This paper presents a realtime locomotion mode recognition method for an active pelvis orthosis. Five locomotion modes, including sitting, standing still, level-ground walking, ascending stairs, and descending stairs, are taken into consideration. The recognition is performed with locomotion information measured by the onboard hip angle sensors and the pressure insoles. These five modes are firstly divided into static modes and dynamic modes, and the two kinds are classified by monitoring the variation of the relative hip angles of the two legs within a pre-defined period. Static states are further classified into sitting and standing still based on the absolute hip angle. As for dynamic modes, a fuzzy-logic based method is proposed for the...
Real-time recognition of locomotion-related activities is a fundamental skill that the controller of...
Abstract — This study investigated the use of surface electromyography (EMG) combined with pattern r...
Current state-of-the-art locomotion mode classifiers for controlling robotic lower-limb prostheses r...
This paper presents a realtime locomotion mode recognition method for an active pelvis orthosis. Fiv...
This paper presents a realtime locomotion mode recognition method for an active pelvis orthosis. Fiv...
In this paper, we present a fuzzy-logic-based hybrid locomotion mode classification method for an ac...
In this paper, we present a fuzzy-logic-based hybrid locomotion mode classification method for an ac...
Recognizing locomotion modes is a crucial step in controlling lower-limb exoskeletons/orthoses. Our ...
Real-time human intent recognition is important for controlling low-limb wearable robots. In this pa...
Recent development in lower limb prosthetics has seen an emergence of powered prosthesis that have t...
Understanding how to seamlessly adapt the assistance of lower-limb wearable assistive devices (activ...
International audienceGait modes, such as level walking, stair ascent/descentand ramp ascent/descent...
Real-time recognition of locomotion-related activities is a fundamental skill that the controller of...
Abstract — This study investigated the use of surface electromyography (EMG) combined with pattern r...
Current state-of-the-art locomotion mode classifiers for controlling robotic lower-limb prostheses r...
This paper presents a realtime locomotion mode recognition method for an active pelvis orthosis. Fiv...
This paper presents a realtime locomotion mode recognition method for an active pelvis orthosis. Fiv...
In this paper, we present a fuzzy-logic-based hybrid locomotion mode classification method for an ac...
In this paper, we present a fuzzy-logic-based hybrid locomotion mode classification method for an ac...
Recognizing locomotion modes is a crucial step in controlling lower-limb exoskeletons/orthoses. Our ...
Real-time human intent recognition is important for controlling low-limb wearable robots. In this pa...
Recent development in lower limb prosthetics has seen an emergence of powered prosthesis that have t...
Understanding how to seamlessly adapt the assistance of lower-limb wearable assistive devices (activ...
International audienceGait modes, such as level walking, stair ascent/descentand ramp ascent/descent...
Real-time recognition of locomotion-related activities is a fundamental skill that the controller of...
Abstract — This study investigated the use of surface electromyography (EMG) combined with pattern r...
Current state-of-the-art locomotion mode classifiers for controlling robotic lower-limb prostheses r...