Intelligent Sensory Modality Selection for Electronic Supportive Devices

Kyle Kotowick, J. Shah
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引用次数: 3

Abstract

Humans operating in stressful environments, such as in military or emergency first-responder roles, are subject to high sensory input loads and must often switch their attention between different modalities. Conventional supportive devices that assist users in such situations typically provide information using a single, static sensory modality; however, this carries the risk of overload when the modalities for the primary task and the supportive device overlap. Effective feedback modality selection is essential in order to avoid such a risk. One potential method for accomplishing this is to intelligently select the supportive device's feedback modality based on the user's environment and given task; however, this may result in delayed or lost information due to the performance cost resulting from switching attention from one modality to another. This paper describes the design and results of a human-participant study designed to evaluate the benefits and risks of various intelligent modality-selection strategies. Our findings suggest complex interactions between strategies, sensory input load levels and feedback modalities, with numerous significant effects across many different performance metrics.
电子辅助设备的智能感官模式选择
在压力环境中工作的人,例如在军事或紧急第一响应者的角色中,受到高感官输入负荷的影响,必须经常在不同的模式之间切换他们的注意力。在这种情况下帮助用户的传统支持装置通常使用单一的静态感官模式提供信息;然而,当主要任务和辅助设备的模式重叠时,这有过载的风险。为了避免这种风险,有效的反馈模式选择是必不可少的。实现这一目标的一种潜在方法是基于用户的环境和给定的任务智能地选择支持设备的反馈模式;然而,由于将注意力从一种模式切换到另一种模式所造成的性能成本,这可能导致信息延迟或丢失。本文描述了一项人类参与研究的设计和结果,该研究旨在评估各种智能模式选择策略的收益和风险。我们的研究结果表明,策略、感官输入负荷水平和反馈方式之间存在复杂的相互作用,在许多不同的绩效指标中具有许多显著的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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