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The final goal of our research is to develop a rehabilitation support robot for self-standing-up training of hemiplegic stroke patients to restore normal standing-up motion. To improve the motor function of the patient's paralyzed leg, a guided standing-up training is effective. The therapist controls the patient's left/right load balance by pulling or pushing the patient's waist during standing-up...
This paper introduces a new Learning from Demonstration (LfD)-based method that makes usage of robot effector forces and torques recorded during expert demonstrations, to generate force-based haptic guidance reference trajectories on-line, that are intended to be used during haptic shared control for additional operator ‘guidance’. Derived haptic guidance trajectories are superimposed to master-device...
Haptic guidance has previously been employed to improve human performance in control tasks. This paper presents an experiment to evaluate whether haptic feedback can be used to help humans learn a compensatory tracking task. In the experiment, participants were divided into two groups: the haptic group and the no-aid group. The haptic group performed a first training phase with haptic feedback and...
Given the difficulty of developing physics-based degradation process models in practice, data-driven prognostics approaches are preferred in several industrial applications. Among data-driven approaches, one can distinguish between (i) degradation-based approaches that predict the future evolution of the equipment degradation and (ii) direct Remaining Useful Life (RUL) prediction approaches which...
Always-on localization is an important problem for a lot of context sensitive mobile computing applications. This paper proposes WaveLoc, which effectively uses measurements from a trajectory as its fingerprint for localization. Different from traditional approaches, which use signatures from single-points for localization, we leverage signatures from a trajectory, since it offers a lot more information...
The paper presents a method for developing illusionary flight profiles situations for practical testing of pilots using the GYRO IPT II spatial disorientation simulator. Standard flight profiles do not use the full capability of the simulator to train pilots for recognition and recovery from illusions appearing unexpectedly. For this reason, there is a need to create new flight profiles so as to demonstrate...
Between 6 and 9 months of age, infants begin to differentiate between the actions of others that are “rational” with respect to goals and those that are not. According to the teleological stance theory, this behavior is underpinned by an innate, naive rationality principle; according to a statistical learning account, experience alone is sufficient to explain this behavior. We present a recurrent...
In this work, we propose a multi-view temporal video segmentation approach that employs a Gaussian scoring process for determining the best segmentation positions. By exploiting the semantic action information that the dense trajectories video description offers, this method can detect intra-shot actions as well, unlike shot boundary detection approaches. We compare the temporal segmentation results...
Motion information is a key factor for action recognition and has been eagerly pursued for decades. How to effectively learn motion features in Convolutional Networks (ConvNets) remains an open issue. Prevalent ConvNets often take several full frames of video as input at a time, which can be a heavy burden for network training. In this paper, we introduce a novel framework called Tube ConvNets, by...
We consider the problem of automatic construction of algorithms for recognition of abnormal behavior segments in phase trajectories of dynamic systems. The recognition algorithm is trained on a set of trajectories containing normal and abnormal behavior of the system. The exact position of segments corresponding to abnormal behavior in the trajectories of the training set is unknown. To construct...
Dance traditions constitute a significant aspect of cultural heritage around the world. The organization, semantic analysis, and retrieval of dance-related multimedia content (i.e., music, video) in databases is, therefore, crucial to their preservation. In this paper we explore the problem of folk dances recognition from video recordings, focusing on Greek folk dances, using different representations...
This paper introduces a novel gait parameterization method that models gait kinematics as a continuous function of gait cycle phase, walking speed, and ground slope. Kinematic data was recorded from seven able-bodied subjects walking on a treadmill at twenty-seven combinations of walking speed and ground slope. Convex optimization was used to determine the parameters of a function of three variables...
Chronic pain is a disease that the patients suffers a lot in their daily life and it is difficult to be released completely. It is difficult to manage because pain can come anytime and it is unpredictable. However, the pain can be represented by the pain related behaviors such as guiding and abrupt actions. In this paper, we will develop a machine learning based system that can detect the pain related...
Reinforcement learning is an effective algorithm for brain machine interfaces (BMIs) which interprets the mapping between neural activities with plasticity and the kinematics. Exploring large state-action space is difficulty when the complicated BMIs needs to assign credits over both time and space. For BMIs attention gated reinforcement learning (AGREL) has been developed to classify multi-actions...
For trajectory model to study mining, using Vector Fields on Manifold instead of the Euclidean distance to metric similarity between trajectories, multi scale transform method is used to optimize the mapping in the Vector Fields on Manifold trajectory distance calculation and use Som algorithm for training a classification model. This method will be the trajectory shape features to measure the similarity...
Previous results suggest that haptic guidance enhances learning of the timing components of motor tasks, whereas error amplification is better for learning the spatial components. In this paper we evaluate a novel mixed guidance controller that combines haptic guidance and error amplification to simultaneously promote learning of the timing and spatial components. The controller is realized using...
Many supervised approaches report state-of-the-art results for recognizing short-term actions in manually clipped videos by utilizing fine body motion information. The main downside of these approaches is that they are not applicable in real world settings. The challenge is different when it comes to unstructured scenes and long-term videos. Unsupervised approaches have been used to model the long-term...
This paper discusses the problem of one shot gesture recognition. This is relevant to the field of human-robot interaction, where the user's intentions are indicated through spontaneous gesturing (one shot) to the robot. The novelty of this work consists of learning the process that leads to the creation of a gesture, rather on the gesture itself. In our case, the context involves the way in which...
Active training mode has good clinical effect for patients who need lower limb rehabilitation, and estimation for the motion trajectory of human lower limb is one of the most important and fundamental work for active training. In this study, a novel estimation method is proposed based on ε-support vector regression (ε-SVR) using acceleration signals of lower limb. Firstly, some qualitative variation...
Rehabilitation robots have been widely used in clinical rehabilitation in stroke subjects. The safety and comfort in rehabilitation training still are affected by many problems, however, such as the single rehabilitation training mode, the poor human-robot interaction and adaptability. In this paper, an adaptive trajectory planning method of lower limb rehabilitation robot based on surface Electromyography...
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