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Hierarchical Classification of EMG Signal for Hand and Wrist Gestures and Forces in Myoelectric Control 手、腕部动作与肌电控制力的肌电信号分级分类。
IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2026-02-06 DOI: 10.1109/TNSRE.2026.3660210
Roberto Billardello;Katarina Dejanovic;Francesca Cordella;Daniele D’Accolti;Christian Cipriani;Loredana Zollo
The loss of an upper limb significantly affects daily activities, making advanced prosthesis control crucial for improving the quality of life. Pattern recognition applied to electromyographic signals has emerged as a leading solution for controlling prosthetic hands; yet, most studies focus solely on steady-state muscle activity, neglecting the transient phase of contraction, thereby limiting real-world applicability. To address this limitation, this study introduces a hierarchical approach that combines an Onset Detection Algorithm, a 9-class steady-state gesture classifier, and a three-level force classifier. Additionally, it investigates Self-selected contraction levels across three grasp types, corresponding to subjectively perceived low, medium, and high forces, chosen according to each participant’s preference or perceived exertion. Results demonstrate improved classification accuracy and responsiveness, particularly during early muscle contraction, outperforming state-of-the-art methods. Moreover, optimal contraction levels were found to be grasp-dependent and significantly lower than those commonly used in the literature, emphasizing the need to adjust reference values to reduce fatigue and enhance comfort.
失去上肢会严重影响日常活动,因此先进的假肢控制对提高生活质量至关重要。应用于肌电信号的模式识别已经成为控制假手的主要解决方案;然而,大多数研究只关注稳态肌肉活动,而忽略了短暂的收缩阶段,从而限制了现实世界的适用性。为了解决这一限制,本研究引入了一种分层方法,该方法结合了开始检测算法,9级稳态手势分类器和三级力分类器。此外,它调查了三种抓握类型的自我选择的收缩水平,对应于主观感知的低、中、高力量,根据每个参与者的偏好或感知的用力选择。结果表明,分类准确性和反应性有所提高,特别是在早期肌肉收缩时,优于最先进的方法。此外,最佳收缩水平被发现是抓握依赖的,明显低于文献中常用的水平,强调需要调整参考值来减少疲劳和增强舒适度。
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引用次数: 0
Transcutaneous Spinal Cord Stimulation Provides Sensations to the Missing Hand of Individuals with Upper Limb Amputation. 经皮脊髓刺激为上肢截肢者缺失的手提供感觉。
IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2026-02-06 DOI: 10.1109/TNSRE.2026.3661849
Rita Kharboush, Alejandro Pascual Valdunciel, Anna Boesendorfer, Benedikt Baumgartner, Oskar C Aszmann, Jaime Ibanez Pereda, Dario Farina

Restoring sensory function post amputation remains a major challenge. Peripheral nerve stimulation and targeted reinnervation may partially restore somatotopic feedback, but their need for surgery hinders widespread adoption. Here, we investigate the feasibility of transcutaneous spinal cord stimulation (tSCS) as a non-invasive approach for sensory restoration in upper-limb amputees. In a study involving seventeen able-bodied participants and five individuals with upper-limb amputation, we show that tSCS can evoke a range of sensations, including touch, tapping, vibration, and movement, perceived as originating from the missing limb. Notably, these perceptions were primarily isolated to the missing limb and absent in the residual limb in 98% of trials. Participants with amputations found tSCS tolerable, with some reporting increased comfort during stimulation. tSCS evoked sensations in the fingertips of 93% of able-bodied participants, though these were mainly paraesthetic. We further characterised how stimulation parameters, including electrode placement, carrier frequency, and burst frequency, modulated the quality and type of perceived sensations. Additionally, we show that tSCS maintained force proprioception necessary for effective prosthesis control. These findings support the potential of tSCS as a non-invasive sensory feedback approach for upper-limb prosthesis users.

