Exploring the Intersection of Brain–Computer Interfaces and Quantum Sensing: A Review of Research Progress and Future Trends
Kun Liao, Zhaochu Yang, Tao Dong, Libo Zhao, Nuno Miguel Matos Pires, Carlos Alberto Dorao, Bjorn Torger Stokke, Lars Eric Roseng, Wen Liu, Zhuangde Jiang
Abstract Brain–computer interfaces (BCIs) can revolutionize how humans interact with technology, but several scientific and technological challenges must be addressed to realize their full potential. Recent developments in quantum‐based sensing methods offer promising solutions to some of these challenges. This review provides an overview of the progress, challenges, and prospects of BCIs research and discuss the feasibility of integrating quantum sensor technology in BCI systems. The applications of quantum sensing in BCIs research are reviewed and the solution based on quantum sensor technology to overcome some of the challenges associated with BCI systems is proposed. The potential of quantum sensor technology for the future development of BCIs is emphasized. Overall, this review highlights quantum sensor technology's significant potential for future development of BCI.
Abstract Brain–computer interfaces (BCIs) can revolutionize how humans interact with technology, but several scientific and technological challenges must be addressed to realize their full potential. Recent developments in quantum‐based sensing methods offer promising solutions to some of these challenges. This review provides an overview of the progress, challenges, and prospects of BCIs research and discuss the feasibility of integrating quantum sensor technology in BCI systems. The applications of quantum sensing in BCIs research are reviewed and the solution based on quantum sensor technology to overcome some of the challenges associated with BCI systems is proposed. The potential of quantum sensor technology for the future development of BCIs is emphasized. Overall, this review highlights quantum sensor technology's significant potential for future development of BCI.
This research explores the potential of quantum computing to revolutionize brain-computer interfaces (BCIs) by providing a fundamentally different approach to simulating neuronal activity and information transfer. The core claim posits that quantum algorithms can accurately model the intricate quantum effects within neural networks, leading to more precise brain interface design and therapeutic interventions. This study will detail the challenges and opportunities inherent in harnessing quantum mechanics for BCI applications, focusing on the unique capabilities of quantum bits (qubits) and their potential to overcome limitations of classical computing. We will examine current research directions, including the development of specialized quantum algorithms for neural network modeling, and discuss the technical and theoretical hurdles that must be addressed before practical implementation becomes feasible.
This paper explores the potential of quantum computing to revolutionize brain-computer interfaces (BCIs) and accelerate complex computations within the brain. We propose a novel architecture for a quantum-enhanced BCI, leveraging quantum algorithms to efficiently decode brain signals and translate them into optimized quantum operations. The core mechanism centers around a quantum-accelerated signal processing pipeline, aiming to significantly increase the speed and accuracy of neural control tasks. The paper details the design of the BCI system, outlining the quantum algorithms employed, the hardware components involved, and a preliminary analysis of the expected performance improvements. We conclude by highlighting the novelty and potential impact of this approach, emphasizing its promise for advancements in neuroscience, cognitive computing, and control systems.
This chapter presents a quantum computing-based approach to study and harness neuronal correlates of mental activity for the development of Brain-Computer Interface (BCI) systems. It introduces the notion of a logic of the mind, where neurophysiological data are encoded as logical expressions representing mental activity. Effective logical expressions are likely to be extensive, involving dozens of variables. Large expressions require considerable computational power to be processed. This is problematic for BCI applications because they require fast reaction times to execute sequences of commands. Quantum computers hold much promise in terms of processing speed for some problems, including those involving logical expressions. Hence, we propose to use quantum computers to process the logic of the mind. The chapter begins with an introduction to BCI and the electroencephalogram, which is the neurophysiological signal that is normally used in BCI. Then, it briefly discusses how the EEG corresponds to mental states, followed by an introduction to the logic of the mind. After that, there is an overview of quantum computing, focusing on the basics deemed necessary to understand how it processes logical expressions. An example of a BCI system is presented. In a nutshell, the system reads the EEG and builds logical expressions, which are sent to a quantum computer to solve them. In turn, the system converts the results into sounds by means of a bespoke synthesiser. Essentially, the BCI here is a musical instrument controlled by the mind of the player. Our BCI is a proof-of-concept aimed at demonstrating how quantum computing may support the development of sophisticated BCI systems. The remaining of the chapter is devoted to technical and practical considerations on the limitations of current quantum computing hardware technology and scalability of the system.
