Attentional demands during walking are increased by small simulated leg length discrepancy [0.03%]
模拟下肢长度差异对行走时注意力需求的影响
Keisuke Takada,Miyu Sugimoto,Yuma Takenaka et al.
Keisuke Takada et al.
Introduction: Leg length discrepancy (LLD) is known to disrupt gait symmetry and affect motor control. However, the effects of LLD-induced gait asymmetry on attention functions during walking remain unclear. Therefore, th...
Estimating the valence and arousal of dyadic conversations using autonomic nervous system responses and regression algorithms [0.03%]
基于自主神经系统的反应和回归算法估计双人对话的情感极性和唤醒度
Iman Chatterjee,Maja Goršič,Robert A Kaya et al.
Iman Chatterjee et al.
Introduction: Autonomic nervous system responses provide valuable information about interactions between pairs or groups of people but have primarily been studied using group-level statistical analysis, with a few studies...
Let's put a person back into Cyber-Physical-Social research: Public Mental Models Framework [0.03%]
让人类回归人机物融合研究：公共心智模型框架
Mare Teichmann,Jaanus Kaugerand,Merik Meriste et al.
Mare Teichmann et al.
In the current paper our focus is on linking Public Mental Models with behavior, Situation Awareness and stress management, with predicting and intervening in public behavior in critical situations. Understanding and influencing behavior wi...
Pilot mental workload analysis in the A320 traffic pattern based on HRV features [0.03%]
基于HRV特征的A320五边区域飞行员工作负荷分析
Jiajun Yuan,Bo Jia,Chenyang Zhang et al.
Jiajun Yuan et al.
Pilot mental workload is a critical factor influencing flight safety, particularly during dynamic flight phases with high cognitive demands such as takeoff and landing. This study evaluates pilot workload across different flight phases (tak...
Diana E Gherman,Thorsten O Zander
Diana E Gherman
Introduction: Large-language models (LLMs) are transforming most industries today and are set to become a cornerstone of the human digital experience. While integrating explicit human feedback into the training and develo...
An EEG-network-metric based approach to real-time trust inference in human-autonomy teaming [0.03%]
基于EEG网络度量的实时人自主团队信任推理方法
Gregory Bales,Allison P A Hayman,Torin K Clark et al.
Gregory Bales et al.
Efficient and effective teaming between humans and autonomous systems requires the establishment and maintenance of trust to maximize team task performance. Despite advances in autonomous systems, human expertise remains critical in tasks f...
Machine learning performance in EEG-based mental workload classification across task types: a systematic review [0.03%]
基于EEG的机器学习在不同任务类型下的心理负荷分类性能系统评价
Miloš Pušica,Bogdan Mijović,Maria Chiara Leva et al.
Miloš Pušica et al.
The literature features a variety of tasks and methodologies to induce mental workload (MWL) and to assess the performance of MWL estimation models. Because no standardized benchmark task or set of tasks exists, the comparison of different ...
Neuro-insights: a systematic review of neuromarketing perspectives across consumer buying stages [0.03%]
神经学见解：消费者购买阶段的神经营销观点系统性回顾
Raveena Gupta,Anuj Pal Kapoor,Harsh V Verma
Raveena Gupta
The application of neurophysiological techniques in marketing and consumer research has seen substantial growth in recent years. This review provides a comprehensive overview of how neuroscience has been integrated into consumer behavior re...
How low can you go: evaluating electrode reduction methods for EEG-based speech imagery BCIs [0.03%]
无下不彻：基于EEG的语音想象BCI中评价电极削减方法
Maurice Rekrut,Johannes Ihl,Tobias Jungbluth et al.
Maurice Rekrut et al.
Speech imagery brain-computer interfaces (SI-BCIs) aim to decode imagined speech from brain activity and have been successfully established using non-invasive brain measures such as electroencephalography (EEG). However, current EEG-based S...
The impact of cross-validation choices on pBCI classification metrics: lessons for transparent reporting [0.03%]
交叉验证选择对pBCI分类指标的影响：透明报道的教训
Felix Schroeder,Stephen Fairclough,Frederic Dehais et al.
Felix Schroeder et al.
Neuroadaptive technologies are a type of passive Brain-computer interface (pBCI) that aim to incorporate implicit user-state information into human-machine interactions by monitoring neurophysiological signals. Evaluating machine learning a...