截肢后恢复感觉功能仍然是一个主要的挑战。外周神经刺激和靶向神经移植可以部分恢复躯体反馈,但它们需要手术,阻碍了广泛采用。在这里,我们研究了经皮脊髓刺激(tSCS)作为上肢截肢者感觉恢复的非侵入性方法的可行性。在一项涉及17名健全参与者和5名上肢截肢者的研究中,我们发现tSCS可以唤起一系列感觉,包括触摸、敲击、振动和运动,这些感觉被认为来自缺失的肢体。值得注意的是,在98%的试验中,这些感知主要孤立于缺失的肢体,而在残肢中不存在。截肢的参与者发现tSCS是可以忍受的,一些人报告在刺激时舒适感增加。tSCS在93%身体健全的参与者的指尖唤起了感觉,尽管这些感觉主要是麻木的。我们进一步描述了刺激参数,包括电极放置、载波频率和突发频率,如何调节感知感觉的质量和类型。此外,我们发现tSCS维持了有效的假体控制所必需的力量本体感觉。这些发现支持tSCS作为上肢假肢使用者非侵入性感觉反馈方法的潜力。
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引用次数: 0
A Hybrid Assistive-Resistive Isokinetic Training Robot for Full-cycle Knee Rehabilitation. 一种用于全周期膝关节康复的混合型辅助-阻力等速训练机器人。
IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2026-02-06 DOI: 10.1109/TNSRE.2026.3661538
Haoyang Wu, Wenjie Chen, Liheng Tuo, Jiaxin Ren, Linhang Ju, Xingyu Hu, Yixin Shao, Di Shi, Lecheng Ruan, Yan Huang, Bi Zhang, Kunyang Wang, Yanggang Feng, Wuxiang Zhang

Previously, we proposed a power-free isokinetic training robot designed to provide resistive isokinetic training for knee injury patients during advanced-stage rehabilitation. However, patients in the early stage often lack sufficient muscle strength and necessitate assistive support. To address this limitation, this study introduces a hybrid assistive-resistive isokinetic training robot that integrates active assistance for early-stage knee rehabilitation and power-free resistive training for advanced stages. The system features a compact mechanical design and a reconfigurable control circuit capable of dynamically switching among three modes: active, passive (regeneration), and passive (consumption). Ten healthy subjects and ten knee-injury patients participated in the experimental validation. The results confirmed the adaptability of the system across multiple rehabilitation stages. These findings demonstrate the feasibility of the hybrid assistive-resistive isokinetic training robot and highlight the potential of the system for both clinical application and home-based rehabilitation. Future work will focus on extending the system to multi-joint training and enhancing control algorithms for broader patient populations.

之前,我们提出了一种无动力等速训练机器人,旨在为膝关节损伤晚期康复患者提供阻力等速训练。然而,早期患者往往缺乏足够的肌肉力量,需要辅助支持。为了解决这一限制,本研究引入了一种混合辅助-阻力等速训练机器人,该机器人集成了早期膝关节康复的主动辅助和高级阶段的无动力阻力训练。该系统具有紧凑的机械设计和可重构的控制电路,能够在三种模式之间动态切换:主动,被动(再生)和被动(消耗)。10名健康受试者和10名膝关节损伤患者参与实验验证。结果证实了该系统在多个康复阶段的适应性。这些发现证明了混合辅助-阻力等速训练机器人的可行性,并突出了该系统在临床应用和家庭康复方面的潜力。未来的工作将集中于将该系统扩展到多关节训练,并为更广泛的患者群体增强控制算法。
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引用次数: 0
A robotic assistance with specialized timing improves motor performance: implications to movement training. 专门计时的机器人辅助改善运动表现:对运动训练的影响。
IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2026-02-03 DOI: 10.1109/TNSRE.2026.3660517
Alex C Dzewaltowski, Philippe Malcolm

Robotic devices can expand the repertoire of rehabilitation methods by enabling actions that cannot be replicated by a physical therapist. We previously developed a technique, we term 'rapid assistance,' that can assist movements beginning within the electromechanical delay between muscle activation and muscle contraction. Here, we evaluated the effects of repeated arm extension training with rapid assistance in older adults (n = 18) during a single session. We compared training with rapid assistance to a control group that performed unassisted arm extension training. Participants positively adapted to rapid assistance indicated by quickening reaction times (15.69%, t = -1.79, p = 0.089, d = 0.36) and greater extension angular velocities (47.93%, t = 3.47, p = 0.002, d = 0.56) compared to the control group following training. These motor performance improvements following rapid assistance training may be due to reducing Golgi-tendon inhibition during muscle contraction thereby, introducing an alternate strategy to improve motor performance. This specialized assistive timing may address a trade-off present in rehabilitative practice between assisting a patient or sufficiently challenging them to facilitate functional recovery.

