ISO/IEC TS 27571:2026

Information technology - Brain-computer interfaces - Data format for non-invasive brain information collection

ISO/IEC TS 27571:2026 specifies the basic brain–computer interface (BCI) data format including the definition of basic data elements, technology-specific information and metadata, design of an extensible and modular data structure, specification of metadata and annotation information, and the development of a standardized data format and naming convention for BCI data. This document is applicable to non-invasive BCI technologies, such as electroencephalography (EEG), magnetoencephalography (MEG), functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI), and provides a comprehensive approach to BCI metadata formats in the product development environment. It takes into consideration various applications, ranging from neurological rehabilitation to human-computer interaction.

General Information

• Status: Published
• Publication Date: 21-Apr-2026
• ICS: 35.020 - Information technology (IT) in general
• ICS: 35.200 - Interface and interconnection equipment
• Technical Committee: ISO/IEC JTC 1/SC 43 - Brain-computer Interfaces
• Current Stage: PPUB - Publication issued
• Start Date: 22-Apr-2026
• Completion Date: 15-May-2026

Overview

ISO/IEC TS 27571:2026 is a technical specification that defines a standardized data format for the collection of brain information using non-invasive brain-computer interface (BCI) technologies. Managed by the International Electrotechnical Commission (IEC), this standard provides a comprehensive framework for consistent structuring, storage, and annotation of brain data captured through technologies such as electroencephalography (EEG), magnetoencephalography (MEG), functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI).

By establishing common data elements, extensible modular data structures, and detailed metadata requirements, ISO/IEC TS 27571:2026 addresses the challenges of interoperability and data integration in multi-modal BCI systems. The standard supports various applications, from neurological rehabilitation to advanced human-computer interaction, and is essential for facilitating effective data sharing, quality assurance, and collaborative BCI research worldwide.

Key Topics

• Unified Data Structure: The specification introduces an extensible and modular data structure, allowing easy integration and management of different non-invasive BCI technologies. This supports scalability and adaptability as new BCI methods emerge.
• Metadata and Annotation: Detailed requirements for metadata and annotations enable comprehensive contextual information to accompany each dataset. This includes device settings, subject demographics, session details, and experimental conditions.
• Standard Naming Conventions: A consistent file naming scheme enhances data organization, retrieval, and traceability across research projects and product development environments.
• Security by Design: The standard emphasizes security features, including data encryption and access controls, protecting the confidentiality and integrity of sensitive BCI data.
• Technology Compatibility: Supports integration of data from EEG, MEG, fNIRS, and fMRI systems, ensuring the format is compatible with a broad array of popular and emerging BCI technologies.

Applications

The standardized data format defined by ISO/IEC TS 27571:2026 offers significant value across multiple domains:

• Research Collaboration: Allows researchers from different organizations or disciplines to share, combine, and analyze brain data easily, accelerating innovation and multidisciplinary studies.
• Healthcare and Neurorehabilitation: Facilitates consistent and accurate documentation of brain activity in clinical settings, crucial for neurological assessment and rehabilitation progress tracking.
• Product Development: Enables device manufacturers and software developers to implement interoperable solutions, reducing integration costs and enhancing market access.
• Human-Computer Interaction: Supports the development and validation of adaptive interfaces and assistive technologies that respond to user intentions through brain signals.
• Data Management and Compliance: Strengthens data governance practices by ensuring all relevant metadata and security measures are incorporated from the outset, aiding in regulatory compliance and ethical data use.

Related Standards

Implementing ISO/IEC TS 27571:2026 is often complemented by adherence to related standards, which provide clarity on terminology, metadata repositories, and existing data formats:

• ISO/IEC 8663: Information technology - Brain-computer interfaces - Vocabulary; offers standardized definitions critical for consistent communication.
• ISO/TS 21526:2019: Health informatics - Metadata repository requirements (MetaRep); guides metadata structuring and repository best practices.
• BIDS (Brain Imaging Data Structure): Focuses on structured metadata for neuroimaging, aligning with some principles in TS 27571 but not covering the full scope of BCI integration.
• EDF (European Data Format): A long-standing format for EEG and related physiological signals, referenced for specific use cases but less modular than the structure in this specification.

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ISO/IEC TS 27571:2026 establishes a future-ready, comprehensive data format for non-invasive BCI information collection. Its adoption strengthens data interoperability, security, and analytic depth across BCI research, clinical applications, and product development, making it a foundational reference for any organization working with brain-computer interfaces.

