Research on Gait Detection and Recognition of Lower Limb Exoskeleton Based on SVMBP
نویسندگان
چکیده
منابع مشابه
A Neural Network-Based Gait Phase Classification Method Using Sensors Equipped on Lower Limb Exoskeleton Robots
An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such robots, foot sensors with force sensing registers are commonly used to classify gait phases. We describe classifiers th...
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A new compact mobile lower limb robotic exoskeleton (MLLRE) has been developed for gait rehabilitation for neurologically impaired patients. This robotic exoskeleton is composed of two exoskeletal orthoses, an active body weight support (BWS) system attached to a motorized mobile base, allowing over-ground walking. The exoskeletal orthosis is optimized to implement the extension and flexion of ...
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There are numerous causes that can affect the functioning of the human locomotor system, leading to the appearance of joint disorders in the lower limb and generating atypical gait patterns. The importance of research and development in assistance technologies to compensate pathological gait have been recognised since the beginning of the twentieth century and numerous challenges still lie ahea...
متن کاملGait Phase Recognition for Lower-Limb Exoskeleton with Only Joint Angular Sensors
Gait phase is widely used for gait trajectory generation, gait control and gait evaluation on lower-limb exoskeletons. So far, a variety of methods have been developed to identify the gait phase for lower-limb exoskeletons. Angular sensors on lower-limb exoskeletons are essential for joint closed-loop controlling; however, other types of sensors, such as plantar pressure, attitude or inertial m...
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Since surface electromyograghic (sEMG) signals are non-invasive and capable of reflecting humans’ motion intention, they have been widely used for the motion recognition of upper limbs. However, limited research has been conducted for lower limbs, because the sEMGs of lower limbs are easily affected by body gravity and muscle jitter. In this paper, sEMG signals and accelerometer signals are acq...
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ژورنال
عنوان ژورنال: Jixie gongcheng xuebao
سال: 2022
ISSN: ['0577-6686']
DOI: https://doi.org/10.3901/jme.2022.12.029