机器人设备可以通过实现物理治疗师无法复制的动作来扩展康复方法的范围。我们之前开发了一种技术,我们称之为“快速辅助”,它可以在肌肉激活和肌肉收缩之间的机电延迟中帮助开始的运动。在这里,我们评估了老年人(n = 18)在单次快速辅助下重复手臂伸展训练的效果。我们将快速辅助训练与无辅助手臂伸展训练的对照组进行了比较。与训练后的对照组相比,参与者积极适应快速援助,反应时间加快(15.69%,t = -1.79, p = 0.089, d = 0.36),扩展角速度加快(47.93%,t = 3.47, p = 0.002, d = 0.56)。快速辅助训练后运动表现的改善可能是由于肌肉收缩过程中高尔基肌腱抑制的减少,从而引入了一种改善运动表现的替代策略。这种专门的辅助时机可以解决在帮助患者或充分挑战他们促进功能恢复之间的权衡。
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引用次数: 0
Design of FPGA-Based Rehabilitation Effect Assessment Headband 基于fpga的康复效果评估头带设计。
IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2026-02-03 DOI: 10.1109/TNSRE.2026.3660726
Willy Chou;Bor-Shing Lin;Yu-Chia Chang;Bor-Shyh Lin
Stroke is an emergency cerebrovascular event, resulting in damage to cranial nerves, and the subsequent rehabilitation is necessary to restore neurological function and improve patient outcomes. In clinical settings, the rehabilitation effectiveness is assessed subjectively by experienced physicians or through the use of performance assessment scales. Although several techniques, such as electroencephalography (EEG), cardiopulmonary exercise testing (CPET), and functional magnetic resonance imaging (fMRI), may also be utilized in the evaluation of rehabilitation effectiveness, they require higher costs and the expertise of professional medical staff for experienced operation and post-analysis. Based on the technique of near-infrared spectroscopy (NIRS), a field programmable gate array (FPGA)-based rehabilitation effect assessment headband was proposed. The designed headband could monitor the change in cerebral blood flow non-invasively and continuously under exercise. From the changes in cerebral blood flow, eight perfusion indexes were also extracted in real time and utilized to assess the cardiopulmonary function status of middle-aged and older adults before and after rehabilitation. The analysis algorithm would be completed in the wireless and wearable headband to greatly improve the convenience of use. The experimental results showed that the cardiopulmonary function status could be effectively classified from defined perfusion indexes, and the differences between defined perfusion indexes and the neural network output before and after rehabilitation were also significant.
