh Ubaidillah Ulfa, Dinda Karisma Ully Asfari Vortis, Cindy G. Wahyu Andy Prastyabudi Yosefan Alfeus Bayuaji