29,453 research outputs found

    Sound Design for a System of 1000 Distributed Independent Audio-Visual Devices

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    This paper describes the sound design for Bloom, a light and sound installation made up of 1000 distributed independent audio-visual pixel devices, each with RGB LEDs, Wifi, Accelerometer, GPS sensor, and sound hardware. These types of systems have been explored previously, but only a few systems have exceeded 30-50 devices and very few have included sound capability, and therefore the sound design possibilities for large systems of distributed audio devices are not yet well understood. In this article we describe the hardware and software implementation of sound synthesis for this system, and the implications for design of media for this context

    Sound design for a system of 1000 distributed independent audio-visual devices

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    This paper describes the sound design for Bloom, a light and sound installation made up of 1000 distributed independent audio-visual pixel devices, each with RGB LEDs, Wifi, Accelerometer, GPS sensor, and sound hardware. These types of systems have been explored previously, but only a few systems have exceeded 30-50 devices and very few have included sound capability, and therefore the sound design possibilities for large systems of distributed audio devices are not well understood. In this article we describe the hardware and software implementation of sound synthesis for this system, and the implications for design of media for this context

    Tactons: structured tactile messages for non-visual information display

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    Tactile displays are now becoming available in a form that can be easily used in a user interface. This paper describes a new form of tactile output. Tactons, or tactile icons, are structured, abstract messages that can be used to communicate messages non-visually. A range of different parameters can be used for Tacton construction including: frequency, amplitude and duration of a tactile pulse, plus other parameters such as rhythm and location. Tactons have the potential to improve interaction in a range of different areas, particularly where the visual display is overloaded, limited in size or not available, such as interfaces for blind people or in mobile and wearable devices. This paper describes Tactons, the parameters used to construct them and some possible ways to design them. Examples of where Tactons might prove useful in user interfaces are given

    Sonification of guidance data during road crossing for people with visual impairments or blindness

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    In the last years several solutions were proposed to support people with visual impairments or blindness during road crossing. These solutions focus on computer vision techniques for recognizing pedestrian crosswalks and computing their relative position from the user. Instead, this contribution addresses a different problem; the design of an auditory interface that can effectively guide the user during road crossing. Two original auditory guiding modes based on data sonification are presented and compared with a guiding mode based on speech messages. Experimental evaluation shows that there is no guiding mode that is best suited for all test subjects. The average time to align and cross is not significantly different among the three guiding modes, and test subjects distribute their preferences for the best guiding mode almost uniformly among the three solutions. From the experiments it also emerges that higher effort is necessary for decoding the sonified instructions if compared to the speech instructions, and that test subjects require frequent `hints' (in the form of speech messages). Despite this, more than 2/3 of test subjects prefer one of the two guiding modes based on sonification. There are two main reasons for this: firstly, with speech messages it is harder to hear the sound of the environment, and secondly sonified messages convey information about the "quantity" of the expected movement

    To “Sketch-a-Scratch”

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    A surface can be harsh and raspy, or smooth and silky, and everything in between. We are used to sense these features with our fingertips as well as with our eyes and ears: the exploration of a surface is a multisensory experience. Tools, too, are often employed in the interaction with surfaces, since they augment our manipulation capabilities. “Sketch-a-Scratch” is a tool for the multisensory exploration and sketching of surface textures. The user’s actions drive a physical sound model of real materials’ response to interactions such as scraping, rubbing or rolling. Moreover, different input signals can be converted into 2D visual surface profiles, thus enabling to experience them visually, aurally and haptically

    Virtual Reality Games for Motor Rehabilitation

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    This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

    Crowd-ML: A Privacy-Preserving Learning Framework for a Crowd of Smart Devices

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    Smart devices with built-in sensors, computational capabilities, and network connectivity have become increasingly pervasive. The crowds of smart devices offer opportunities to collectively sense and perform computing tasks in an unprecedented scale. This paper presents Crowd-ML, a privacy-preserving machine learning framework for a crowd of smart devices, which can solve a wide range of learning problems for crowdsensing data with differential privacy guarantees. Crowd-ML endows a crowdsensing system with an ability to learn classifiers or predictors online from crowdsensing data privately with minimal computational overheads on devices and servers, suitable for a practical and large-scale employment of the framework. We analyze the performance and the scalability of Crowd-ML, and implement the system with off-the-shelf smartphones as a proof of concept. We demonstrate the advantages of Crowd-ML with real and simulated experiments under various conditions
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