脑卒中是一种紧急脑血管事件,导致脑神经损伤,随后的康复治疗对于恢复神经功能和改善患者预后是必要的。在临床环境中,康复效果由经验丰富的医生或通过使用绩效评估量表进行主观评估。虽然脑电图(EEG)、心肺运动试验(CPET)和功能磁共振成像(fMRI)等几种技术也可用于康复效果的评估,但它们需要较高的成本和专业医务人员的专业知识,以获得经验丰富的操作和事后分析。基于近红外光谱(NIRS)技术,提出了一种基于现场可编程门阵列(FPGA)的康复效果评估头带。所设计的头带可以无创、连续监测运动时脑血流量的变化。从脑血流变化中实时提取8项灌注指标,用于评估康复前后中老年人心肺功能状态。分析算法将在无线可穿戴头带中完成,大大提高了使用的便利性。实验结果表明,从定义的灌注指标可以有效地对心肺功能状态进行分类,并且定义的灌注指标与康复前后神经网络输出的差异也很显著。
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引用次数: 0
Design and Evaluation of User-Centered Extended Reality Myoelectric Prosthesis Training Tool 以用户为中心的扩展现实肌电假肢训练工具的设计与评价。
IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2026-02-02 DOI: 10.1109/TNSRE.2026.3660215
InHwa Lee;Christopher L. Hunt;Nitish V. Thakor;Rahul R. Kaliki
In recent years, extended reality-based myoelectric training has emerged as a promising approach to prepare users for advanced prosthesis control. This study: 1) identified User Needs for an ideal training tool through qualitative interviews with occupational therapists; 2) developed the Myoelectric Training in Extended Reality (MyoTrainXR) system; and 3) evaluated its usability using an advanced postural control strategy. Six individuals with intact limbs and two with trans-radial upper limb loss underwent four 45-minute training sessions with the Block Builder module. The Pasta Box Task was used during training and evaluation, and the Cup Transfer Task was used only during evaluation. In the Pasta Box Task, participants with intact limbs maintained a 100% completion rate, while their success rate increased from $86.1pm 5.8$ % to $98.5pm 3.7$ %. Participants with upper limb loss began with completion rates between 0% and 40%, improving to 100%, with success rates between 90.9% and 100% by the final evaluation. Iteration completion times showed significant reduction across all participants ( $p$ -value < 0.05, linear mixed-effects model), with the median decreasing from 19.4 to 15.8 seconds. The Cup Transfer Task showed a similar trend of significant improvement, demonstrating that the acquired skills generalized to an untrained task. The system also demonstrated excellent usability, with an average System Usability Scale score of $81.9pm 10.0$ . These findings indicate that our user-centered extended reality training tool holds promise for enhancing myoelectric control proficiency.
近年来,扩展的基于现实的肌电训练已经成为一种有前途的方法,为用户准备先进的假肢控制。本研究(1)通过对职业治疗师的定性访谈,确定了理想训练工具的用户需求;(2)开发了扩展现实中的肌电训练(MyoTrainXR)系统;(3)使用先进的姿势控制策略评估了其可用性。6个肢体完整的个体和2个桡骨上肢缺失的个体用Block Builder模块进行了4次45分钟的训练。面食盒任务在训练和评估期间使用,杯子转移任务仅在评估期间使用。在面食盒任务中,四肢完好的受试者保持100%的完成率,成功率从86.1±5.8%提高到98.5±3.7%。上肢丧失的参与者开始时的完成率在0%至40%之间,到最终评估时,完成率在90.9%至100%之间。所有参与者的迭代完成时间均显著减少(p值< 0.05,线性混合效应模型),中位数从19.4秒减少到15.8秒。杯子转移任务显示出类似的显著改善趋势,表明习得的技能可以推广到未经训练的任务中。该系统的可用性也很好,系统可用性量表的平均得分为81.9±10.0。这些发现表明,我们以用户为中心的扩展现实训练工具有望提高肌电控制能力。
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引用次数: 0
Behavioral Cloning of Physiotherapists in Adapting Robot Control Parameter 物理治疗师在机器人控制参数适应中的行为克隆。
IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2026-01-29 DOI: 10.1109/TNSRE.2026.3659215
Rita Molle;Christian Tamantini;Clemente Lauretti;Davide Sebastiani;Fabio Santacaterina;Marco Bravi;Federica Bressi;Sandra Miccinilli;Loredana Zollo
