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As Brain-computer interface (BCI) technology develops it is likely it may be incorporated into protocols that complement and supplement existing movements of the user. Two possible scenarios for such a control could be: the increasing…

神经元与认知 · 定量生物学 2016-04-06 Luke Bashford , Jing Wu , Devapratim Sarma , Kelly Collins , Jeff Ojemann , Carsten Mehring

Mental imagery-based brain-computer interfaces (BCIs) allow to interact with the external environment by naturally bypassing the musculoskeletal system. Making BCIs efficient and accurate is paramount to improve the reliability of real-life…

Brain-Computer Interface(BCI) systems support communication through direct measures of neural activity without muscle activity. Brain-Computer Interface systems need to be validated in long-term studies of real-world use by people with…

人机交互 · 计算机科学 2022-04-05 Bosubabu Sambana , Priyanka Mishra

BCI systems are able to communicate directly between the brain and computer using neural activity measurements without the involvement of muscle movements. For BCI systems to be widely used by people with severe disabilities, long-term…

人机交互 · 计算机科学 2023-05-31 Krishna Pai , Rakhee Kallimani , Sridhar Iyer , B. Uma Maheswari , Rajashri Khanai , Dattaprasad Torse

Brain-computer interfaces (BCIs) promise to extend human movement capabilities by enabling direct neural control of supernumerary effectors, yet integrating augmented commands with multiple degrees of freedom without disrupting natural…

机器人学 · 计算机科学 2025-11-12 Tianyu Jia , Xingchen Yang , Ciaran McGeady , Yifeng Li , Jinzhi Lin , Kit San Ho , Feiyu Pan , Linhong Ji , Chong Li , Dario Farina

Brain-computer interfaces (BCIs) read neural signals directly from the brain to infer motor planning and execution. However, the implementation of this technology has been largely limited to laboratory settings, with few real-world…

Brain computer interface (BCI) provides promising applications in neuroprosthesis and neurorehabilitation by controlling computers and robotic devices based on the patient's intentions. Here, we have developed a novel BCI platform that…

机器人学 · 计算机科学 2017-07-25 Reza Abiri , Griffin Heise , Xiaopeng Zhao , Yang Jiang , Fateme Abiri

Brain-computer interfaces (BCIs) make possible to interact with the external environment by decoding the mental intention of individuals. BCIs can therefore be used to address basic neuroscience questions but also to unlock a variety of…

Motor imagery-based brain-computer interfaces (BCIs) use an individuals ability to volitionally modulate localized brain activity as a therapy for motor dysfunction or to probe causal relations between brain activity and behavior. However,…

Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working…

A Brain Computer Interface (BCI) is a communication system that receives neurological signals from the brain and translates them into control commands for electrical (e.g., computer mouse) and electromechanical (e.g., Wheelchair) devices.…

人机交互 · 计算机科学 2016-10-19 Amin Behdad , Amro Nour , Arash Zereshkian , Cesar Marquez Chin , Milos Popovic

The integration of brain-computer interfaces (BCIs) into the realm of smart wheelchair (SW) technology signifies a notable leap forward in enhancing the mobility and autonomy of individuals with physical disabilities. BCIs are a technology…

人机交互 · 计算机科学 2024-04-30 Shiva Ghasemi , Denis Gracanin , Mohammad Azab

Human-machine interactions are being increasingly explored to create alternative ways of communication and to improve our daily life. Based on a classification of the user's intention from the user's underlying neural activity,…

神经元与认知 · 定量生物学 2020-01-07 Fabrizio De Vico Fallani , Danielle S. Bassett

Brain-computer interfaces (BCIs) constitute a promising tool for communication and control. However, mastering non-invasive closed-loop systems remains a learned skill that is difficult to develop for a non-negligible proportion of users.…

With the recent developments in neuroscience and engineering, it is now possible to record brain signals and decode them. Also, a growing number of stimulation methods have emerged to modulate and influence brain activity. Current…

系统与控制 · 电气工程与系统科学 2024-01-18 Hoda Fares , Margherita Ronchini , Milad Zamani , Hooman Farkhani , Farshad Moradi

Brain-computer interfaces (BCI) are presented as a solution for people with global paralysis, also known as locked-in syndrome (LIS). The targeted population includes the most severe patients, with no residual eye movements, who cannot use…

神经元与认知 · 定量生物学 2023-10-03 Perrine Seguin , Emmanuel Maby , Fabien Perrin , Alessandro Farnè , Jérémie Mattout

A major objective of Brain-Computer interfaces (BCI) is to restore communication and control in patients with severe motor impairments, like people with Locked-in syndrome. These patients are left only with limited eye and eyelid movements.…

人机交互 · 计算机科学 2023-02-14 P Séguin , E Maby , J Mattout

Brain-computer interfaces (BCIs) use brain signals such as electroencephalography to reflect user intention and enable two-way communication between computers and users. BCI technology has recently received much attention in healthcare…

人机交互 · 计算机科学 2024-01-31 Byoung-Hee Kwon , Ji-Hoon Jeong , Seong-Whan Lee

Brain-computer interfaces (BCIs) offer a way to interact with computers without relying on physical movements. Non-invasive electroencephalography (EEG)-based visual BCIs, known for efficient speed and calibration ease, face limitations in…

人机交互 · 计算机科学 2023-11-22 Changxing Huang , Nanlin Shi , Yining Miao , Xiaogang Chen , Yijun Wang , Xiaorong Gao

Myoelectric interfaces enable intuitive and natural control by decoding residual muscle activity, providing an effective pathway for motor restoration in individuals with preserved musculature. However, in patients with severe muscular…

神经元与认知 · 定量生物学 2025-11-26 Sun Ye , Zuo Cuiming , Zhang Rui , Shi Bin , Pang Yajing , Gao Lingyun , Zhao Bowei , Wang Jing , Yao Dezhong , Liu Gang
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