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多参数非线性 TENS 调制,整合直观的感觉反馈。

Multiparametric non-linear TENS modulation to integrate intuitive sensory feedback.

机构信息

Laboratory for Neuroengineering, Department of Health Science and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092 Zürich, Switzerland.

School of Electrical Engineering, University of Belgrade, 11 000 Belgrade, Serbia.

出版信息

J Neural Eng. 2023 Jun 1;20(3). doi: 10.1088/1741-2552/acd4e8.

Abstract

. Transcutaneous electrical nerve stimulation (TENS) has been recently introduced in neurorehabilitation and neuroprosthetics as a promising, non-invasive sensory feedback restoration alternative to implantable neurostimulation. Yet, the adopted stimulation paradigms are typically based on single-parameter modulations (e.g. pulse amplitude (PA), pulse-width (PW) or pulse frequency (PF)). They elicit artificial sensations characterized by a low intensity resolution (e.g. few perceived levels), low naturalness and intuitiveness, hindering the acceptance of this technology. To address these issues, we designed novel multiparametric stimulation paradigms, featuring the simultaneous modulation of multiple parameters, and implemented them in real-time tests of performance when exploited as artificial sensory inputs.. We initially investigated the contribution of PW and PF variations to the perceived sensation magnitude through discrimination tests. Then, we designed three multiparametric stimulation paradigms comparing them with a standard PW linear modulation in terms of evoked sensation naturalness and intensity. The most performant paradigms were then implemented in real-time in a Virtual Reality-TENS platform to assess their ability to provide intuitive somatosensory feedback in a functional task.. Our study highlighted a strong negative correlation between perceived naturalness and intensity: less intense sensations are usually deemed as more similar to natural touch. In addition, we observed that PF and PW changes have a different weight on the perceived sensation intensity. As a result, we adapted the activation charge rate (ACR) equation, proposed for implantable neurostimulation to predict the perceived intensity while co-modulating the PF and charge per pulse, to TENS (ACR). ACRallowed to design different multiparametric TENS paradigms with the same absolute perceived intensity. Although not reported as more natural, the multiparametric paradigm, based on sinusoidal PF modulation, resulted being more intuitive and subconsciously integrated than the standard linear one. This allowed subjects to achieve a faster and more accurate functional performance.. Our findings suggest that TENS-based, multiparametric neurostimulation, despite not consciously perceived naturally, can provide integrated and more intuitive somatosensory information, as functionally proved. This could be exploited to design novel encoding strategies able to improve the performance of non-invasive sensory feedback technologies.

摘要

经皮神经电刺激(TENS)最近被引入神经康复和神经假肢领域,作为一种有前途的、非侵入性的感觉反馈恢复替代方法,用于植入式神经刺激。然而,所采用的刺激模式通常基于单参数调制(例如,脉冲幅度(PA)、脉冲宽度(PW)或脉冲频率(PF))。它们产生的人工感觉具有低强度分辨率(例如,几个可感知的水平)、低自然度和直观性,从而阻碍了这项技术的接受。为了解决这些问题,我们设计了新的多参数刺激模式,其特点是同时调制多个参数,并在将其用作人工感觉输入时进行实时性能测试。

我们首先通过辨别测试研究了 PW 和 PF 变化对感知感觉大小的贡献。然后,我们设计了三种多参数刺激模式,将其与 PW 线性调制的标准进行了比较,从自然度和强度方面评估了诱发感觉。表现最好的模式随后在虚拟现实-TENS 平台中实时实现,以评估它们在功能任务中提供直观的体感反馈的能力。

我们的研究突出了感知自然度和强度之间的强烈负相关

感觉强度越低,通常被认为越接近自然触感。此外,我们观察到 PF 和 PW 变化对感知感觉强度有不同的权重。结果,我们修改了用于植入式神经刺激的激活电荷量率(ACR)方程,以预测同时调制 PF 和每个脉冲电荷量时的感知强度,即 TENS(ACR)。ACR 允许设计具有相同绝对感知强度的不同多参数 TENS 模式。虽然没有被报告为更自然,但基于正弦 PF 调制的多参数模式比标准线性模式更直观和潜意识地集成,这使得参与者能够更快、更准确地完成功能任务。

我们的研究结果表明,尽管基于 TENS 的多参数神经刺激并未被有意识地感知为自然,但可以提供集成度更高、更直观的体感信息,正如功能证明的那样。这可以用于设计新的编码策略,以提高非侵入性感觉反馈技术的性能。

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