3,842 research outputs found
Human-Machine Interface for Tele-Robotic Operation: Mapping of Tongue Movements Based on Aural Flow Monitoring
2004 IEEE International Conference on Intelligent Robots and Systems (IROS), October, 2004 (Awarded “Best Paper in Conference”
Portable Tongue-Supported Human Computer Interaction System Design and Implementation
Tongue supported human-computer interaction (TSHCI) systems can help critically ill patients interact with both computers and people. These systems can be particularly useful for patients suffering injuries above C7 on their spinal vertebrae. Despite recent successes in their application, several limitations restrict performance of existing TSHCI systems and discourage their use in real life situations. This paper proposes a low-cost, less-intrusive, portable and easy to use design for implementing a TSHCI system. Two applications of the proposed system are reported. Design considerations and performance of the proposed system are also presented
Silent Speech Interfaces for Speech Restoration: A Review
This work was supported in part by the Agencia Estatal de Investigacion (AEI) under Grant PID2019-108040RB-C22/AEI/10.13039/501100011033. The work of Jose A. Gonzalez-Lopez was supported in part by the Spanish Ministry of Science, Innovation and Universities under Juan de la Cierva-Incorporation Fellowship (IJCI-2017-32926).This review summarises the status of silent speech interface (SSI) research. SSIs rely on non-acoustic biosignals generated by the human body during speech production to enable communication whenever normal verbal communication is not possible or not desirable. In this review, we focus on the first case and present latest SSI research aimed at providing new alternative and augmentative communication methods for persons with severe speech disorders. SSIs can employ a variety of biosignals to enable silent communication, such as electrophysiological recordings of neural activity, electromyographic (EMG) recordings of vocal tract movements or the direct tracking of articulator movements using imaging techniques. Depending on the disorder, some sensing techniques may be better suited than others to capture speech-related information. For instance, EMG and imaging techniques are well suited for laryngectomised patients, whose vocal tract remains almost intact but are unable to speak after the removal of the vocal folds, but fail for severely paralysed individuals. From the biosignals, SSIs decode the intended message, using automatic speech recognition or speech synthesis algorithms. Despite considerable advances in recent years, most present-day SSIs have only been validated in laboratory settings for healthy users. Thus, as discussed in this paper, a number of challenges remain to be addressed in future research before SSIs can be promoted to real-world applications. If these issues can be addressed successfully, future SSIs will improve the lives of persons with severe speech impairments by restoring their communication capabilities.Agencia Estatal de Investigacion (AEI)
PID2019-108040RB-C22/AEI/10.13039/501100011033Spanish Ministry of Science, Innovation and Universities under Juan de la Cierva-Incorporation Fellowship
IJCI-2017-3292
A Mimetic Strategy to Engage Voluntary Physical Activity In Interactive Entertainment
We describe the design and implementation of a vision based interactive
entertainment system that makes use of both involuntary and voluntary control
paradigms. Unintentional input to the system from a potential viewer is used to
drive attention-getting output and encourage the transition to voluntary
interactive behaviour. The iMime system consists of a character animation
engine based on the interaction metaphor of a mime performer that simulates
non-verbal communication strategies, without spoken dialogue, to capture and
hold the attention of a viewer. The system was developed in the context of a
project studying care of dementia sufferers. Care for a dementia sufferer can
place unreasonable demands on the time and attentional resources of their
caregivers or family members. Our study contributes to the eventual development
of a system aimed at providing relief to dementia caregivers, while at the same
time serving as a source of pleasant interactive entertainment for viewers. The
work reported here is also aimed at a more general study of the design of
interactive entertainment systems involving a mixture of voluntary and
involuntary control.Comment: 6 pages, 7 figures, ECAG08 worksho
Interaction Methods for Smart Glasses : A Survey
Since the launch of Google Glass in 2014, smart glasses have mainly been designed to support micro-interactions. The ultimate goal for them to become an augmented reality interface has not yet been attained due to an encumbrance of controls. Augmented reality involves superimposing interactive computer graphics images onto physical objects in the real world. This survey reviews current research issues in the area of human-computer interaction for smart glasses. The survey first studies the smart glasses available in the market and afterwards investigates the interaction methods proposed in the wide body of literature. The interaction methods can be classified into hand-held, touch, and touchless input. This paper mainly focuses on the touch and touchless input. Touch input can be further divided into on-device and on-body, while touchless input can be classified into hands-free and freehand. Next, we summarize the existing research efforts and trends, in which touch and touchless input are evaluated by a total of eight interaction goals. Finally, we discuss several key design challenges and the possibility of multi-modal input for smart glasses.Peer reviewe
Prototyping Digital Tongue Diagnosis System on Raspberry Pi
Tongue inspection is a complementary diagnosis method that widely used in Traditional Chinese Medicine (TCM) by inspecting the tongue body constitution to decide the physiological and pathological functions of the human body. Since tongue manifestation is done by practitioner’s observation using naked eye, many limitations can affect the diagnosis result including environment condition and experiences of the practitioner. Lately, tongue diagnosis has been widely studied in order to solve these limitations via digital system. However, most of recent digital system are bulky and not equipped with intelligent diagnosis system that can finally predict the health status of the patient. In this research, digital tongue diagnosis system that uses intelligent diagnosis consisted of image segmentation analysis, tongue coating recognition analysis, and tongue color classification has been embedded on Raspberry Pi. Tongue segmentation implements Hue, Saturation and Value (HSV) color space with Brightness Conformable Multiplier (BCM) for adaptive brightness filtering to recognized tongue body accurately while eliminating perioral area. Tongue Coating Recognition uses threshold method to detect tongue coating and eliminate the unwanted features including shadow. Tongue color classification uses hybrid method consisted of k-means clustering and Support Vector Machine (SVM) to classify between red, light red and deep red tongue and further gave diagnosis based on color. This experiment concluded that it is feasible to embed the algorithm on Raspberry Pi to promote system portability while attaining similar accuracy for future telemedicine
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When users control the algorithms: Values expressed in practices on the twitter platform
Recent interest in ethical AI has brought a slew of values, including fairness, into conversations about technology design. Research in the area of algorithmic fairness tends to be rooted in questions of distribution that can be subject to precise formalism and technical implementation. We seek to expand this conversation to include the experiences of people subject to algorithmic classification and decision-making. By examining tweets about the “Twitter algorithm” we consider the wide range of concerns and desires Twitter users express. We find a concern with fairness (narrowly construed) is present, particularly in the ways users complain that the platform enacts a political bias against conservatives. However, we find another important category of concern, evident in attempts to exert control over the algorithm. Twitter users who seek control do so for a variety of reasons, many well justified. We argue for the need for better and clearer definitions of what constitutes legitimate and illegitimate control over algorithmic processes and to consider support for users who wish to enact their own collective choices
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