Editorial: Advances in haptic feedback for neurorobotics applications

摘要

In a similar context, Luis, Marko et al -from University Medical Center Göttingen, Hamburg University of Applied Sciences, Medical School Hannover, DE -investigated vibrotactile sensation of the arm-shoulder region in Vibrotactile mapping of the upper extremity: Absolute perceived intensity is location-dependent; perception of relative changes is not, providing an overview of the sensory bandwidth that can be achieved with vibrotactile stimulation of the human arm Teng, Zhang et al -from Xi'an Jiaotong University, CN -looked at human-robot interaction from a further perspective and they presented a Personalized Speed Adaptation (PSA) method where electroencephalogram and electro-oculogram capture operator's mental state, and then regulate robot's speed according to this mental state. To the best of our knowledge, this paper is the first Feasibility study of personalized speed adaptation method based on mental state for teleoperated robots Focusing on Brain Computer and Brain Machine Interfaces (BCI, BMI), Rui, Di et al -from Xi'an University of Technology, Xi'an People's Hospital, CN and King Mongkut's University of Technology, TH -presented A novel EEG decoding method for a facial-expression-based BCI system using the combined convolutional neural network and genetic algorithm where they showed that their Facial-Expression-based BCI (FE-BCI) system provides superior performance vs traditional methodsThe Institute for Human Centered Engineering and Balgrist University Hospital, CH -namely Rafael, Tobia et al -proposed a FeetBack-Redirecting touch sensation from a prosthetic hand to the human foot where a vibrotactile insole was set up in order to vibrate according to the sensed force of prosthetic fingers while subjects manipulate fragile and heavy objects, providing a novel approach vs tactile sensation in myoelectric prosthetics