3,869 research outputs found
Ergonomics of using a mouse or other non-keyboard input device
Ten years ago, when the Health and Safety (Display Screen Equipment) Regulations
(HSE, 1992) were drafted, the majority of computer interaction occurred with text driven
interfaces, using a keyboard. It is not surprising then that the guidance accompanying
the DSE Regulations included virtually no mention of the computer mouse or other
non-keyboard input devices (NKID).
In the intervening period, graphical user interfaces, incorporating ‘windows, icons and
pull down menus’ (WIMPS), with a heavy reliance on pointing devices such as the
mouse, have transformed user computer interaction. Accompanying this, however,
have been increasing anecdotal reports of musculoskeletal health problems affecting
NKID users.
While the performance aspects of NKID (e.g. accuracy and speed) have been the
subject of detailed research, the possible implications for user health have received
comparatively little attention. The research presented in this report was commissioned
by the Health and Safety Executive to improve understanding of the nature and extent
of NKID health problems. This investigation, together with another project examining
mobile computing (Heasman et. al., 2000), was intended to contribute to a planned
review and updating of the DSE Regulations and accompanying guidance
Modulation of Stretch Reflexes of the Finger Flexors by Sensory Feedback from the Proximal Upper Limb Poststroke
Neural coupling of proximal and distal upper limb segments may have functional implications in the recovery of hemiparesis after stroke. The goal of the present study was to investigate whether the stretch reflex response magnitude of spastic finger flexor muscles poststroke is influenced by sensory input from the shoulder and the elbow and whether reflex coupling of muscles throughout the upper limb is altered in spastic stroke survivors. Through imposed extension of the metacarpophalangeal (MCP) joints, stretch of the relaxed finger flexors of the four fingers was imposed in 10 relaxed stroke subjects under different conditions of proximal sensory input, namely static arm posture (3 different shoulder/elbow postures) and electrical stimulation (surface stimulation of biceps brachii or triceps brachii, or none). Fast (300°/s) imposed stretch elicited stretch reflex flexion torque at the MCP joints and reflex electromyographic (EMG) activity in flexor digitorum superficialis. Both measures were greatest in an arm posture of 90° of elbow flexion and neutral shoulder position. Biceps stimulation resulted in greater MCP stretch reflex flexion torque. Fast imposed stretch also elicited reflex EMG activity in nonstretched heteronymous upper limb muscles, both proximal and distal. These results suggest that in the spastic hemiparetic upper limb poststroke, sensorimotor coupling of proximal and distal upper limb segments is involved in both the increased stretch reflex response of the finger flexors and an increased reflex coupling of heteronymous muscles. Both phenomena may be mediated through changes poststroke in the spinal reflex circuits and/or in the descending influence of supraspinal pathways
Autonomous space processor for orbital debris
This work continues to develop advanced designs toward the ultimate goal of a GETAWAY SPECIAL to demonstrate economical removal of orbital debris utilizing local resources in orbit. The fundamental technical feasibility was demonstrated last year through theoretical calculations, quantitative computer animation, a solar focal point cutter, a robotic arm design and a subscale model. During this reporting period, several improvements are made in the solar cutter, such as auto track capabilities, better quality reflectors and a more versatile framework. The major advance has been in the design, fabrication and working demonstration of a ROBOTIC ARM that has several degrees of freedom. The functions were specifically tailored for the orbital debris handling. These advances are discussed here. Also a small fraction of the resources were allocated towards research in flame augmentation in SCRAMJETS for the NASP. Here, the fundamental advance was the attainment of Mach numbers up to 0.6 in the flame zone and a vastly improved injection system; the current work is expected to achieve supersonic combustion in the laboratory and an advanced monitoring system
Sistema de miografia óptica para reconhecimento de gestos e posturas de mão
Orientador: Éric FujiwaraDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia MecânicaResumo: Nesse projeto, demonstrou-se um sistema de miografia óptica como uma alternativa promissora para monitorar as posturas da mão e os gestos do usuário. Essa técnica se fundamenta em acompanhar as atividades musculares responsáveis pelos movimentos da mão com uma câmera externa, relacionando a distorção visual verificada no antebraço com a contração e o relaxamento necessários para dada postura. Três configurações de sensores foram propostas, estudadas e avaliadas. A primeira propôs monitorar a atividade muscular analisando a variação da frequência espacial de uma textura de listras uniformes impressa sobre a pele, enquanto que a segunda se caracteriza pela contagem de pixels de pele visível dentro da região de interesse. Ambas as configurações se mostraram inviáveis pela baixa robustez e alta demanda por condições experimentais controladas. Por fim, a terceira recupera o estado da mão acompanhando o deslocamento de uma série de marcadores coloridos distribuídos ao longo do antebraço. Com um webcam de 24 fps e 640 × 480 pixels, essa última configuração foi validada para oito posturas distintas, explorando principalmente a flexão e extensão dos dedos e do polegar, além da adução e abdução do último. Os dados experimentais, adquiridos off-line, são submetidos a uma rotina de processamento de imagens para extrair a informação espacial e de cor dos marcadores em cada quadro, dados esses utilizados para rastrear os mesmos marcadores ao longo de todos os quadros. Para reduzir a influência das vibrações naturais e inerentes ao corpo humano, um sistema de referencial local é ainda adotado dentro da própria região de interesse. Finalmente, os dados quadro a quadro com o ground truth são alimentados a uma rede neural artificial sequencial, responsável pela calibração supervisionada do sensor e posterior classificação das posturas. O desempenho do sistema para a classificação das oito posturas foi avaliado com base na validação cruzada com 10-folds, com a câmera monitorando o antebraço pela superfície interna ou externa. O