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Teenagers need some guidance in order to decide the itinerary that best suits their competences and professional interests. They need to be aware of their abilities, a fundamental knowledge to have a successful access to the labour market. This short paper presents the preliminary results of an edutainment platform, Waypass, a gamified tool conceived to guide and empower young people during their...
We present in this paper a real-time method for visual categorization to do robot grasping. We describe an object database with SURF feature points which we quantify with the Kmeans clustering algorithm to make visual words. Then, we train a Support Vector Machine classifier having as entries the distribution of the bag of features extracted earlier. Likewise, we do object recognition using the SVM...
We present a Recurrent Neural Network (RNN), namely an Echo State Network (ESN), that performs sentence comprehension and can be used for Human-Robot Interaction (HRI). The RNN is trained to map sentence structures to meanings (i.e. predicates). We have previously shown that this ESN is able to generalize to unknown sentence structures. Moreover, it is able to learn English, French or both at the...
Virtual/mixed reality leveraging an encountered type haptic display will suffer difficulty if virtual and real objects are spatially discrepant. We propose a new method for resolving this issue, visual guidance. The visual guidance algorithm is defined and described in detail, and contrasted with a previously explored approach. The feasibility of the proposed algorithm is experimentally verified.
This study has developed a device and system for the exercise of eccentric contraction of the tibialis anterior, with the objective of maintaining ambulatory function. A system was built that allows for exercises of appropriate load and speed, by providing the trainee with force data in the form of visual feedback. An experimental verification with two healthy participants shows small variation in...
With the aging population problem getting more and more aggravated, the number of hemiplegia patients increases rapidly, which results in the increasing requirement of rehabilitation training for regaining the body movement function. Taking advantages of rehabilitation robots makes the rehabilitation training more scientific and efficient compared to traditional rehabilitation measures such as manual...
Brain-machine interface (BMI) systems have the potential to restore function to people who suffer from paralysis due to a spinal cord injury. However, in order to achieve long-term use, BMI systems have to overcome two challenges — signal degeneration over time, and non-stationarity of signals. Effects of loss in spike signals over time can be mitigated by using local field potential (LFP) signals...
Following stroke, rehabilitation exercises paired with medical treatment are important for the recovery and maintenance of upper limb function. We developed a 2-DOF passive haptic system for upper limb rehabilitation and software focusing on reaching exercises, known as the coin collecting program, which provides training and evaluation of motor function, particularly dexterity. Past studies have...
Minimally invasive surgery can be performed with robotic assistance, as evolution of laparoscopic surgery. Robots for assisted surgery are far from being user friendly and require extensive training. To this end, ad-hoc devices and experimental set-ups are needed. The da Vinci system is one of the most diffused surgical robotics technology. The aim of the study was two-fold: i) to propose a neurophysiological...
Physical interaction between man and machines is increasing the interest of the research as well as the industrial community. It is known that physical coupling between active persons can be beneficial and increase the performance of the dyad compared to an individual. However, the factors that may result in performance benefits are still poorly understood. The aim of this work is to investigate how...
This paper studies the definition of risk and simply analyzes multi-investment risk management in detail. Aimed to establish a risk evaluation system of software project, an artificial neural network-based investing risk evaluation model of software project is proposed. In addition, it analyzes learning process of BP neural network. Finally, with the established neural network model to perform risk...
Voice-based system used in human-robot interaction is susceptible to challenging environment conditions. In an enclosed environment, the speech signal is often reflected which causes smearing as it is observed in the microphone. This phenomenon creates mismatch with the acoustic model, degrading the recognition performance and the robot's ability to understand and execute commands. Moreover, phantoms...
With the development of artificial intelligence, robot navigation based on natural language processing is concerned by more researchs. At the present stage, there are few studies on route natural language processing (RNLP), and there is no professional corpus, so the method of route natural language processing is generally based on a small amount of restricted corpus. This paper puts forward a method...
In recent decades, face recognition has been a hot topic in image processing, pattern recognition and other areas. To solve the issue of the lack of feature information brought by single training face sample, this paper proposed a method on homography transformation, which is about producing virtual multi-pose face by a front view image of face. First, assume that the single sample face is positive...
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...
One of the complicated issue in compliance control for rehabilitation and assistive robots is to predict right human's motion intention. In this paper, we have proposed an algorithm to estimate Desired Motion Intention (DMI) so that better compliance could be provided by the rehabilitation and assitive robots. Proposed algorithms is based on Extreme Learning Machine (ELM) and takes inputs from different...
The problem of place recognition is central to robot navigation. The robot needs to be able to recognize or at least to be able to estimate the likelihood that it has been at a place before when it has returned to a previously visited place. We cast the place recognition problem as one of classifying among multiple linear regression models, and argue that new theory from sparse signal representation...
In this paper, we propose a muscle gesture-computer interface (MGCI) system for a five-fingered robotic hand control employing a commercial wearable MYO gesture armband. Eight channels of surface EMG (sEMG) signals were acquired and segmented. Then four levels of Daubechies 5 Wavelet family were performed to analyze the EMG signal. Totally 72 features were extracted from the EMG raw data for 16 hand...
With the development of aging society, the number of hemiplegia patients grows rapidly and over 75% of survivors suffering hemiplegia need rehabilitation training. To assist therapists, series of rehabilitation training robots were carried out. However, most of current researches are only focusing on function training. They ignore the importance of neurological rehabilitation in early phrase of hemiplegia...
There has been significant research aimed at leveraging programmable robotic devices to provide haptic assistance or augmentation to a human user so that new motor skills can be trained efficiently and retained long after training has concluded. The success of these approaches has been varied, and retention of skill is typically not significantly better for groups exposed to these controllers during...
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