Standards Content (Sample)

ISO/IEC TS 27571
Edition 1.0 2026-04
TECHNICAL
SPECIFICATION
Information technology - Brain-computer interfaces - Data format for non-
invasive brain information collection
ICS 35.020; 35.200  ISBN 978-2-8327-1203-0

ISO/IEC TS 27571: 2026-04(en)
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CONTENTS
FOREWORD . 2
INTRODUCTION . 3
1 Scope . 4
2 Normative references . 4
3 Terms and definitions . 4
4 Abbreviated terms. 5
5 Basic data elements . 5
5.1 Electroencephalography (EEG) . 5
5.2 Magnetoencephalography (MEG) . 5
5.3 Functional near-infrared spectroscopy (fNIRS) . 5
5.4 Functional magnetic resonance imaging (fMRI) . 6
6 Extensible and modular data . 6
7 Metadata and annotation information . 8
8 Standardized data format . 9
8.1 Overview . 9
8.2 BCI devices . 9
8.3 Subjects . 10
8.4 Data acquisition sessions . 10
8.5 Data files . 10
8.5.1 Overview . 10
8.5.2 Data acquisition . 11
8.5.3 Data processing . 11
8.5.4 Annotations . 12
8.5.5 Security by design. 12
9 Naming convention for BCI data files . 12
10 Integration of multiple BCI technologies . 13
10.1 Overview . 13
10.2 Compatibility with existing BCI technologies . 13
10.3 Multimodal data integration and management for BCI technologies . 14
11 Raw data format selection specification . 16
12 Required metadata information . 16
Bibliography . 18

Figure 1 – Non-invasive unified BCI data formatting procedure . 6
Figure 2 – Example of modular data structure for non-invasive data format . 7
Figure 3 – Example of ETSI ENI format metadata and annotation structure . 8
Figure 4 – Naming convention of data file . 12
Figure 5 – File common dataset and each modality data designation . 14
Figure 6 – Required data elements and extraction of required items . 15
Figure 7 – Element composition and required itemized data . 15
Figure 8 – Raw data converter and data combination . 16

Table 1 – Required metadata elements . 17
Information technology -
Brain–computer interfaces -
Data format for non-invasive brain information collection

FOREWORD
1) ISO (the International Organization for Standardization) and IEC (the International Electrotechnical Commission)
form the specialized system for worldwide standardization. National bodies that are members of ISO or IEC
participate in the development of International Standards through technical committees established by the
respective organization to deal with particular fields of technical activity. ISO and IEC technical committees
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2) The formal decisions or agreements of IEC and ISO on technical matters express, as nearly as possible, an
international consensus of opinion on the relevant subjects since each technical committee has representation
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3) IEC and ISO documents have the form of recommendations for international use and are accepted by IEC and
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IEC and ISO documents is accurate, IEC and ISO cannot be held responsible for the way in which they are used
or for any misinterpretation by any end user.
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8) Attention is drawn to the Normative references cited in this document. Use of the referenced publications is
indispensable for the correct application of this document.
9) IEC and ISO draw attention to the possibility that the implementation of this document may involve the use of (a)
patent(s). IEC and ISO take no position concerning the evidence, validity or applicability of any claimed patent
rights in respect thereof. As of the date of publication of this document, IEC and ISO had not received notice of
(a) patent(s), which may be required to implement this document. However, implementers are cautioned that this
may not represent the latest information, which may be obtained from the patent database available at
https://patents.iec.ch and www.iso.org/patents. IEC and ISO shall not be held responsible for identifying any or
all such patent rights.
ISO/IEC TS 27571 has been prepared by subcommittee 43: Brain–computer interfaces, of
ISO/IEC joint technical committee 1: Information technology. It is a Technical Specification.
The text of this Technical Specification is based on the following documents:
Draft Report on voting
JTC1-SC43/185/DTS JTC1-SC43/205/RVDTS

Full information on the voting for its approval can be found in the report on voting indicated in
the above table.
The language used for the development of this Technical Specification is English.
This document was drafted in accordance with ISO/IEC Directives, Part 2, and developed in
accordance with ISO/IEC Directives, Part 1, and the ISO/IEC Directives, JTC 1 Supplement
available at www.iec.ch/members_experts/refdocs and www.iso.org/directives.

