Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges

In recent years, new research has brought the field of EEG-based Brain-Computer Interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus on the development of practical BCI technologies that can be brought out of the lab and into real-world applications. In particular, we focus on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT). In pursuit of more practical BCIs for use outside of the lab, in this paper, we identify four application areas where disabled individuals could greatly benefit from advancements in BCI technology, namely,“Communication and Control”, “Motor Substitution”, “Entertainment”, and “Motor Recovery”. We review the current state of the art and possible future developments, while discussing the main research issues in these four areas. In particular, we expect the most progress in the development of technologies such as hybrid BCI architectures, user-machine adaptation algorithms, the exploitation of users’ mental states for BCI reliability and confidence measures, the incorporation of principles in human-computer interaction (HCI) to improve BCI usability, and the development of novel BCI technology including better EEG devices

A new living lab for usability evaluation of ICT and next generation networks for elderly@home

Living Usability Lab for Next Generation Networks (www.livinglab.pt) is a Portuguese industry-academia collaborative R&D project, active in the field of live usability testing, focusing on the development of technologies and services to support healthy, productive and active citizens. The project adopts the principles of universal design and natural user interfaces (speech, gesture) making use of the benefits of next generation networks and distributed computing. Therefore, it will have impact on the general population, including the elderly and citizens with permanent or situational special needs. This paper presents project motivations, conceptual model, architecture and work in progress.info:eu-repo/semantics/acceptedVersio

BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients

This presentation summarises the development of a portable and cost-efficient BCI controlled assistive technology using a non-invasive BCI headset 'OpenBCI' and an open source robotic arm, U-Arm, to accomplish tasks related to rehabilitation, such as access to resources, adaptability or home use. The resulting system used a combination of EEG and EMG sensor readings to control the arm, which could perform a number of different tasks such as picking/placing objects or assist users in eating

Empowering and assisting natural human mobility: The simbiosis walker

This paper presents the complete development of the Simbiosis Smart Walker. The device is equipped with a set of sensor subsystems to acquire user-machine interaction forces and the temporal evolution of user's feet during gait. The authors present an adaptive filtering technique used for the identification and separation of different components found on the human-machine interaction forces. This technique allowed isolating the components related with the navigational commands and developing a Fuzzy logic controller to guide the device. The Smart Walker was clinically validated at the Spinal Cord Injury Hospital of Toledo - Spain, presenting great acceptability by spinal chord injury patients and clinical staf

Are We the Robots? : Man-Machine Integration

We experience and interact with the world through our body. The founding father of computer science, Alan Turing, correctly realized that one of the most important features of the human being is the interaction between mind and body. Since the original demonstration that electrical activity of the cortical neurons can be employed to directly control a robotic device, the research on the so-called Brain-Machine Interfaces (BMIs) has impressively grown. For example, current BMIs dedicated to both experimental and clinical studies can translate raw neuronal signals into computational commands to reproduce reaching or grasping in artificial actuators. These developments hold promise for the restoration of limb mobility in paralyzed individuals. However, as the authors review in this chapter, before this goal can be achieved, several hurdles have to be overcome, including developments in real-time computational algorithms and in designing fully implantable and biocompatible devices. Future investigations will have to address the best solutions for restoring sensation to the prosthetic limb, which still remains a major challenge to full integration of the limb into the user's self-image

Brain-computer interfaces: barriers and opportunities to widespread clinical adoption

Brain-computer Interface (BCI) is an emerging neurotechnology with potential applications involving primarily neurological disorders. There is a rising interest in the use of BCI to address current unmet clinical needs from patients. Despite their therapeutic potential, BCI use is still mostly limited to research stages and its translation into mainstream clinical applications and widespread adoption is lagging. This study revises the current potential clinical applications of BCIs in humans, attempts to understand barriers and opportunities to wider clinical adoption and draws health policy and management implications of BCIs use in medical practice. The methodology followed a two-step approach which included a systematic review of potential clinical applications of BCIs and a qualitative study, using focus group method, to understand and integrate professionals’ experiences, perceptions, thoughts and feelings on the wide clinical adoption of BCIs. Focus groups included professionals from the medical, engineering and management field. BCI clinical applications with more clinical evidence include neurorehabilitation with non-invasive devices and the control of assistive devices with invasive BCIs. Nowadays, several barriers to wider clinical adoption of BCIs, including technological, seem addressable. However, systemic barriers from the health systems to innovation and technological interventions need a comprehensive and multidisciplinary approach to enhance their adoption. Professionals from medicine, engineering and management, working in collaboration in healthcare contexts, are some of the stakeholders important to change the current vision of healthcare towards innovation.As interfaces cérebro-computador (BCI) são uma Neurotecnologia emergente com potencial para serem aplicadas no âmbito clínico, nomeadamente em condições de foro neurológico. Existe um interesse crescente no uso desta tecnologia para ir de encontro às necessidades clínicas de doentes com poucas soluções de tratamento e apoio médico. Apesar das potencialidades das BCI para serem usadas em contexto clínico em humanos, as suas aplicações têm-se limitado a contextos específicos de pesquisa e sem transição para a área da saúde com consequente adoção enquanto ferramenta terapêutica. Com este trabalho pretende-se rever as aplicações clínicas atuais destes dispositivos em humanos, perceber quais as barreiras e oportunidades para a sua adoção em contextos clínicos e retirar ilações do uso de BCI para políticas de saúde e gestão de inovação na prática médica. A metodologia foi dividida em duas fases, que incluíram uma revisão sistemática das potenciais aplicações clínicas de BCI e um estudo qualitativo, usando focus groups, para melhor perceber e integrar as experiências, perceções, ideias e sentimentos de profissionais em relação à adoção de BCI na prática clínica comum. Os focus groups incluíram profissionais das áreas médica, de engenharia e de gestão. As aplicações clínicas com maior nível de evidência para a clínica incluem a neuroreabilitação com BCI não-invasivos e o controlo de dispositivos de assistência com BCI invasivos. Atualmente, diversas barreiras à implementação de BCI em contexto clínico, incluindo o desenvolvimento tecnológico, parecem ser possíveis de ultrapassar num prazo razoável. Contudo, barreiras sistemáticas à inovação e intervenções tecnológicas no âmbito dos sistemas de saúde, apresentam-se como um problema mais complexo e necessitarão de uma abordagem mais globalizada e multidisciplinar para tornar possível a adoção de BCI na prática clínica. Para atingir este objetivo e ultrapassar estas barreiras, profissionais das áreas de medicina, engenharia e gestão devem colaborar e trabalhar em conjunto em contextos de saúde, contribuindo para uma mudança de cultura e tornando os sistemas de saúde mais abertos à inovação

Enhancing brain/neural-machine interfaces for upper limb motor restoration in chronic stroke and cervical spinal cord injury

Operation of assistive exoskeletons based on voluntary control of sensorimotor rhythms (SMR, 8-12 Hz) enables intuitive control of finger or arm movements in severe paralysis after chronic stroke or cervical spinal cord injury (SCI). To improve reliability of such systems outside the laboratory, in particular when brain activity is recorded non-invasively with scalp electroencephalography (EEG), a hybrid EEG/electrooculography (EOG) brain/neural-machine interface (B/NMI) was recently introduced. Besides providing assistance, recent studies indicate that repeated use of such systems can trigger neural recovery. However, important prerequisites have to achieved before broader use in clinical settings or everyday life environments is feasible. Current B/NMI systems predominantly restore hand function, but do not allow simultaneous control of more proximal joints for whole-arm motor coordination as required for most stroke survivors suffering from paralysis in the entire upper limb. Besides paralysis, cognitive impairments including post-stroke fatigue due to the brain lesion reduce the capacity to maintain effortful B/NMI control over a longer period of time. This impedes the applicability in daily life assistance and might even limits the efficacy of neurorehabilitation training. In contrast to stroke survivors, tetraplegics due to cervical SCI lack motor function in both hands. Given that most activities of daily living (ADL) involve bimanual manipulation, e.g., to open the lid of a bottle, bilateral exoskeleton control is required but was not shown yet in tetraplegics. To further enhance B/NMI systems, we first investigated whether B/NMI whole-arm exoskeleton control in hemiplegia after chronic stroke is feasible and safe. In contrast to simple grasping, control of more complex tasks involving the entire upper limb was not feasible with established B/NMIs because high- dimensionality of such multiple joint systems exceeds the bandwidth of these interfaces. Thus, we blended B/NMI control with vision-guidance to receive a semiautonomous whole-arm exoskeleton control. Such setup allowed to divide ADL tasks into a sequence of EEG/EOG-triggered sub-tasks reducing complexity for the user. While, for instance, a drinking task was resolved into EOG-induced reaching, lifting and placing back the cup, grasping and releasing movements were based on intuitive SMR control. Feasibility of such shared vision-guided B/NMI control was assumed when executions were initialized within 3 s (fluent control) and a minimum of 75 % of subtasks were executed within that time (reliable control). We showed feasibility in healthy subjects as well as stroke survivors without report of any side effects documenting safe use. Similarly, feasibility and safety of bilateral B/NMI control after cervical SCI was evaluated. To enable bilateral B/NMI control, established EEG-based grasping and EOG-based releasing or stop commands were complemented with a novel EOG command allowing to switch laterality by performing prolonged horizontal eye movements (>1 s) to the left or to the right. Study results with healthy subjects and tetraplegics document fluent initialization of grasping motions below 3 s as well as safe use as unintended grasping could be stopped before a full motion was conducted. Superiority of novel bilateral control was documented by a higher accuracy of up to 22 % in tetraplegics compared to a bilateral control without prolonged EOG command. Lastly, as reliable B/NMI control is cognitively demanding, e.g., by imagining or attempting the desired movements, we investigated whether heart rate variability (HRV) can be used as biomarker to predict declining control performance, which is often reported in stroke survivors due to their cognitive impairments. Referring to the close brain-heart connection, we showed in healthy subjects that a decline in HRV is specific as well as predictive to a decline in B/NMI control performance within a single training session. The predictive link was revealed by a Granger-causality analysis. In conclusion, we could demonstrate important enhancements in B/NMI control paradigms including complex whole-arm exoskeleton control as well as individual performance monitoring within a training session based on HRV. Both achievements contribute to broaden the use as a standard therapy in stroke neurorehabilitation. Especially the predictive characteristic of HRV paves the way for adaptive B/NMI control paradigms to account for individual differences among impaired stroke survivors. Moreover, we also showed feasibility and safety of a novel implementation for bilateral B/NMI control, which is necessary for reliable operation of two hand-exoskeletons for bimanual ADLs after SCI

Boosting brain–computer interfaces with functional electrical stimulation: potential applications in people with locked-in syndrome

Individuals with a locked-in state live with severe whole-body paralysis that limits their ability to communicate with family and loved ones. Recent advances in brain–computer interface (BCI) technology have presented a potential alternative for these people to communicate by detecting neural activity associated with attempted hand or speech movements and translating the decoded intended movements to a control signal for a computer. A technique that could potentially enrich the communication capacity of BCIs is functional electrical stimulation (FES) of paralyzed limbs and face to restore body and facial movements of paralyzed individuals, allowing to add body language and facial expression to communication BCI utterances. Here, we review the current state of the art of existing BCI and FES work in people with paralysis of body and face and propose that a combined BCI-FES approach, which has already proved successful in several applications in stroke and spinal cord injury, can provide a novel promising mode of communication for locked-in individuals