241 research outputs found

    Sensory Motor Remapping of Space in Human-Machine Interfaces

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    Studies of adaptation to patterns of deterministic forces have revealed the ability of the motor control system to form and use predictive representations of the environment. These studies have also pointed out that adaptation to novel dynamics is aimed at preserving the trajectories of a controlled endpoint, either the hand of a subject or a transported object. We review some of these experiments and present more recent studies aimed at understanding how the motor system forms representations of the physical space in which actions take place. An extensive line of investigations in visual information processing has dealt with the issue of how the Euclidean properties of space are recovered from visual signals that do not appear to possess these properties. The same question is addressed here in the context of motor behavior and motor learning by observing how people remap hand gestures and body motions that control the state of an external device. We present some theoretical considerations and experimental evidence about the ability of the nervous system to create novel patterns of coordination that are consistent with the representation of extrapersonal space. We also discuss the perspective of endowing human–machine interfaces with learning algorithms that, combined with human learning, may facilitate the control of powered wheelchairs and other assistive devices

    In-situ crack and keyhole pore detection in laser directed energy deposition through acoustic signal and deep learning

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    Cracks and keyhole pores are detrimental defects in alloys produced by laser directed energy deposition (LDED). Laser-material interaction sound may hold information about underlying complex physical events such as crack propagation and pores formation. However, due to the noisy environment and intricate signal content, acoustic-based monitoring in LDED has received little attention. This paper proposes a novel acoustic-based in-situ defect detection strategy in LDED. The key contribution of this study is to develop an in-situ acoustic signal denoising, feature extraction, and sound classification pipeline that incorporates convolutional neural networks (CNN) for online defect prediction. Microscope images are used to identify locations of the cracks and keyhole pores within a part. The defect locations are spatiotemporally registered with acoustic signal. Various acoustic features corresponding to defect-free regions, cracks, and keyhole pores are extracted and analysed in time-domain, frequency-domain, and time-frequency representations. The CNN model is trained to predict defect occurrences using the Mel-Frequency Cepstral Coefficients (MFCCs) of the lasermaterial interaction sound. The CNN model is compared to various classic machine learning models trained on the denoised acoustic dataset and raw acoustic dataset. The validation results shows that the CNN model trained on the denoised dataset outperforms others with the highest overall accuracy (89%), keyhole pore prediction accuracy (93%), and AUC-ROC score (98%). Furthermore, the trained CNN model can be deployed into an in-house developed software platform for online quality monitoring. The proposed strategy is the first study to use acoustic signals with deep learning for insitu defect detection in LDED process.Comment: 36 Pages, 16 Figures, accepted at journal Additive Manufacturin

    Musicians and Performance Related Injuries to the Hand

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    Musicians spend a great amount of energy and time preparing for auditions, competitions, performances, and recitals. The process of developing techniques and learning musical pieces requires practice sessions filled with long hours of repeating musical passages and awkward upper extremity positions. Performance related injuries often result from these conditions. Injuries include joint disorders, musculotendinous disorders, muscle cramps and pain disorders, neurological disorders, and focal dystonia or occupational palsy disorders. Pain, numbness, tingling, muscle cramping, and motor dysfunctions are associated symptoms. If symptoms are ignored and intense performance is continued, the musician can experience tissue damage and permanent loss of function. Research has indicated that the hand, the wrist, and the fingers are the areas of the body where performance related injuries are most frequent. This literature review will focus on the common hand injuries experienced by musicians. Common types of injuries, evaluation procedures, treatments, and prevention techniques specific to the needs of musicians will be discussed

    Comparison of in-sight and handheld navigation devices toward supporting industry 4.0 supply chains: First and last mile deliveries at the human level

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    Last (and First) mile deliveries are an increasingly important and costly component of supply chains especially those that require transport within city centres. With reduction in anticipated manufacturing and delivery timescales, logistics personnel are expected to identify the correct location (accurately) and supply the goods in appropriate condition (safe delivery). Moving towards more environmentally sustainable supply chains, the last/first mile of deliveries may be completed by a cyclist courier which could result in significant reductions in congestion and emissions in cities. In addition, the last metres of an increasing number of deliveries are completed on foot i.e. as a pedestrian. Although research into new technologies to support enhanced navigation capabilities is ongoing, the focus to date has been on technical implementations with limited studies addressing how information is perceived and actioned by a human courier. In the research reported in this paper a comparison study has been conducted with 24 participants evaluating two examples of state-of-the-art navigation aids to support accurate (right time and place) and safe (right condition) navigation. Participants completed 4 navigation tasks, 2 whilst cycling and 2 whilst walking. The navigation devices under investigation were a handheld display presenting a map and instructions and an in-sight monocular display presenting text and arrow instructions. Navigation was conducted in a real-world environment in which eye movements and device interaction were recorded using Tobii-Pro 2 eye tracking glasses. The results indicate that the handheld device provided better support for accurate navigation (right time and place), with longer but less frequent gaze interactions and higher perceived usability. The in-sight display supported improved situation awareness with a greater number of hazards acknowledged. The benefits and drawbacks of each device and use of visual navigation support tools are discussed

    Promoting Health Across the Lifespan

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    This document contains health lesson plans on a variety of topics. The content is intended for use by health educators, and the target audience of the materials varies from elementary aged children to older adults. Each lesson plan has a topic overview, time and format information, Healthy People 2020 Objectives, National Health Education Standards information, learning objectives, key concepts and terms, materials needed, and teaching steps. This material was developed by Plymouth State University students as a part of their coursework for Promoting Health Across the Lifespan, in fall 2017 with Dr. Barbara McCahan. Materials are Licensed under the Creative Commons Attribution 4.0 license except where otherwise indicated

    The Hilltop 10-16-2001

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    https://dh.howard.edu/hilltop_0010/1036/thumbnail.jp

    Fatigue-Aware gaming system for motor rehabilitation using biocybernetic loops.

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    Esta tesis tiene como objetivo proponer una terapia de rehabilitación complementaria basada en paradigmas de interacción humano-computadora (HCI) que exploran i) Técnicas de rehabilitación virtual, integrando tecnologías de realidad virtual (VR) sofisticadas y (hoy en día) accesibles, ii) sensores fisiológicos de bajo costo, a saber, electromiografía de superficie (sEMG) y iii)sistema inteligente, a través de adaptación biocibernética, para proporcionar una nueva técnica de rehabilitación virtual..
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