The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
O ajuste de um determinado parâmetro durante a execução de uma tarefa de trajetória, como desenhar ou gesticular, é uma manipulação comum na interação baseada em caneta. Como as informações da ponta da caneta estão confinadas aos dados das coordenadas xy, esse ajuste de parâmetro simultâneo não é facilmente realizado em dispositivos que usam apenas a ponta da caneta. Este artigo investiga comparativamente o desempenho das modalidades de entrada de caneta inerentes (Pressão, Inclinar, Azimute e rolando) e Pressionamento de tecla com a mão não preferencial usada para manipulação de parâmetros de precisão durante ações de deslizamento da caneta. Elaboramos aqui nossa estrutura de projeto experimental e conduzimos experimentações para avaliar o efeito das cinco técnicas. Os resultados mostram que Pressão permitiu o desempenho mais rápido junto com a menor taxa de erro, enquanto Azimute apresentou o pior desempenho. Inclinar mostrou um desempenho ligeiramente mais rápido e alcançou uma taxa de erro menor do que rolando. Porém, rolando alcançou o efeito de aprendizagem mais significativo em Tempo de seleção e foi favorecido Inclinar em avaliações subjetivas. Nossos resultados experimentais proporcionam uma compreensão geral do desempenho das modalidades inerentes de entrada da caneta no decorrer de uma tarefa de trajetória em HCI (interação humano-computador).
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Yizhong XIN, Xiangshi REN, "A Study of Inherent Pen Input Modalities for Precision Parameter Manipulations during Trajectory Tasks" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 12, pp. 2454-2461, December 2009, doi: 10.1587/transinf.E92.D.2454.
Abstract: Adjustment of a certain parameter in the course of performing a trajectory task such as drawing or gesturing is a common manipulation in pen-based interaction. Since pen tip information is confined to x-y coordinate data, such concurrent parameter adjustment is not easily accomplished in devices using only a pen tip. This paper comparatively investigates the performance of inherent pen input modalities (Pressure, Tilt, Azimuth, and Rolling) and Key Pressing with the non-preferred hand used for precision parameter manipulation during pen sliding actions. We elaborate our experimental design framework here and conduct experimentation to evaluate the effect of the five techniques. Results show that Pressure enabled the fastest performance along with the lowest error rate, while Azimuth exhibited the worst performance. Tilt showed slightly faster performance and achieved a lower error rate than Rolling. However, Rolling achieved the most significant learning effect on Selection Time and was favored over Tilt in subjective evaluations. Our experimental results afford a general understanding of the performance of inherent pen input modalities in the course of a trajectory task in HCI (human computer interaction).
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.2454/_p
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@ARTICLE{e92-d_12_2454,
author={Yizhong XIN, Xiangshi REN, },
journal={IEICE TRANSACTIONS on Information},
title={A Study of Inherent Pen Input Modalities for Precision Parameter Manipulations during Trajectory Tasks},
year={2009},
volume={E92-D},
number={12},
pages={2454-2461},
abstract={Adjustment of a certain parameter in the course of performing a trajectory task such as drawing or gesturing is a common manipulation in pen-based interaction. Since pen tip information is confined to x-y coordinate data, such concurrent parameter adjustment is not easily accomplished in devices using only a pen tip. This paper comparatively investigates the performance of inherent pen input modalities (Pressure, Tilt, Azimuth, and Rolling) and Key Pressing with the non-preferred hand used for precision parameter manipulation during pen sliding actions. We elaborate our experimental design framework here and conduct experimentation to evaluate the effect of the five techniques. Results show that Pressure enabled the fastest performance along with the lowest error rate, while Azimuth exhibited the worst performance. Tilt showed slightly faster performance and achieved a lower error rate than Rolling. However, Rolling achieved the most significant learning effect on Selection Time and was favored over Tilt in subjective evaluations. Our experimental results afford a general understanding of the performance of inherent pen input modalities in the course of a trajectory task in HCI (human computer interaction).},
keywords={},
doi={10.1587/transinf.E92.D.2454},
ISSN={1745-1361},
month={December},}
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TY - JOUR
TI - A Study of Inherent Pen Input Modalities for Precision Parameter Manipulations during Trajectory Tasks
T2 - IEICE TRANSACTIONS on Information
SP - 2454
EP - 2461
AU - Yizhong XIN
AU - Xiangshi REN
PY - 2009
DO - 10.1587/transinf.E92.D.2454
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2009
AB - Adjustment of a certain parameter in the course of performing a trajectory task such as drawing or gesturing is a common manipulation in pen-based interaction. Since pen tip information is confined to x-y coordinate data, such concurrent parameter adjustment is not easily accomplished in devices using only a pen tip. This paper comparatively investigates the performance of inherent pen input modalities (Pressure, Tilt, Azimuth, and Rolling) and Key Pressing with the non-preferred hand used for precision parameter manipulation during pen sliding actions. We elaborate our experimental design framework here and conduct experimentation to evaluate the effect of the five techniques. Results show that Pressure enabled the fastest performance along with the lowest error rate, while Azimuth exhibited the worst performance. Tilt showed slightly faster performance and achieved a lower error rate than Rolling. However, Rolling achieved the most significant learning effect on Selection Time and was favored over Tilt in subjective evaluations. Our experimental results afford a general understanding of the performance of inherent pen input modalities in the course of a trajectory task in HCI (human computer interaction).
ER -