International audienceWith a recent rise in the availability of affordable head mounted gear sets, various sensory stimulations (e.g., visual, auditory and haptics) are integrated to provide seamlessly embodied virtual experience in areas such as education, entertainment, therapy and social interactions. Currently, there is an abundance of available toolkits and application programming interfaces (APIs) for generating the visual and audio content. However, such richness in hardware technologies and software tools is missing in designing haptic experiences. Current solutions to integrate haptic effects are limited due to: i) a user's rigid adaptation to new hardware and software technologies, ii) limited scalability of the existing tools to incorporate haptic hardware and applications, iii) inflexible authoring capabilities, iv) missing infrastructure for storing, playback and distribution, and v) and unreliable hardware for long term usage

Recently, various dimensionality reduction approaches have been proposed as alternatives to PCA or LDA. These improved approaches do not rely on a linearity assumption, and are hence capable of discovering more complex embeddings within different regions of the data sets. Despite their success on artificial datasets, it is not straightforward to predict which technique is the most appropriate for a given real dataset. In this paper, we empirically evaluate recent techniques on two real audio use cases: musical instrument loops used in music production and sound effects used in sound editing. ISOMAP and t-SNE are being compared to PCA in a visualization problem, where we end up with a two-dimensional view. Various evaluation measures are used: classification performance, as well as trustworthiness/continuity assessing the preservation of neighborhoods. Although PCA and ISOMAP can yield good continuity performance even locally (samples in the original space remain close-by in the low-dimensional one), they fail to preserve the structure of the data well enough to ensure that distinct subgroups remain separate in the visualization. We show that t-SNE presents the best performance, and can even be beneficial as a pre-processing stage for improving classification when the amount of labeled data is low.

International audienceWe propose InspectorWidget, an opensource application to track and analyze users' behaviors in interactive software. The key contributions of our application are: 1) it works with closed applications that do not provide source code nor scripting capabilities; 2) it covers the whole pipeline of software analysis from logging input events to visual statistics through browsing and programmable annotation; 3) it allows post-recording logging; and 4) it does not require programming skills. To achieve this, InspectorWidget combines low-level event logging (e.g. mouse and keyboard events) and high-level screen features (e.g. interface widgets) captured though computer vision techniques. InspectorWidget benefits end users, usability experts and HCI researchers

Physical controls are fabricated through complicated assembly of parts requiring expensive machinery and are prone to mechanical wear. One solution is to embed controls directly in interactive surfaces, but the proprioceptive part of gestural interaction that makes physical controls discoverable and usable solely by hand gestures is lost and has to be compensated, by vibrotactile feedback for instance. Vibrotactile actuators face the same aforementioned issues as for physical controls. We propose printed vibrotactile actuators and sensors. They are printed on plastic sheets, with piezoelectric ink for actuation, and with silver ink for conductive elements, such as wires and capacitive sensors. These printed actuators and sensors make it possible to design vibrotactile widgets on curved surfaces, without complicated mechanical assembly.

This paper presents the MappEMG pipeline. The goal of this pipeline is to augment the traditional classical concert experience by giving listeners access, through the sense of touch, to an intimate and non-visible dimension of the musicians’ bodily experience while performing. The live-stream pipeline produces vibrations based on muscle activity captured through surface electromyography (EMG). Therefore, MappEMG allows the audience to experience the performer’s muscle effort, an essential component of music performance which is typically unavailable to direct visual observation. The paper is divided in four sections. First, we overview related works on EMG, music performance, and vibrotactile feedback. We then present conceptual and methodological issues of capturing musicians’ muscle effort related to their expressive intentions. We further explain the different components of the live-stream data pipeline: a python software named Biosiglive for data acquisition and processing, a Max/MSP patch for data post-processing and mapping, and a mobile application named hAPPtiks for real-time control of smartphones’ vibration. Finally, we address the application of the pipeline in an actual music performance. Thanks to their modular structure, the tools presented could be used in different creative and biomedical contexts involving gestural control of haptic stimuli.