用人工振动触觉线索补偿不确定的视觉目标信息的同时,优化多感官整合的到达规划

IF 5.2 2区 医学 Q1 ENGINEERING, BIOMEDICAL Journal of NeuroEngineering and Rehabilitation Pub Date : 2024-09-09 DOI:10.1186/s12984-024-01448-0
Lukas K. Amann, Virginia Casasnovas, Jannis Hainke, Alexander Gail
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引用次数: 0

摘要

计划和执行动作需要整合不同的感觉模式,如视觉和本体感觉。然而,中风等神经系统疾病会导致本体感觉全部或部分丧失,从而导致运动障碍。最近的研究重点是为患者提供额外的感官反馈,以弥补患者的感官缺失,事实证明振动触觉刺激是一种可行的选择,因为它成本低廉且易于实施。在这里,我们测试了如何将这种振动触觉信息与视觉信号相结合,以估计伸手目标的空间位置。我们对 31 名健康的人类参与者采用了中心向外伸手范例,研究人工振动触觉刺激如何与指示目标位置的视觉空间线索相结合。具体来说,我们使用偏心旋转质量(ERM)电机为移动的优势臂提供多点振动触觉刺激。当其中一种感觉模式不确定时,整合多种感觉模式的输入就变得尤为重要,因此我们还额外调节了视觉线索的可靠性。然后,我们将作为视觉不确定性函数的振动触觉和视觉输入的权衡与最大似然估计(MLE)框架的预测进行了比较,以确定参与者是否实现了准最佳整合。我们的结果表明,参与者可以根据振动触觉指令估计目标位置。经过短期培训后,当视觉线索不确定时,结合视觉和振动触觉线索可提高命中率并减少到达错误。此外,我们还观察到,当存在振动触觉刺激时,在视觉不确定性较低的试验中反应时间较短。利用 MLE 预测,我们发现当振动触觉线索需要检测一个或两个活动电机时,振动触觉和视觉线索的整合遵循最佳整合。但是,如果估计目标的位置需要分辨两个线索的强度,整合就违反了 MLE 预测。我们的结论是,参与者可以很快学会整合视觉和人工振动触觉信息。因此,使用额外的振动触觉刺激可能是改善本体感觉缺失患者康复或控制假肢装置的一种有前途的方法。
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Optimality of multisensory integration while compensating for uncertain visual target information with artificial vibrotactile cues during reach planning
Planning and executing movements requires the integration of different sensory modalities, such as vision and proprioception. However, neurological diseases like stroke can lead to full or partial loss of proprioception, resulting in impaired movements. Recent advances focused on providing additional sensory feedback to patients to compensate for the sensory loss, proving vibrotactile stimulation to be a viable option as it is inexpensive and easy to implement. Here, we test how such vibrotactile information can be integrated with visual signals to estimate the spatial location of a reach target. We used a center-out reach paradigm with 31 healthy human participants to investigate how artificial vibrotactile stimulation can be integrated with visual-spatial cues indicating target location. Specifically, we provided multisite vibrotactile stimulation to the moving dominant arm using eccentric rotating mass (ERM) motors. As the integration of inputs across multiple sensory modalities becomes especially relevant when one of them is uncertain, we additionally modulated the reliability of visual cues. We then compared the weighing of vibrotactile and visual inputs as a function of visual uncertainty to predictions from the maximum likelihood estimation (MLE) framework to decide if participants achieve quasi-optimal integration. Our results show that participants could estimate target locations based on vibrotactile instructions. After short training, combined visual and vibrotactile cues led to higher hit rates and reduced reach errors when visual cues were uncertain. Additionally, we observed lower reaction times in trials with low visual uncertainty when vibrotactile stimulation was present. Using MLE predictions, we found that integration of vibrotactile and visual cues followed optimal integration when vibrotactile cues required the detection of one or two active motors. However, if estimating the location of a target required discriminating the intensities of two cues, integration violated MLE predictions. We conclude that participants can quickly learn to integrate visual and artificial vibrotactile information. Therefore, using additional vibrotactile stimulation may serve as a promising way to improve rehabilitation or the control of prosthetic devices by patients suffering loss of proprioception.
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来源期刊
Journal of NeuroEngineering and Rehabilitation
Journal of NeuroEngineering and Rehabilitation 工程技术-工程:生物医学
CiteScore
9.60
自引率
3.90%
发文量
122
审稿时长
24 months
期刊介绍: Journal of NeuroEngineering and Rehabilitation considers manuscripts on all aspects of research that result from cross-fertilization of the fields of neuroscience, biomedical engineering, and physical medicine & rehabilitation.
期刊最新文献
Comparison of synergy extrapolation and static optimization for estimating multiple unmeasured muscle activations during walking. Immersive virtual reality for learning exoskeleton-like virtual walking: a feasibility study. Instrumented assessment of lower and upper motor neuron signs in amyotrophic lateral sclerosis using robotic manipulation: an explorative study. Rest the brain to learn new gait patterns after stroke. Effects of virtual reality rehabilitation after spinal cord injury: a systematic review and meta-analysis.
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