Let's read! We will often find out this sentence everywhere. When still being a kid, mom used to order us to always read, so did the teacher. Some books are fully read in a week and we need the obligation to support reading. What about now? Do you still love reading? Is reading only for you who have obligation? Absolutely not! We here offer you a new book enPDFd the perception of the visual world to read.

The Perception of the Visual World. By James J. Gibson. U.S.A.: Houghton Mifflin Company, 1950 (George Allen & Unwin, Ltd., London). Price 35s.

체험마케팅(Experiential Marketing)의 오해와 진실

Starting from human ?sense of touch,? this paper reviews the state of tactile sensing in robotics. The physiology, coding, and transferring tactile data and perceptual importance of the ?sense of touch? in humans are discussed. Following this, a number of design hints derived for robotic tactile sensing are presented. Various technologies and transduction methods used to improve the touch sense capability of robots are presented. Tactile sensing, focused to fingertips and hands until past decade or so, has now been extended to whole body, even though many issues remain open. Trend and methods to develop tactile sensing arrays for various body sites are presented. Finally, various system issues that keep tactile sensing away from widespread utility are discussed.

Tactile Sensing—From Humans to Humanoids

This chapter introduces the subject of statistical pattern recognition (SPR). It starts by considering how features are defined and emphasizes that the nearest neighbor algorithm achieves error rates comparable with those of an ideal Bayes’ classifier. The concepts of an optimal number of features, representativeness of the training data, and the need to avoid overfitting to the training data are stressed. The chapter shows that methods such as the support vector machine and artificial neural networks are subject to these same training limitations, although each has its advantages. For neural networks, the multilayer perceptron architecture and back-propagation algorithm are described. The chapter distinguishes between supervised and unsupervised learning, demonstrating the advantages of the latter and showing how methods such as clustering and principal components analysis fit into the SPR framework. The chapter also defines the receiver operating characteristic, which allows an optimum balance between false positives and false negatives to be achieved.

Statistical Pattern Recognition

It is generally accepted that augmented feedback, provided by a human expert or a technical display, effectively enhances motor learning. However, discussion of the way to most effectively provide augmented feedback has been controversial. Related studies have focused primarily on simple or artificial tasks enhanced by visual feedback. Recently, technical advances have made it possible also to investigate more complex, realistic motor tasks and to implement not only visual, but also auditory, haptic, or multimodal augmented feedback. The aim of this review is to address the potential of augmented unimodal and multimodal feedback in the framework of motor learning theories. The review addresses the reasons for the different impacts of feedback strategies within or between the visual, auditory, and haptic modalities and the challenges that need to be overcome to provide appropriate feedback in these modalities, either in isolation or in combination. Accordingly, the design criteria for successful visual, auditory, haptic, and multimodal feedback are elaborated.

/pdf/augmented-visual-auditory-haptic-and-multimodal-feedback-in-2jc0b0ky7k.pdf

Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review

Presenting waypoint navigation on a visual display is not suited for all situations. The present experiments investigate if it is feasible to present the navigation information on a tactile display. Important design issue of the display is how direction and distance information must be coded. Important usability issues are the resolution of the display and its usefulness in vibrating environments. In a pilot study with 12 pedestrians, different distance-coding schemes were compared. The schemes translated distance to vibration rhythm while the direction was translated into vibration location. The display consisted of eight tactors around the user's waist. The results show that mapping waypoint direction on the location of vibration is an effective coding scheme that requires no training, but that coding for distance does not improve performance compared to a control condition with no distance information. In Experiment 2, the usefulness of the tactile display was shown in two case studies with a helicopter and a fast boat.

Waypoint navigation with a vibrotactile waist belt

A vibrotactile display, consisting ofeight vibrating elements or tactors mounted in a driver's seat, was tested in a driving simulator. Participants drove with visual, tactile and multimodal navigation displays through a built-up area. Workload and the reaction time to navigation messages were measured for normal and high workload conditions. The results demonstrated that the tactile navigation display reduces the driver's workload compared to the visual display, particularly in the high workload group. The fastest reaction was found with the multimodal display. It was concluded that this study quantitatively supports the claims that a localised vibration or tap is an intuitive way to present direction information, and that employing the tactile channel may release other heavily loaded sensory channels, therefore potentially providing a major safety enhancement.