Robot-aided rehabilitation effectively supports treatment of upper-limb disorders and enhances outcomes when combined with traditional therapy. Artificial intelligence enables behavioral cloning of physiotherapists’ expertise to autonomously modulate robot assistance from real-time multimodal patient data. Therefore, this paper aims to propose and validate a behavioral cloning strategy, namely Physiotherapist-Supervised Parameter Adaptation (PSPA), for online tuning the robot assistance level replicating the physiotherapists’ decision-making.The experimental validation was conducted in a clinical setting involving ten post-surgical orthopedic patients who participated in a robot-aided rehabilitation session using the KUKA LWR 4 + robot. The sessions were supervised by physiotherapists who could adjust the level of robotic assistance as needed, thus labelling the collected patient multimodal data. The validation aimed at i) identifying the best-performing input modality, feature set, and classifier, and ii) comparing the capability of the approach in tailoring the assistance level with respect to the established performance-based (PB) one.Combining biomechanical and physiological features significantly improved the classification performance across all classifiers, with the highest performance observed for the Multilayer Perceptron on the present dataset. Moreover, using the optimized feature set, the proposed PSPA methodology achieved an even greater alignment with the physiotherapists’ decisions with respect to the PB approach ( $Delta text {F1-score} = {15}.{40} pm {30}.{33}%$ , $rho = {0}.{56} pm {0}.{21}$ for PSPA, $rho = -{0}.{12} pm {0}.{43}$ for PB).
机器人辅助康复有效地支持上肢疾病的治疗,并在与传统治疗相结合时提高疗效。人工智能使物理治疗师的专业知识的行为克隆能够从实时多模态患者数据中自主调节机器人辅助。因此,本文旨在提出并验证一种行为克隆策略,即物理治疗师监督参数自适应(PSPA),用于在线调整复制物理治疗师决策的机器人辅助水平。实验验证在临床环境中进行,涉及10名骨科术后患者,他们使用KUKA LWR 4+机器人参加机器人辅助康复课程。这些疗程由物理治疗师监督,他们可以根据需要调整机器人辅助的水平,从而标记收集到的患者多模式数据。验证的目的是:i)识别性能最好的输入模式、特征集和分类器,以及ii)比较该方法在根据已建立的基于性能的(PB)方法定制辅助水平方面的能力。结合生物力学和生理特征显著提高了所有分类器的分类性能,在本数据集上观察到的多层感知器的性能最高。此外,使用优化的特征集,所提出的PSPA方法在PB方法方面与物理治疗师的决策实现了更大的一致性(ΔF1-score = 15.40±30.33%,ρ = 0.56±0.21,ρ = -0.12±0.43)。
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引用次数: 0
Functional Assessment of a Flexible Thermal Stimulation Device for Hand Edema Elimination in Stroke Survivors 一种用于脑卒中幸存者手部水肿消除的柔性热刺激装置的功能评估。
IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2026-01-29 DOI: 10.1109/TNSRE.2026.3659248
Yitong Zhou;Jun Zhang;Yingying Li;Congzhi Tang;Xi Yang;Aiguo Song
Stroke survivors often suffer from severe discomfort caused by persistent hand edema, including hand pain, restricted knuckle mobility, and negative emotions, which significantly hinders normal rehabilitation progress. Whether physical or psychological in impact, the prevention and treatment of hand edema warrant significant attention throughout all stages of stroke rehabilitation. However, traditional rehabilitation therapies generally neglect edema management, focusing primarily on motor function recovery. Consequently, this study introduces the TESSR (ThErmal Stimulation device for Stroke Rehabilitation), a novel apparatus designed to promote hand rehabilitation for stroke survivors. TESSR is equipped with a flexible stimulation array comprising 50 independently controlled stimulation units, each capable of rapid heating and cooling transitions as well as delivering sustained and stable thermal outputs. This alternating thermal stimulation (TS) is designed to alleviate edema and activate the sensory cortex, thereby facilitating neuroplasticity. A controlled clinical study was conducted with 12 stroke survivors to assess the effectiveness of the TESSR device. The participants were divided into two groups: one receiving conventional rehabilitation (CR group) and the other receiving supplementary TS conducted by the TESSR device (TS group). Following a two-week intervention, the TS group exhibited a notable reduction in hand edema, with a mean decrease of 38.6%, compared to the minimal improvement observed in the CR group. Furthermore, participants in the TS group demonstrated improved hand function, including enhanced sensory perception and diminished pain. The findings demonstrate the potential of TESSR as a comprehensive and effective tool for hand rehabilitation.