INTRODUCTION
Brain–computer interfaces (BCIs) have emerged as a promising area of research with
applications spanning from neurorehabilitation to human–computer interaction. Non-invasive
BCI technologies such as electroencephalography (EEG), magnetoencephalography (MEG),
functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging
(fMRI) have contributed significantly to our understanding of the human brain. [1] However,
the lack of a standardized data format for these diverse BCI technologies poses challenges to
data sharing, integration and analysis. This document specifically addresses the integration
challenges posed by multi-modal BCI systems, ensuring that data from different technologies
can be combined effectively and efficiently. By establishing a uniform data format, this
document facilitates deeper insights into neurological processes and enhances the practical
deployment of BCI technologies across various fields.
To address this issue, this document provides a description of the current state-of-the-art and
the need for a data fusion system to integrate and analyse data from different non-invasive BCI
technologies. This document focuses on the following components: defining basic data
elements for each technology, identifying technical information and metadata, designing an
extensible and modular data structure, specifying metadata and annotation information for data
comprehension and traceability, and establishing a unified data format for consistent data
integration.
Data fusion demands situational awareness. It is a set of closed control loops that are
responsible for
a) ingesting each type of data and applying appropriate processing (e.g. data deduplication
and cleansing and anonymization),
b) normalizing those data into a common language using a consensual vocabulary,
c) semantically enriching the normalized data based on context,
d) understanding the normalized data in order to make decisions about the meaning of the
data, and
e) recording this understanding as a set of conclusions.
The resulting standardization will accelerate advancements in BCI research and applications
by promoting consistent data organization, enhancing data quality, and enabling more effective
collaboration among researchers and practitioners in the field.