Vibrotactile in-vehicle navigation system

Previous studies indicate that both electroencephalogram (EEG) spectral power (in particular the alpha and theta band) and event-related potentials (ERPs) (in particular the P300) can be used as a measure of mental work or memory load. We compare their ability to estimate workload level in a well-controlled task. In addition, we combine both types of measures in a single classification model to examine whether this results in higher classification accuracy than either one alone. Participants watched a sequence of visually presented letters and indicated whether or not the current letter was the same as the one (n instances) before. Workload was varied by varying n. We developed different classification models using ERP features, frequency power features or a combination (fusion). Training and testing of the models simulated an online workload estimation situation. All our ERP, power and fusion models provide classification accuracies between 80% and 90% when distinguishing between the highest and the lowest workload condition after 2 min. For 32 out of 35 participants, classification was significantly higher than chance level after 2.5 s (or one letter) as estimated by the fusion model. Differences between the models are rather small, though the fusion model performs better than the other models when only short data segments are available for estimating workload.

https://iopscience.iop.org/article/10.1088/1741-2560/9/4/045008/pdf

Estimating workload using EEG spectral power and ERPs in the n-back task

In this study, we investigated a Brain-Computer Interface (BCI) based on EEG responses to vibro-tactile stimuli around the waist. P300 BCIs based on tactile stimuli have the advantage of not taxing the visual or auditory system and of being potentially unnoticeable to other people. A tactile BCI could be especially suitable for patients whose vision or eye movements are impaired. In Experiment 1, we investigated its feasibility and the effect of the number of equally spaced tactors. Whereas a large number of tactors is expected to enhance the P300 amplitude since the target will be less frequent, it could also negatively affect the P300 since it will be difficult to identify the target when tactor density increases. Participants were asked to attend to the vibrations of a target tactor, embedded within a stream of distracters. The number of tactors was two, four or six. We demonstrated the feasibility of a tactile P300 BCI. We did not find a difference in SWLDA classification performance between the different numbers of tactors. In a second set of experiments we reduced the stimulus onset asynchrony (SOA) by shortening the on- and/or off-time of the tactors. The SOA for an optimum performance as measured in our experiments turned out to be close to conventional SOAs of visual P300 BCIs.

/pdf/a-tactile-p300-brain-computer-interface-3tscfwlfky.pdf

A tactile P300 brain-computer interface.

While studies exist that compare different physiological variables with respect to their association with mental workload, it is still largely unclear which variables supply the best information about momentary workload of an individual and what is the benefit of combining them. We investigated workload using the n-back task, controlling for body movements and visual input. We recorded EEG, skin conductance, respiration, ECG, pupil size and eye blinks of 14 subjects. Various variables were extracted from these recordings and used as features in individually tuned classification models. Online classification was simulated by using the first part of the data as training set and the last part of the data for testing the models. The results indicate that EEG performs best, followed by eye related measures and peripheral physiology. Combining variables from different sensors did not significantly improve workload assessment over the best performing sensor alone. Best classification accuracy, a little over 90% (SD 4%), was reached for distinguishing between high and low workload on the basis of 2 minute segments of EEG and eye related variables. A similar and not significantly different performance of 86% (SD 5%) was reached using only EEG from single electrode location Pz.

/pdf/combining-and-comparing-eeg-peripheral-physiology-and-eye-1rhlam0ley.pdf

Jan B. F. van Erp

Papers

Waypoint navigation with a vibrotactile waist belt

Vibrotactile in-vehicle navigation system

Estimating workload using EEG spectral power and ERPs in the n-back task

A tactile P300 brain-computer interface.

Combining and comparing EEG, peripheral physiology and eye-related measures for the assessment of mental workload