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Lower-limb exoskeleton is widely used for assisting walk in rehabilitation field. One key problem for exoskeleton control is to model and predict the suitable gait trajectories of wearer. In this paper, we propose a Deep Rehabilitation Gait Learning (DRGL) for modeling the knee joints of lower-limb exoskeleton, which firstly leverage Long-Short Term Memory (LSTM) to learn the inherent spatial-temporal...
In this paper, a running person detection method is proposed for the community patrol robot. The challenges include the diversity of movement direction and the ego-motion of camera. The diversity of movement direction means that it is difficult to gain high accuracy detection by only using appearance information. The ego-motion of camera means that the motion information contains high noise. To address...
This paper introduces a novel approach to predict human motion for the Non-binding Lower Extremity Exoskeleton (NBLEX). Most of the exoskeletons must be attached to the pilot, which exists potential security problems. In order to solve these problems, the NBLEX is studied and designed to free pilots from the exoskeletons. Rather than applying Electromyography (EMG) and Ground Reaction Force (GFR)...
Real-time performance can be greatly improved, if the early recognition is implemented. In this paper, a dynamic hand gesture early recognition system is proposed. The system can recognize the gesture before it is completed. Our method is based on the Hidden Semi-Markov Models. Three-dimensional information of the gesture trajectory collected by leapmotion is the main data we used. Experiments on...
In this paper, an abnormal event detection system inspired by the saliency attention mechanism of human visual system is presented. Conventionally, training-based methods assume that anomalies are events with rare appearance, which suffer from visual scale, complexity of normal events and insufficiency of training data. Instead, we make the assumption that anomalies are events that attract human attentions...
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