Aug 4, 2022 · This study designs a deep neural network to detect gait phases, including heel-strike (HS), foot-flat (FF), heel-off (HO) and swing (SW).

This study designs a deep neural network to detect gait phases, including heel-strike (HS), foot-flat (FF), heel-off (HO) and swing (SW).

Jun 11, 2023 · In this paper, we highlight some advantages of using adaptive frequency oscillators (AFOs) over traditional gait event detection algorithms.

May 17, 2023 · This study aimed to investigate whether muscle synergy features could provide a more accurate and robust classification of gait events.

This paper proposes a real-time, multi-classifier system that incorporates three artificial neural network (ANN) models to simultaneously recognize five gait ...

In this paper we present a classifier based on a hidden Markov model (HMM) that was applied to a gait treadmill dataset for gait phase detection and walking/ ...

Apr 21, 2018 · Performance of several gait phase detection systems reported in the literature. The number of gait phases considered in these papers is four.

This paper presents a data-driven approach for real-time gait phase detection to facilitate gait analysis and rehabilitation.

Gait phase detection holds significant importance in rehabilitation robotic systems, enabling precise and timely control of the patient's walking patterns.

Mar 8, 2023 · To get more precise and realistic sequencing of the gait cycle, we chose to only use the information of heel or toe contacts with Force Sensing.