Real-Time Identification of Knee Joint Walking Gait as Preliminary Signal for Developing Lower Limb Exoskeleton
| العنوان: | Real-Time Identification of Knee Joint Walking Gait as Preliminary Signal for Developing Lower Limb Exoskeleton |
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| المؤلفون: | Abdullah Sani, Daniel Sutopo Pamungkas, Hendawan Soebhakti, Susanto Susanto, Riska Analia, Wahyu Caesarendra, Ipensius Tua Simorangkir |
| المصدر: | Electronics, Vol 10, Iss 2117, p 2117 (2021) Electronics Volume 10 Issue 17 |
| بيانات النشر: | MDPI AG, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | real-time application, medicine.medical_specialty, Rehabilitation, TK7800-8360, Computer Networks and Communications, Computer science, neural network, medicine.medical_treatment, Work (physics), Wearable computer, wearable sensor, Knee Joint, Exoskeleton, walking gait cycle, Physical medicine and rehabilitation, Stairs, Hardware and Architecture, Control and Systems Engineering, Inertial measurement unit, Climbing, Signal Processing, medicine, Electrical and Electronic Engineering, Electronics |
| الوصف: | An exoskeleton is a device used for walking rehabilitation. In order to develop a proper rehabilitation exoskeleton, a user’s walking intention needs to be captured as the initial step of work. Moreover, every human has a unique walking gait style. This work introduced a wearable sensor, which aimed to recognize the walking gait phase, as the fundamental step before applying it into the rehabilitation exoskeleton. The sensor used in this work was the IMU sensor, used to recognize the pitch angle generated from the knee joint while the user walks, as information about the walking gait cycle, before doing the investigation on how to identify the walking gait cycle. In order to identify the walking gait cycle, Neural Network has been proposed as a method. The gait cycle identification was generated to recognize the gait cycle on the knee joint. To verify the performance of the proposed method, experiments have been done in real-time application. The experiments were carried out with different processes such as walking on a flat floor, climbing up, and walking down stairs. Five subjects were trained and tested using the system. The experiments showed that the proposed method was able to recognize each gait cycle for all users as they wore the sensor on their knee joints. This study has the potential to be applied on an exoskeleton rehabilitation robot as a further research experiment. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 2079-9292 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::52df2f9007d296555698096fbbdb15ac https://www.mdpi.com/2079-9292/10/17/2117 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....52df2f9007d296555698096fbbdb15ac |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 20799292 |
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