Publication: Gait Phase Recognition using Textile-based Sensor
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IEEE
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© 2022 IEEE.Human gait phase detection has become an emerging field of study due to its impact in various clinical studies. In this study, a system is developed to detect the toe-off, mid-swing, heel-strike, and heel-off phases of a gait cycle in real-time by using a textile-based capacitive strain sensor mounted on the kneepad. Five healthy subjects performed walks including those four phases of the gait at a constant speed and gait distance in a laboratory environment while wearing the kneepad. The phases are labeled according to the gyroscope data of the Inertial Measurement Unit (IMU) located on the kneepad. An Long Short-Term Memory (LSTM) based network is utilized to detect the phases using the capacitance data obtained from the strain sensor. Recognition of four phases with 87 % accuracy is accomplished.
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COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, Computer Networks and Communications, Mühendislik, ENGINEERING, algorithms, BİLGİSAYAR BİLİMİ, YAPAY ZEKA, Information Systems, Communication and Control Engineering, Yapay Zeka, Bilgisayarla Görme ve Örüntü Tanıma, Artificial Intelligence, Long Short-Term Memory, Bilgisayar Bilimleri, Textile-based Strain Sensor, Engineering, Computing & Technology (ENG), Bilgisayar Bilimi Uygulamaları, Computer Sciences, Mühendislik, Bilişim ve Teknoloji (ENG), COMPUTER SCIENCE, Real-time Gait Phase Recognition, Computer Science Applications, Fizik Bilimleri, Physical Sciences, TELECOMMUNICATIONS, Engineering and Technology, Bilgisayar Bilimi, Inertial Measurement Unit, Mühendislik ve Teknoloji, Computer Vision and Pattern Recognition, Bilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği, Gait Analysis, Algoritmalar, TELEKOMÜNİKASYON, Bilgisayar Ağları ve İletişim