The IEEE Standards Association (IEEE-SA) kicked off a discussion in June at a workshop on Standards and Modularity of Brain-Computer Interfaces and Neuroprosthesessponsored by the U.S. National Institutes of Health. Neuroprostheses may help people who lack motor, sensory, or cognitive skills, which might have been damaged as a result of injury or disease. The NIH brought together regulatory agencies, manufacturers, researchers, and IEEE-SA to discuss how to begin the standards development process.
For BCI devices to be more widely available beyond the research environment, criteria for their safety and effectiveness must be met. Therefore, there is an opportunity for performance standards to be developed.
The cost needs to be brought down as well. Interoperable standards could help, because BCI modules from more manufacturers could be combined.
As a follow-up to the NIH workshop, the IEEE-SA is planning to form a committee to sponsor new standards activities on neurotechnologies, which can be used to capture, transmit, and record brain signals. They can be helpful for rehabilitation purposes, for example, in conjunction with prosthetics and cognitive training. Neurotechnologies also can be used for entertainment and education, such as interacting in augmented and virtual reality environments, as well as interacting with smart home devices and driving semi-autonomous cars.
A full-day standards session was held during the October Brain Machine Interface Workshop at the IEEE Conference on Systems, Man, and Cybernetics. Researchers and manufacturers discussed their current work, and a panel presented an overview of the IEEE-SA standards process and related technical work. At the roundtable discussion that followed, participants suggested standards areas to focus on.
RELATED STANDARDS AND ONGOING PROJECTS
- IEEE 11073’s suite of standards for communications among medical devices helps ensure the interoperability of the devices, including health and fitness products, and of systems for disease management.
- IEEE P1589 Standard for an Augmented Reality Learning Experience Model specifies an overarching integrated conceptual model and the data model specifications for representing activities, learning context and environment, also known as workplace, and potentially other data model components needed for AR-enhanced learning activities.
- IEEE P1918.1 Tactile Internet: Application Scenarios, Definitions and Terminology, Architecture, Functions, and Technical Assumptions defines a framework for the Tactile Internet, including descriptions of various application scenarios, definitions and terminology, functions, and technical assumptions. It encompasses mission-critical applications in manufacturing, transportation, health care, and mobility, as well as noncritical applications such as edutainment and events. The Tactile Internet is a new type of network designed to operate in virtual haptic environments that call for highly sensitive touch and precision, and when reaction time must be no more than a millisecond. In medicine, the Tactile Internet could be used in telesurgery and exoskeleton control, and to assist with the precise movements of remotely controlled robots.
- IEEE 3333.1.1-2015 Standard for Quality of Experience (QoE) and Visual-Comfort Assessments of Three-Dimensional (3D) Contents Based on Psychophysical Studies describes quality-assessment techniques applied in the development of 3-D display devices. The standard introduces a 3-D subjective assessment method that covers the characteristics of human perception, display mechanisms, and viewing environments.
- IEEE P3333.1.2 Standard for the Perceptual Quality Assessment of Three Dimensional (3D) and Ultra High Definition (UHD) Contents establishes methods to assess the quality of 3-D and UHD content based on physiological mechanisms such as perceptual quality and visual attention.
In addition, the IEEE Engineering and Biology Society Standards Committee’s Neurotechnology Working Group produced the 2010–2012 IEEE Recommended Practice for Neurofeedback Systems, which describes the documentation required for instruments and software. Neurofeedback uses real-time displays of brain activity—most commonly electroencephalography—to teach the self-regulation of brain function. Typically, sensors are placed on the scalp to measure activity, with the resulting measurements displayed via video or sound.
The U.S. Food and Drug Administration cited the neurofeedback systems standard as a Recognized Consensus Standard, meaning it was developed by an open and transparent process and provides performance criteria to streamline the review and approval of conforming devices.
This article is part of our November 2016 special issue on technologies for the brain.