脑卒中幸存者通常会因手部持续水肿而遭受严重不适,包括手部疼痛、关节活动受限以及负面情绪,这严重阻碍了正常的康复进展。无论是生理上还是心理上的影响,手部水肿的预防和治疗在卒中康复的各个阶段都值得重视。然而,传统的康复疗法通常忽视水肿的治疗,主要关注运动功能的恢复。因此,本研究介绍了TESSR (ThErmal Stimulation device for Stroke Rehabilitation),这是一种旨在促进中风幸存者手部康复的新型设备。TESSR配备了一个灵活的增产阵列,包括50个独立控制的增产单元,每个单元都能够快速加热和冷却转换,并提供持续稳定的热输出。这种交替热刺激(TS)旨在减轻水肿,激活感觉皮层,从而促进神经可塑性。对12名中风幸存者进行了一项对照临床研究,以评估TESSR装置的有效性。参与者分为两组:一组接受常规康复治疗(CR组),另一组接受TESSR装置辅助TS治疗(TS组)。经过两周的干预,TS组手部水肿明显减少,平均减少38.6%,而CR组的改善最小。此外,TS组的参与者表现出了手功能的改善,包括感觉知觉增强和疼痛减轻。研究结果显示TESSR作为一种全面有效的手部康复工具的潜力。
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引用次数: 0
Predicting Attention Decline: An Integrated Beta-Band and SSVEP Approach for Visual Brain–Computer Interfaces 预测注意力下降:脑机视觉接口的综合β -波段和SSVEP方法
IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2026-01-28 DOI: 10.1109/TNSRE.2026.3658740
Siwen Wei;Yongzhi Huang;Haiqing Yu;Jiayuan Meng;Rui Xu;Tzyy-Ping Jung;Minpeng Xu;Dong Ming
Real-time monitoring of sustained attention fluctuations during continuous complex tasks is vital for enhancing task performance and preventing accidents. Attention modulates neurons in the visual cortex in various ways to improve the visual sensitivity at an attended location. EEG-based brain-computer interfaces (BCIs) offer one of the most effective approaches for monitoring the state of human individuals. Whether transient responses evoked by brief stimuli, steady-state responses elicited by prolonged stimuli, or spontaneous neural oscillations, researchers can extract recognized electrophysiological features that reflect attention levels. However, unimodal features face inherent limitations, such as the low signal-to-noise ratio of transient responses and susceptibility of spontaneous rhythms to electrophysiological interference. Nevertheless, few studies have explored multimodal feature fusion for attention state monitoring. Here, we developed an innovative continuous go/no-go task to concurrently evoke both event-related potential (ERP) and steady-state visual evoked potential (SSVEP), while modulating spontaneous oscillatory activities through attentional engagement. To maximize the attentional modulation effect, we integrated the contrast-response functions of the modulation effect of attention on SSVEP and implemented 12 stimulus contrast levels to identify optimal visual stimulation intensity. Results from 25 subjects demonstrated that the decline in sustained attention during a continuous task was predictable before behavioral mistakes. Classification performance peaked at 31.60% stimulus contrast condition using the fused features combining spontaneous beta-band oscillations and SSVEP responses (average: 74.48%; best: 90.83%). These findings advance the development of more robust real-time attention monitoring systems based on BCI technology.
