A Comparative Analysis of Smartphone and Standard Tools for Touch Perception Assessment Across Multiple Body Sites

IF 2.4 3区 计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS IEEE Transactions on Haptics Pub Date : 2024-01-14 DOI:10.48550/arXiv.2401.07211
Rachel A. G. Adenekan, Alejandrina Gonzalez Reyes, Kyle T. Yoshida, S. Kodali, Allison M. Okamura, Cara M. Nunez
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引用次数: 1

Abstract

Tactile perception plays an important role in activities of daily living, and it can be impaired in individuals with certain medical conditions. The most common tools used to assess tactile sensation, the Semmes-Weinstein monofilaments and the 128 Hz tuning fork, have poor repeatability and resolution. Long term, we aim to provide a repeatable, high-resolution testing platform that can be used to assess vibrotactile perception through smartphones without the need for an experimenter to be present to conduct the test. We present a smartphone-based vibration perception measurement platform and compare its performance to measurements from standard monofilament and tuning fork tests. We conducted a user study with 36 healthy adults in which we tested each tool on the hand, wrist, and foot, to assess how well our smartphone-based vibration perception thresholds (VPTs) detect known trends obtained from standard tests. The smartphone platform detected statistically significant changes in VPT between the index finger and foot and also between the feet of younger adults and older adults. Our smartphone-based VPT had a moderate correlation to tuning fork-based VPT. Our overarching objective is to develop an accessible smartphone-based platform that can eventually be used to measure disease progression and regression.
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智能手机和标准工具在多个身体部位进行触觉评估的比较分析
触觉在日常生活中起着重要作用,患有某些疾病的人触觉可能会受损。最常用的触觉评估工具--塞姆斯-温斯坦单丝和 128 赫兹音叉的重复性和分辨率都很差。从长远来看,我们的目标是提供一个可重复、高分辨率的测试平台,可用于通过智能手机评估振动触觉感知,而无需实验人员在场进行测试。我们介绍了基于智能手机的振动感知测量平台,并将其性能与标准单丝和音叉测试的测量结果进行了比较。我们对 36 名健康成年人进行了用户研究,测试了手部、腕部和足部的每种工具,以评估基于智能手机的振动感知阈值(VPT)对标准测试中已知趋势的检测效果。智能手机平台检测到食指和脚之间的振动感知阈值发生了统计学意义上的显著变化,年轻成年人和老年人脚之间的振动感知阈值也发生了显著变化。我们基于智能手机的 VPT 与基于音叉的 VPT 具有适度的相关性。我们的总体目标是开发一个基于智能手机的便捷平台,该平台最终可用于测量疾病的进展和消退。
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来源期刊
IEEE Transactions on Haptics
IEEE Transactions on Haptics COMPUTER SCIENCE, CYBERNETICS-
CiteScore
5.90
自引率
13.80%
发文量
109
审稿时长
>12 weeks
期刊介绍: IEEE Transactions on Haptics (ToH) is a scholarly archival journal that addresses the science, technology, and applications associated with information acquisition and object manipulation through touch. Haptic interactions relevant to this journal include all aspects of manual exploration and manipulation of objects by humans, machines and interactions between the two, performed in real, virtual, teleoperated or networked environments. Research areas of relevance to this publication include, but are not limited to, the following topics: Human haptic and multi-sensory perception and action, Aspects of motor control that explicitly pertain to human haptics, Haptic interactions via passive or active tools and machines, Devices that sense, enable, or create haptic interactions locally or at a distance, Haptic rendering and its association with graphic and auditory rendering in virtual reality, Algorithms, controls, and dynamics of haptic devices, users, and interactions between the two, Human-machine performance and safety with haptic feedback, Haptics in the context of human-computer interactions, Systems and networks using haptic devices and interactions, including multi-modal feedback, Application of the above, for example in areas such as education, rehabilitation, medicine, computer-aided design, skills training, computer games, driver controls, simulation, and visualization.
期刊最新文献
Investigating the Kappa Effect Elicited Through Concurrent Visual and Tactile Stimulation. Two rapid alternatives compared to the staircase method for the estimation of the vibrotactile perception threshold. Multichannel Vibrotactile Glove: Validation of a new device designed to sense vibrations. Passive Realizations of Series Elastic Actuation: Effects of Plant and Controller Dynamics on Haptic Rendering Performance. VT-SGN:Spiking Graph Neural Network for Neuromorphic Visual-Tactile Fusion.
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