sensor apresentou uma precisão de ?92.4% e exatidão de ?97.9% para o primeiro caso, e uma precisão de ?75.1% e exatidão de ?92.5% para o segundo, sendo comparável a outras técnicas de miografia, demonstrando a viabilidade do projeto e abrindo perspectivas para aplicações em interfaces humano-robôAbstract: In this work, an optical myography system is demonstrated as a promising alternative to monitor hand posture and gestures of the user. This technique is based on accompanying muscular activities responsible for hand motion with an external camera, and relating the visual deformation observed on the forearm to the muscular contractions/relaxations for a given posture. Three sensor designs were proposed, studied and evaluated. The first one intended to monitor muscular activity by analyzing the spatial frequency variation of a uniformly distributed stripe pattern stamped on the skin, whereas the second one is characterized by reckoning visible skin pixels inside the region of interest. Both designs are impracticable due to their low robustness and high demand for controlled experimental conditions. At last, the third design retrieves hand configuration by tracking visually the displacements of a series of color markers distributed over the forearm. With a webcam of 24 fps and 640 × 480 pixels, this design was validated for eight different postures, exploring fingers and thumb flexion/extension, plus thumb adduction/abduction. The experimental data are acquired offline and, then, submitted to an image processing routine to extract color and spatial information of the markers in each frame; the extracted data is subsequently used to track the same markers along all frames. To reduce the influence of human body natural and inherent vibrations, a local reference frame is yet adopted in the region of interest. Finally, the frame by frame data, along with the ground truth posture, are fed into a sequential artificial neural network, responsible for sensor supervised calibration and subsequent posture classification. The system performance was evaluated in terms of eight postures classification via 10-fold cross-validation, with the camera monitoring either the underside or the back of the forearm. The sensor presented a ?92.4% precision and ?97.9% accuracy for the former, and a ?75.1% precision and ?92.5% accuracy for the latter, being thus comparable to other myographic techniques; it also demonstrated that the project is feasible and offers prospects for human-robot interaction applicationsMestradoEngenharia MecanicaMestre em Engenharia Mecânica33003017CAPE
Hand Neuro-Motor Characterization and Motor Intention Decoding in Duchenne Muscular Dystrophy
Improving the Performance of Dynamic Electromyogram-to-Force Models for the Hand-Wrist and Multiple Fingers
Relating surface electromyogram (EMG) activity to force/torque models is used in many areas including: prosthesis control systems, to regulate direction and speed of movement in reaching and matching tasks; clinical biomechanics, to assess muscle deficiency and effort levels; and ergonomics analysis, to assess risk of work-related injury such as back pain, fatigue and skill tests. This thesis work concentrated on improving the performance of dynamic EMG-to-force models for the hand-wrist and multiple fingers. My contributions include: 1) rapid calibration of dynamic hand-wrist EMG-force models using a minimum number of electrodes, 2) efficiently training two degree of freedom (DoF) hand-wrist EMG-force models, and 3) estimating individual and combined fingertip forces from forearm EMG during constant-pose, force-varying tasks. My calibration approach for hand-wrist EMG-force models optimized three main factors for 1-DoF and 2-DoF tasks: training duration (14, 22, 30, 38, 44, 52, 60, 68, 76 s), number of electrodes (2 through 16), and model forms (subject-specific, DoF-specific, universal). The results show that training duration can be reduced from historical 76 s to 40–60 s without statistically affecting the average error for both 1-DoF and 2-DoF tasks. Reducing the number of electrodes depended on the number of DoFs. One-DoF models can be reduced to 2 electrodes with average test error range of 8.3–9.2% maximum voluntary contraction (MVC), depending on the DoF (e.g., flexion-extension, radial-ulnar deviation, pronation-supination, open-close). Additionally, 2-DoF models can be reduced to 6 electrodes with average error of 7.17–9.21 %MVC. Subject-specific models had the lowest error for 1-DoF tasks while DoF-specific and universal were the lowest for 2-DoF tasks. In the EMG-finger project, we studied independent contraction of one, two, three or four fingers (thumb excluded), as well as contraction of four fingers in unison. Using regression, we found that a pseudo-inverse tolerance (ratio of largest to smallest singular value) of 0.01 was optimal. Lower values produced erratic models and higher values produced models with higher errors. EMG-force errors using one finger ranged from 2.5–3.8 %MVC, using the optimal pseudoinverse tolerance. With additional fingers (two, three or four), the average error ranged from 5–8 %MVC. When four fingers contracted in unison, the average error was 4.3 %MVC. Additionally, I participated in two team projects—EMG-force dynamic models about the elbow and relating forearm muscle EMG to finger force during slowly force varying contractions. This work is also described herein
Int J Hum Comput Stud
The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input.T42 OH008429/OH/NIOSH CDC HHS/United States2016-10-01T00:00:00Z26028955PMC444761
Is movement better? Comparing sedentary and motion-based game controls for older adults
Providing cognitive and physical stimulation for older adults is critical for their well-being. Video games offer the opportunity of engaging seniors, and research has shown a variety of positive effects of motion-based video games for older adults. However, little is known about the suitability of motion-based game controls for older adults and how their use is affected by age-related changes. In this paper, we present a study evaluating sedentary and motion-based game controls with a focus on differences between younger and older adults. Our results show that older adults can apply motion-based game controls efficiently, and that they enjoy motion-based interaction. We present design implications based on our study, and demonstrate how our findings can be applied both to motion-based game design and to general interaction design for older adults. Copyright held by authors
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