Investigating Passive Haptic Learning of Piano Songs Using Three Tactile Sensations of Vibration, Stroking and Tapping

IF 3.6 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2023-09-27 DOI:10.1145/3610899
Likun Fang, Timo Müller, Erik Pescara, Nikola Fischer, Yiran Huang, Michael Beigl
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Abstract

Passive Haptic Learning (PHL) is a method by which users are able to learn motor skills without paying active attention. In past research, vibration is widely applied in PHL as the signal delivered on the participant's skin. The human somatosensory system provides not only discriminative input (the perception of pressure, vibration, slip, and texture, etc.) to the brain but also an affective input (sliding, tapping and stroking, etc.). The former is often described as being mediated by low-threshold mechanosensitive (LTM) units with rapidly conducting large myelinated (Aᵬ) afferents, while the latter is mediated by a class of LTM afferents called C-tactile afferents (CTs). We investigated whether different tactile sensations (tapping, light stroking, and vibration) influence the learning effect of PHL in this work. We built three wearable systems corresponding to the three sensations respectively. 17 participants were invited to learn to play three different note sequences passively via three different systems. The subjects were then tested on their remembered note sequences after each learning session. Our results indicate that the sensations of tapping or stroking are as effective as the vibration system in passive haptic learning of piano songs, providing viable alternatives to the vibration sensations that have been used so far. We also found that participants on average made up to 1.06 errors less when using affective inputs, namely tapping or stroking. As the first work exploring the differences in multiple types of tactile sensations in PHL, we offer our design to the readers and hope they may employ our works for further research of PHL.
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用振动、抚摸、敲击三种触觉研究钢琴歌曲的被动触觉学习
被动触觉学习(Passive Haptic Learning, PHL)是一种让使用者在没有主动注意的情况下学习运动技能的方法。在过去的研究中,振动作为传递到参与者皮肤上的信号被广泛应用于物理物理。人体体感系统不仅向大脑提供判别输入(对压力、振动、滑动和纹理等的感知),而且还提供情感输入(滑动、敲击和抚摸等)。前者通常被描述为由具有快速传导大髓鞘(Aᵬ)传入的低阈值机械敏感(LTM)单元介导,而后者由一类称为c -触觉传入(ct)的LTM传入介导。在这项研究中,我们研究了不同的触觉感觉(敲击、轻触和振动)是否会影响PHL的学习效果。我们分别针对这三种感觉构建了三个可穿戴系统。17名参与者被邀请通过三种不同的系统被动地学习演奏三种不同的音符序列。在每次学习结束后,研究人员对受试者记忆的音符序列进行了测试。我们的研究结果表明,在钢琴歌曲的被动触觉学习中,敲击或抚摸的感觉与振动系统一样有效,为迄今为止使用的振动感觉提供了可行的替代方案。我们还发现,参与者在使用情感输入(即敲击或抚摸)时,平均减少了1.06个错误。作为探索PHL中多种类型触觉差异的第一个作品,我们将我们的设计提供给读者,希望他们可以利用我们的作品进一步研究PHL。
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来源期刊
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Computer Science-Computer Networks and Communications
CiteScore
9.10
自引率
0.00%
发文量
154
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