Gait Phase Recognition using Textile-based Sensor

Pazar A., Khalilbayli F., Özlem K., Yılmaz F., TUNÇAY ATALAY A., Atalay Ö., ...More

7th International Conference on Computer Science and Engineering, UBMK 2022, Diyarbakır, Turkey, 14 - 16 September 2022, pp.338-343 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/ubmk55850.2022.9919491
  • City: Diyarbakır
  • Country: Turkey
  • Page Numbers: pp.338-343
  • Keywords: Gait Analysis, Inertial Measurement Unit, Long Short-Term Memory, Real-time Gait Phase Recognition, Textile-based Strain Sensor
  • Istanbul Technical University Affiliated: Yes


© 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.