An investigation into the effectiveness of using acoustic touch to assist people who are blind

In this work, we explored the potential of a technique known as \"acoustic touch\" to assist people who are blind in finding objects. This technique is an auditory sensory augmentation paradigm that uses smart glasses to sonify objects entering the device's field of view. We developed a wearable Foveated Audio Device (FAD) to study the efficacy and usability of using acoustic touch to search, memorise, and reach items. The study involved 14 participants, 7 blind/low vision and 7 sighted blindfolded participants. We compared the wearable device to two idealised conditions, a verbal clock face description and a sequential audio presentation through external speakers. We found that the wearable device can effectively aid the recognition and reaching of an object. We also observed that the device does not significantly increase the user's cognitive workload. These promising results suggest that acoustic touch can provide a wearable and effective method of sensory augmentation., The datasets were collected at UTS Techlab. All files are in CSV format. Each row represents a participant's data, and each column represents the data category. The label B means the participant is within the blind/low vision group. The label S means the participant is within the sighted w/ blindfold group. I've attached an example figure for the result from the data., The data files were processed using Matlab R2020a. The formatted data files can be imported into Excel, SPSS, and other software.

本研究探索了被称为"声学触觉（acoustic touch）"的技术在辅助视障人群寻找物品方面的应用潜力。该技术是一种听觉感官增强范式，通过智能眼镜将进入设备视野内的物体转化为可听化音频信号。我们开发了一款可穿戴式凹点音频设备（Foveated Audio Device, FAD），以探究声学触觉应用于物品搜索、记忆与抓取任务的效能与易用性。本研究共招募14名受试者，其中7名为盲/低视力人群，7名为蒙眼视力正常人群。我们将该可穿戴设备与两种理想化对照条件进行了对比：一是口头时钟面描述，二是通过外置扬声器呈现的序列音频。研究结果表明，该可穿戴设备可有效辅助受试者完成物体识别与抓取任务；同时未显著增加使用者的认知负荷。上述积极结果显示，声学触觉可作为一种可穿戴且高效的感官增强手段。
本数据集采集于UTS Techlab，所有文件均采用CSV格式。每一行代表一名受试者的实验数据，每一列代表一类数据指标。标签B代表受试者属于盲/低视力组，标签S代表受试者属于蒙眼视力正常组。本研究附带有一份基于该数据生成的结果示例图。
数据文件均通过Matlab R2020a进行处理。格式化后的数据集可导入Excel、SPSS及其他同类数据分析软件。