Purpose The purpose of this paper is to provide details of developments in quantum technologies and consider their potential applications in robotics. Design/methodology/approach Following a short introduction, this study first provides an overview of the global quantum technology landscape. It then discusses developments in quantum computing and sensing technologies. Potential applications in robotics are then considered and finally, brief conclusions are drawn. Findings Quantum technologies are the topic of a rapidly growing global R&D effort. Quantum computing has the potential to conduct conventional computations far more rapidly than traditional computers and solve complex problems that are presently challenging or impossible. If realised, robotic applications could include enhanced route planning, machine learning and data fusion. Quantum position and magnetic field sensors have the potential to revolutionise navigation systems in airborne, land and marine robots and overcome limitations of GPS and inertial measurement units. Magnetic sensors also have a role in health care in the control of robotic prostheses and exoskeletons and in brain–computer interface techniques. Quantum radar, lidar and imaging systems stand to outperform their conventional counterparts, and applications are anticipated in military and civilian robots. Quantum technologies are still at an early stage of development, and much progress will be made in the future, opening up many further robotic applications. Originality/value This study provides an insight into quantum technology developments and their potential applications in robotics.
As the importance of quantum technologies is rapidly rising, e.g., in cyber security domain, further surge applications of such systems in various domains are expected in near term.In fact, the integration of quantum technologies with classical systems is inevitable in many disciplines, particularly as quantum devices are becoming more accessible.Among the various areas in which quantum technologies can potentially provide important complementary contributions, the area of Brain Computer Interface (BCI) has yet to be explored.The two areas of experimental photon quantum mechanics and BCI are brought together in this paper, for the first time.The applications of EEG signals to the control of mechanical systems, for example controlling drones remotely with brain wave signals, have been studied by various researchers.This paper presents the mechanism in which an EEG device is used to control the quantum properties in quantum experimental setups.In particular, a brain wave signal is used in changing the polarization of photons using a motorized half-waveplate in pre-built quantum entanglement and quantum cryptography experiments.This, in fact shows the mechanism on how quantum-BCI can be integrated as a system, before BCIbased control can be applied to hybrid classical-quantum systems, such as quantum experiments mounted on robotic platforms.The mechatronics of such systems is explained in this paper.This paper also outlines the necessary educational aspects of quantum related topics for students who have not traditionally exposed to quantum mechanics in their discipline, such as mechanical, aerospace, and electromechanical engineering students, which indeed is an essential step in preparing the next generation of engineering workforce for the fast-changing industry, the R&D sectors and academia.The quantum mechanics education and training steps in the mechatronics course and senior design projects are particularly promoted and discussed here.
The current rise of quantum technology is compelled by quantum sensing research. Thousands of research labs are developing and testing a broad range of sensor prototypes. However, there is a lack of knowledge about specific applications and real-world use cases where the benefits of these sensors will be most pronounced. This study presents a comprehensive review of quantum sensing state-of-practice. It also provides a detailed analysis of how quantum sensing overcomes the existing limitations of sensor-driven systems’ precision and performance. Based on the review of over 500 quantum sensor prototype reports, we determined four groups of quantum sensors and discussed their readiness for commercial usage. We concluded that quantum magnetometry and quantum optics are the most advanced sensing technologies with empirically proven results. In turn, quantum timing and kinetics are still in the early stages of practical validation. In addition, we defined four systems domains in which quantum sensors offer a solution for existing limitations of conventional sensing technologies. These domains are 1) GPS-free positioning and navigating services, 2) time-based operations, 3) topological visibility, and 4) environment detection, prediction, and modeling. Finally, we discussed the current constraints of quantum sensing technologies and offered directions for future research.