___________
Numbers in square brackets refer to the Bibliography.
1 Scope
This document specifies the basic brain–computer interface (BCI) data format including the
definition of basic data elements, technology-specific information and metadata, design of an
extensible and modular data structure, specification of metadata and annotation information,
and the development of a standardized data format and naming convention for BCI data. This
document is applicable to non-invasive BCI technologies, such as electroencephalography
(EEG), magnetoencephalography (MEG), functional near-infrared spectroscopy (fNIRS) and
functional magnetic resonance imaging (fMRI), and provides a comprehensive approach to BCI
metadata formats in the product development environment. It takes into consideration various
applications, ranging from neurological rehabilitation to human–computer interaction.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content
constitutes requirements of this document. For dated references, only the edition cited applies.
For undated references, the latest edition of the referenced document (including any
amendments) applies.
ISO/IEC 8663, Information technology - Brain–computer interfaces - Vocabulary
ISO/TS 21526:2019, Health informatics - Metadata repository requirements (MetaRep)
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO/IEC 8663 and the
following apply.
ISO and IEC maintain terminology databases for use in standardization at the following
addresses:
– IEC Electropedia: available at https://www.electropedia.org/
– ISO Online browsing platform: available at https://www.iso.org/obp
3.1
annotation
specific type of metadata that provides additional information or explanation about a concept
3.2
application programming interface
API
interface used for communication between software applications
3.3
dataset
collection of related data used for a common purpose or task, organized in a structured format
3.4
extensibility
capability of a system to be expanded with new features
3.5
interface
shared boundary across which two or more separate components of a computer system
exchange information
3.6
modularity
ability to separate and recombine selected elements of a system
Note 1 to entry: Modularity is typically facilitated by software architecture designed for data fusion.
3.7
data encryption
conversion of plaintext into ciphertext using an encryption algorithm to protect the confidentiality
of the stored or transmitted data
4 Abbreviated terms
EEG electroencephalography
ENI experiential networked intelligence
ETSI European Telecommunications Standards Institute
fNIRS functional near-infrared spectroscopy
fMRI functional magnetic resonance imaging
LED light emitting diode
MEG magnetoencephalography
5 Basic data elements
5.1 Electroencephalography (EEG)
Electroencephalography (EEG) measures the electrical activity of the brain through electrodes
placed on the scalp. Basic data elements for EEG include timestamps, channel labels, electrode
type (wet, semi-wet, or dry), number and positions of electrodes, and whether electrodes are
active or passive. The data set also includes the sampling rate and raw voltage values.
Additionally, information about the reference electrode and ground electrode, filtering settings,
and electrode impedance should be included to ensure accurate data interpretation and
analysis. The ground electrode provides a stable zero-voltage point, which is essential for
reducing electrical noise and improving the overall quality of the EEG data.
5.2 Magnetoencephalography (MEG)
Magnetoencephalography (MEG) records the magnetic fields generated by neuronal currents
in the brain. Basic data elements for MEG include timestamps, channel labels, sensor positions,
sampling rate, and raw magnetic field values. Technology-specific information for MEG consists
of sensor types (e.g. magnetometers, gradiometers), reference sensors, and noise reduction
techniques.
5.3 Functional near-infrared spectroscopy (fNIRS)
Functional near-infrared spectroscopy (fNIRS) measures changes in haemoglobin
concentration in the brain using near-infrared light. Basic data elements for fNIRS include
timestamps, channel labels that specify the positions and types of light sources (LEDs or lasers)
and detectors, optode positions, sampling rate, and raw optical density values. Wavelengths of
near-infrared light, differential pathlength factor, and baseline correction methods should also
be specified as technology-specific information.
5.4 Functional magnetic resonance imaging (fMRI)
Functional magnetic resonance imaging (fMRI) detects changes in blood flow in the brain using
magnetic resonance imaging. Basic data elements for fMRI include timestamps, voxel
coordinates, slice timing, repetition time, and raw blood-oxygen-level-dependent (BOLD) signal
values. Information about the MRI scanner model, magnetic field strength, echo time, and
spatial resolution should be included as technology-specific information.
6 Extensible and modular data
An extensible and modular data structure allows for the integration of various non-invasive BCI
technologies and facilitates the addition of new technologies in the future. The hierarchical
structure organizes data into modular components, such as technology-specific subfolders and
data files. Standard interfaces enable seamless data exchange and interoperability across
different BCI devices and platforms. This approach ensures that each technology's unique
requirements are accommodated while maintaining a consistent structure for data storage and
analysis. Figure 1 illustrates the unified data formatting procedure applied to non-invasive BCI
technologies.
Figure 1 – Non-invasive unified BCI data formatting procedure
The following example assumes data from four different non-invasive BCI technologies: EEG,
MEG, fNIRS, and fMRI. An extensible and modular data structure for these technologies can
be created by the following steps.
Create a top-level folder for the entire dataset, e.g. "BCI_data".
Within the "BCI_data" folder, create subfolders for each technology: "EEG", "MEG", "fNIRS",
and "fMRI" as needed. These subfolders will house the respective data files and any
technology-specific metadata or auxiliary files.
Each technology-specific folder includes multiple subject-specific folders, labelled, for example,
as "Subject_001" and each subject includes subject metadata with corresponding filenames like
EEG_ST_001_Tl_001_mi_20230410_001.json. This structure effectively isolates the data for
each subject, simplifying the management and access to individual datasets. It ensures that
data pertaining to each subject are organized and maintained separately, which minimizes
errors in data handling and enhances data security.
Within each subject's folder, data are meticulously organized into session-specific subfolders,
such as "Session_001." These folders are crucial as they contain various types of data:
"Raw_data", "Processed_data", and metadata and annotation information, with corresponding
filenames like EEG_ST_001_Sn_001_Tl_001_mi_20230410_001.json. This arrangement
ensures that all related data and information are systematically catalogued, facilitating easy
retrieval and analysis.
Develop standard interfaces or APIs to facilitate data exchange and interoperability between
different BCI devices and platforms. These interfaces can be built upon common data structures
and exchange formats, such as JSON or XML, to ensure compatibility across various
technologies.
To accommodate future BCI technologies, this modular structure allows for the easy addition of
new subfolders and data files. By following the same naming conventions and implementing the
necessary interfaces, new technologies can be smoothly integrated into the existing data
structure.
The data file format specifies the organization of data files within a directory structure that
reflects the hierarchy and relationships between different types of collected data. This structure
is designed to ensure that data files are systematically categorized, making them easily
accessible and maintainable for current use and future reference. An example of this modular
directory organization is shown in Figure 2.

Figure 2 – Example of modular data structure for non-invasive data format
7 Metadata and annotation information
Metadata and annotations should be used to increase the specificity of both the data format
and the understanding of the data for the data fusion system. Metadata includes task or event
description, participant information, recording information, and data processing history.
Annotation information consists of event markers, stimulus information, and behavioural
responses, which are essential for accurate data analysis and interpretation. Metadata and
annotation information may be used to provide descriptive information, prescriptive information,
or both, about fundamental managed entities such as context. This in turn enables differences
in situations (e.g. the same experiment with the same patient) to be identified when the context
of the exper
...