A Novel CNN-BiLSTM Ensemble Model With Attention Mechanism for Sit-to-Stand Phase Identification Using Wearable Inertial Sensors [0.03%]
基于注意力机制的CNN-BiLSTM集成模型在穿戴式惯性传感器坐-站姿态识别中的应用研究
Xin Chen,Shibo Cai,Longjie Yu et al.
Xin Chen et al.
Sit-to-stand transition phase identification is vital in the control of a wearable exoskeleton robot for assisting patients to stand stably. In this study, we aim to propose a method for segmenting and identifying the sit-to-stand phase usi...
Assessing Free-Living Postural Sway in Persons With Multiple Sclerosis [0.03%]
用于评估多发性硬化症患者的日常生活中的姿势变换的方法
Brett M Meyer,Jenna G Cohen,Paolo DePetrillo et al.
Brett M Meyer et al.
Postural instability is associated with disease status and fall risk in Persons with Multiple Sclerosis (PwMS). However, assessments of postural instability, known as postural sway, leverage force platforms or wearable accelerometers, and a...
Cutting Edge Bionics in Highly Impaired Individuals: A Case of Challenges and Opportunities [0.03%]
高度受损个体中的尖端生物电子学：挑战与机遇一例
Eric J Earley,Jan Zbinden,Maria Munoz-Novoa et al.
Eric J Earley et al.
Highly impaired individuals stand to benefit greatly from cutting-edge bionic technology, however concurrent functional deficits may complicate the adaptation of such technology. Here, we present a case in which a visually impaired individu...
Event-Related EEG Desynchronization Reveals Enhanced Motor Imagery From the Third Person Perspective by Manipulating Sense of Body Ownership With Virtual Reality for Stroke Patients [0.03%]
事件相关的EEG去同步化揭示了通过虚拟现实操纵身体所有权感可增强中风患者的第三人称运动想象
Xiaotian Xu,Xiaoya Fan,Jiaoyang Dong et al.
Xiaotian Xu et al.
Virtual reality (VR)-based rehabilitation training holds great potential for post-stroke motor recovery. Existing VR-based motor imagery (MI) paradigms mostly focus on the first-person perspective, and the benefit of the third-person perspe...
Channel Selection for Stereo- Electroencephalography (SEEG)-Based Invasive Brain-Computer Interfaces Using Deep Learning Methods [0.03%]
基于深度学习方法的立体脑电(SEEG)入侵式脑机接口通道选择研究
Xiaolong Wu,Guangye Li,Xin Gao et al.
Xiaolong Wu et al.
Brain-computer interfaces (BCIs) can enable direct communication with assistive devices by recording and decoding signals from the brain. To achieve high performance, many electrodes will be used, such as the recently developed invasive BCI...
Multi-Branch Mutual-Distillation Transformer for EEG-Based Seizure Subtype Classification [0.03%]
基于多分支互蒸馏变压器的癫痫发作亚型分类研究
Ruimin Peng,Zhenbang Du,Changming Zhao et al.
Ruimin Peng et al.
Cross-subject electroencephalogram (EEG) based seizure subtype classification is very important in precise epilepsy diagnostics. Deep learning is a promising solution, due to its ability to automatically extract latent patterns. However, it...
IMU-Based Kinematics Estimation Accuracy Affects Gait Retraining Using Vibrotactile Cues [0.03%]
基于IMU的运动学估计精度影响使用振动触觉线索的步态再训练
Nataliya Rokhmanova,Owen Pearl,Katherine J Kuchenbecker et al.
Nataliya Rokhmanova et al.
Wearable sensing using inertial measurement units (IMUs) is enabling portable and customized gait retraining for knee osteoarthritis. However, the vibrotactile feedback that users receive directly depends on the accuracy of IMU-based kinema...
Gait Intention Prediction Using a Lower-Limb Musculoskeletal Model and Long Short-Term Memory Neural Networks [0.03%]
使用下肢肌肉骨骼模型和长短期记忆神经网络进行步态意图预测
Qingyao Bian,Marco Castellani,Duncan Shepherd et al.
Qingyao Bian et al.
The prediction of gait motion intention is essential for achieving intuitive control of assistive devices and diagnosing gait disorders. To reduce the cost associated with using multimodal signals and signal processing, we proposed a novel ...
Rapid-IAF: Rapid Identification of Individual Alpha Frequency in EEG Data Using Sequential Bayesian Estimation [0.03%]
快速IAF：使用顺序贝叶斯估计在EEG数据中快速识别个人阿尔法频率
Seitaro Iwama,Junichi Ushiba
Seitaro Iwama
Rapid and robust identification of the individual alpha frequency (IAF) in electroencephalogram (EEG) is an essential factor for successful brain-computer interface (BCI) use. Here we demonstrate an algorithm to determine the IAF from short...
Neural Network Dynamics and Brain Oscillations Underlying Aberrant Inhibitory Control in Internet Addiction [0.03%]
网络动力学和脑震荡在互联网成瘾中异常抑制控制的作用机制研究
Yi-Li Tseng,Yu-Kai Su,Wen-Jiun Chou et al.
Yi-Li Tseng et al.
Previous studies have reported a role of alterations in the brain's inhibitory control mechanism in addiction. Mounting evidence from neuroimaging studies indicates that its key components can be evaluated with brain oscillations and connec...