In this paper, we present a fuzzy-logic-based hybrid locomotion mode classification method for an active pelvis orthosis. Locomotion information measured by the onboard hip joint angle sensors and the pressure insoles is used to classify five locomotion modes, including two static modes (sitting, standing still), and three dynamic modes (level-ground walking, ascending stairs, and descending stairs). The proposed method classifies these two kinds of modes first by monitoring the variation of the relative hip joint angle between the two legs within a specific period. Static states are then classified by the time-based absolute hip joint angle. As for dynamic modes, a fuzzy-logic based method is proposed for the classification. Preliminary ex...
Intelligent lower-limb prosthesis appears in the public view due to its attractive and potential fun...
The objective of the work presented here is to develop a low cost active above knee prosthetic devic...
Current state-of-the-art locomotion mode classifiers for controlling robotic lower-limb prostheses r...
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...
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...
Recognizing locomotion modes is a crucial step in controlling lower-limb exoskeletons/orthoses. Our ...
Real-time recognition of locomotion-related activities is a fundamental skill that the controller of...
International audienceGait modes, such as level walking, stair ascent/descentand ramp ascent/descent...
Computerized gait analysis using fuzzy logic has become an integral part of the treatment decision-m...
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...
Intelligent lower-limb prosthesis appears in the public view due to its attractive and potential fun...
The objective of the work presented here is to develop a low cost active above knee prosthetic devic...
Current state-of-the-art locomotion mode classifiers for controlling robotic lower-limb prostheses r...
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...
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...
Recognizing locomotion modes is a crucial step in controlling lower-limb exoskeletons/orthoses. Our ...
Real-time recognition of locomotion-related activities is a fundamental skill that the controller of...
International audienceGait modes, such as level walking, stair ascent/descentand ramp ascent/descent...
Computerized gait analysis using fuzzy logic has become an integral part of the treatment decision-m...
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...
Intelligent lower-limb prosthesis appears in the public view due to its attractive and potential fun...
The objective of the work presented here is to develop a low cost active above knee prosthetic devic...
Current state-of-the-art locomotion mode classifiers for controlling robotic lower-limb prostheses r...