实时监测连续复杂任务中持续的注意力波动对于提高任务绩效和预防事故至关重要。注意通过多种方式调节视觉皮层的神经元,以提高被注意位置的视觉灵敏度。基于脑电图的脑机接口(bci)为监测个体状态提供了最有效的方法之一。无论是短暂刺激引起的瞬态反应,长时间刺激引起的稳态反应,还是自发的神经振荡,研究人员都可以提取反映注意力水平的公认电生理特征。然而,单峰特征面临固有的局限性,例如瞬态响应的低信噪比和自发节律对电生理干扰的敏感性。然而,很少有研究探讨多模态特征融合用于注意状态监测。在这里,我们开发了一个创新的连续去/不去任务,同时唤起事件相关电位(ERP)和稳态视觉诱发电位(SSVEP),同时通过注意参与调节自发振荡活动。为了最大限度地发挥注意调制效应,我们整合了注意对SSVEP调制效应的对比-反应函数,并实施了12种刺激对比水平,以确定最佳视觉刺激强度。来自25名受试者的结果表明,在行为错误之前,在连续任务中持续注意力的下降是可以预测的。结合自发β波段振荡和SSVEP反应的融合特征刺激对比条件下,分类性能达到31.60%,平均为74.48%,最佳为90.83%。这些发现促进了基于脑机接口技术的更强大的实时注意力监测系统的发展。
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引用次数: 0
Biphasic Electrostimulation Artifact Model for ECAP Extraction in Spinal Cord Stimulation 脊髓刺激中ECAP提取的双相电刺激伪影模型。
IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2026-01-28 DOI: 10.1109/TNSRE.2026.3658636
Haochen Zhang;Xuesong Luo;Bozhi Ma;Luming Li;Xulan Yin;Zhongwei Luo;Boyang Zhang;Xi Zhang;Hongda Li;Qingyu Yao;Junhong Lim
Evoked compound action potential (ECAP) is extensively used as biomarker for neural activity in closed-loop spinal cord stimulation (SCS). However, accurate monitoring of neural activity is challenged by the low signal-to-noise ratio of ECAP recording, primarily due to the interference from stimulation-induced artifacts. This study proposes biphasic electrostimulation artifact model (BEAM) for ECAP extraction and assesses its efficacy using an enhanced quantification approach. The BEAM model is built based on the principle of additivity and incorporates boundary conditions that account for the equivalent electrical environment and temporal relationships. A bilinear growth curve model is introduced to calculate the E-score, enabling a comparison of ECAP extraction results with other methods. The proposed approach is extensively validated using clinical data from nine-month SCS therapy. BEAM method achieves the highest E-scores and reduces stimulation artifacts clinically without distorting information related to neural activity. BEAM accurately characterizes the morphology of artifacts generated by stimulation across various neurostimulation scenarios. Our model may lead to unique interpretation of neural activation in ECAP signals, evoked by electrical stimulation especially in closed-loop controlling strategies that aim to maintain consistent neural excitation.
诱发复合动作电位(ECAP)被广泛用作闭环脊髓刺激(SCS)中神经活动的生物标志物。然而,ECAP记录的低信噪比给神经活动的准确监测带来了挑战,这主要是由于刺激引起的伪影的干扰。本研究提出了用于ECAP提取的双相电刺激伪影模型(BEAM),并使用增强的量化方法评估其有效性。BEAM模型是基于可加性原理建立的,并结合了考虑等效电环境和时间关系的边界条件。引入双线性增长曲线模型计算E-score,将ECAP提取结果与其他方法进行比较。该方法通过9个月SCS治疗的临床数据得到了广泛验证。BEAM方法获得了最高的e分数,并且在临床上减少了刺激伪影,而不会扭曲与神经活动相关的信息。BEAM准确地表征了各种神经刺激情景下刺激产生的伪影的形态。我们的模型可能会对电刺激引起的ECAP信号中的神经激活产生独特的解释,特别是在旨在保持神经兴奋一致的闭环控制策略中。
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IEEE Transactions on Neural Systems and Rehabilitation Engineering
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