Gait Phase Detection System based on Peak Detection Method and Neural Network
سال انتشار: 1403
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 78
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شناسه ملی سند علمی:
ISME32_237
تاریخ نمایه سازی: 15 تیر 1403
چکیده مقاله:
Accurate human gait phase detection is imperative in rehabilitation and robotics, forming the foundation for developing adaptive technologies and interventions. Precise gait detection enables the timing and coordination of robotic assistance or rehabilitation exercises tailored to specific gait cycle phases. In this study, a custom designed inertial measurement unit was fixated on an individual's lower back, and a peak detection method was developed for detecting heel strike and toe-off events. The method solely uses the linear acceleration data along the subject's walking direction. Two insoles with push button switches were placed in the subject's custom-designed shoes to identify instants of foot contact and lift-off. The differ-ences between the timing and peak linear accelerations of the switches were measured. Subsequently, distinct
phases of gait on the right and left feet were detected, and
data labeling was performed. This process was repeated
for ۱۴ trials, generating a dataset comprising the linear
acceleration and angular orientation. Finally, a neural
network model was designed, trained, and evaluated using
this dataset. The proposed technique demonstrated a
notable performance in detecting the defined phases with
approximately ۸۵% accuracy on average for all phases.
کلیدواژه ها:
نویسندگان
Amir Sadeghi
Department of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad
Mostafa Moazen Kakhki
Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad
Amirhosein Feiz
Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad
Seyed Abdolmajid Yousefsani
Department of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad
Alireza Akbarzadeh
Department of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad