Residential buildings with brain-computer interface functionality: An elevator case study

Brain–computer interfaces (BCI) are systems that use signals recorded from the brain to enable communication and control applications. One of the most important applications of BCI technology is that enables people who are severely paralyzed by amyotrophic lateral sclerosis, brainstem stroke, or other disorders to communicate, operate computer programs, or even control numerous devices. Moreover, elevators are probably the best option for disabled persons to expand their access and mobility within a house or a building. In this study, a prototype application is presented, together with an experimental setup of a BCI system that attempts to control an elevator. Practical application Many researchers are dealing with BCI systems that give the possibility to disabled people to control a variety of devices from wheelchairs to different home appliances, using the signals of their brain and forming a smart home services framework. This work comes to support this effort by presenting a case study, as a proof of concept, for an elevator BCI system that could be part of a complete “smart” home BCI system. The presented experimental setup proves that elevators with BCI functionalities are practically feasible and in an affordable cost, and that they could be a significant element within a “smart” residential building.

MSC 2021 Virtual E-Abstract

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Single-Channel Selection for Detecting Steady-State Visual Evoked Potentials in a Brain-Computer Interface Speller

Purpose: Brain-Computer Interface (BCI) provides a secondary communication pathway for patients with neuromuscular diseases such as amyotrophic lateral sclerosis (ALS) or brainstem stroke in which they are almost incapacitated to move or talk. BCI enacts neural oscillations to generate a command signal for machines to operate desired tasks instead of patients. Steady-State Visual Evoked Potential (SSVEP) is the brain response to a visual stimulus, with the same frequency as its eliciting signal (or its harmonics), that has been widely used in BCI environments. In order to provide a more convenient situation for BCI users, we aim to find the best single-channel EEG, which results in the highest accuracy for detecting SSVEP. Materials and Methods: We developed a Deep Convolutional Neural Network with single-channel EEG as input to classify a 40-class SSVEP; each class represents a stimulus, which has been acquired from 35 subjects. We used 3.5 s windows of the data (Trials of 3.5 seconds length for each class) to train our model and leave-one-subject-out cross-validation for the testing. Results: The proposed method resulted in the average classification accuracy of 74.30%±20.85 and Information Transfer Rate (ITR) of 57.51 bpm which outperforms the previous single-channel SSVEP BCIs in terms of ITR. Also, the O1 channel achieved the best performance criteria among the channels in the occipital and parietal lobes, which seems reasonable according to previous researches for finding the location of neurons, responsible for visual tasks in the brain. Conclusion: In this study, we dedicated our efforts to reduce the number of EEG channels to a single channel while proposing a deep learning strategy for an SSVEP-based BCI speller to make it more feasible for patients whose lives are dependent on such systems. The overall results, although not ideal, open a new promising window toward a feasible BCI system.

Pontine hemorrhage presenting as Foville’s syndrome

Foville’s syndrome, also known as inferior medial pontine syndrome is one of the rare brainstem stroke syndromes with only few cases reported worldwide occurring due to involvement of the infero-medial aspect of pons. Condition is characterised by various cluster of neurological features as a result of defect in multiple vital areas like cortico spinal tract, medial lemniscus, middle cerebral peduncle, facial nerve and abducens nerve involvement. We reported one such rare case of a patient with no known systemic co-morbidity, who presented with sudden onset diplopia, lagophthalmos and contralateral weakness of limbs. On evaluation with computed tomography imaging, hemorrhage at the level of inferior pons was found. Patient subsequently treated and commenced on physiotherapy for rehabilitation.

Brainstem stroke presenting as isolated bilateral ptosis

Pure midbrain infarctions not involving surrounding structures are an uncommon clinical phenomenon. A midbrain infarction that results in isolated bilateral ptosis as the only neurological deficit is much rarer and an easy diagnosis to miss; therefore, potentially leading to further downstream complications. We describe the case of an elderly patient who presented with isolated bilateral ptosis, initially thought to be consequent to myasthenia gravis but subsequently identified to have a perforator infarct in the midbrain, resulting in his symptoms.