Concerns in the Blurred Divisions between Medical and Consumer Neurotechnology

An XYZ-axis Matrix Approach for the Integration of Neuroscience and Neuroethics

The recent, unprecedented advancement in neuroscience has led to new discoveries about the human brain and its function. Yet at the same time, it has spurred novel ethical and regulatory issues, and the field of neuroethics has emerged as an interdisciplinary endeavor to address these issues. Across the globe, extensive efforts have been underway to achieve the integration of neuroscience and Neuroethics, with active engagement not only from academia but also from the government, the public, and industry. However, in some countries, integrating neuroscience and neuroethics has proved to be a particularly challenging task. For example, in South Korea, the government has primarily driven the integration effort, and only a small group of researchers is properly trained for conducting an interdisciplinary evaluation of ethical, legal, social, and cultural implications (ELSCI) of neurotechnology. On the basis of the last few years of experience pursuing a government-funded neuroethics project in South Korea, we developed a new operational framework to provide practical guidance on ELSCI research. This framework consists of the X, Y, and Z axes; the X-axis represents a target neurotechnology, the Y-axis represents different developmental stages of the technology, and the Z-axis represents ELSCI issues that may arise from the development and use of the neurotechnology. Here we also present a step-by-step workflow to apply this matrix framework, from organizing a panel for a target neurotechnology to facilitating stakeholder discussion through public hearings. This framework will enable meaningful integration of neuroscience and neuroethics to promote responsible innovation in neuroscience and neurotechnology.

Deep Mobile Linguistic Therapy for Patients with ASD

Autistic spectrum disorder (ASD) is one of the most complex groups of neurobehavioral and developmental conditions. The reason is the presence of three different impaired domains, such as social interaction, communication, and restricted repetitive behaviors. Some children with ASD may not be able to communicate using language or speech. Many experts propose that continued therapy in the form of software training in this area might help to bring improvement. In this work, we propose a design of software speech therapy system for ASD. We combined different devices, technologies, and features with techniques of home rehabilitation. We used TensorFlow for Image Classification, ArKit for Text-to-Speech, Cloud Database, Binary Search, Natural Language Processing, Dataset of Sentences, and Dataset of Images with two different Operating Systems designed for Smart Mobile devices in daily life. This software is a combination of different Deep Learning Technologies and makes Human-Computer Interaction Therapy very easy to conduct. In addition, we explain the way these were connected and put to work together. Additionally, we explain in detail the architecture of software and how each component works together as an integrated Therapy System. Finally, it allows the patient with ASD to perform the therapy anytime and everywhere, as well as transmitting information to a medical specialist.

Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier

The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9th, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering topics in BCI (also called brain-machine interface) research. As in the past, workshops covered the breadth of topics in BCI. Some workshops provided detailed examinations of specific methods, hardware, or processes. Others focused on specific BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and increase the ease of comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were both the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, presents an overview of the discussion topics, and describes the conclusion, challenges, or initiatives that resulted from the interactions and discussion at the workshop.

A Roadmap Towards Standards for Neurally Controlled End Effectors

The control and manipulation of various types of end effectors such as powered exoskeletons, prostheses, and ‘neural’ cursors by brain-machine interface (BMI) systems has been the target of many research projects. A seamless “plug and play” interface between any BMI and end effector is desired, wherein similar user's intent cause similar end effectors to behave identically. This report is based on the outcomes of an IEEE Standards Association Industry Connections working group on End Effectors for Brain-Machine Interfacing that convened to identify and address gaps in the existing standards for BMI-based solutions with a focus on the end-effector component. A roadmap towards standardization of end effectors for BMI systems is discussed by identifying current device standards that are applicable for end effectors. While current standards address basic electrical and mechanical safety, and to some extent, performance requirements, several gaps exist pertaining to unified terminologies, data communication protocols, patient safety and risk mitigation.