ISO/TS 22077-5:2021

TECHNICAL ISO/TS
SPECIFICATION 22077-5
First edition
2021-04
Health informatics — Medical
waveform format —
Part 5:
Neurophysiological signals
Reference number
©
ISO 2021
© ISO 2021
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ii © ISO 2021 – All rights reserved

Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Symbols and abbreviated terms . 1
5 General . 2
5.1 Overview of the rules . 2
5.2 Configuration of waveform data . 2
5.3 Time synchronization . 3
6 Waveform encoding . 5
6.1 General . 5
6.1.1 Application of EEG studies . 5
6.1.2 Full disclosure waveforms . 6
6.1.3 Intermittent record waveforms . 6
6.2 Waveform class . 7
6.2.1 General. 7
6.2.2 Waveform Class for EEG, PSG, EP, EMG . 7
6.3 Waveform attributes (lead names) . 9
6.3.1 Waveform code . 9
6.3.2 EEG .10
6.3.3 PSG, EOG, EMG, EP, RESP .10
6.3.4 ECG .11
6.4 Sampling attributes .12
6.4.1 General.12
6.4.2 MWF_IVL (0Bh): Sampling rate .12
6.4.3 MWF_SEN (0Ch): Sampling resolution .13
6.5 Frame attributes .13
6.6 Pointer .13
6.7 Filter .14
7 Event information .14
7.1 General .14
7.2 Measurement status – related events.15
Annex A (informative) MFER conformance statement .16
Annex B (informative) EEG electrode code .17
Annex C (informative) Example of waveform encoding .23
Bibliography .34
Foreword
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This document was prepared by Technical Committee ISO/TC 215, Health informatics.
A list of all parts in the ISO 22077 series can be found on the ISO website.
Any feedback or questions on this document should be directed to the user’s national standards body. A
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iv © ISO 2021 – All rights reserved

Introduction
Neurophysiological signals are used to monitor and assess an individual’s brain activity for a wide array
of clinical examinations including sleep polysomnography (PSG), determination of brain death, evoked
potentials (EP), and electromyography (EMG).
Electroencephalography (EEG) is an electrophysiological monitoring method to record electrical
activity of the brain. It is typically non-invasive, with multiple electrodes placed along the scalp (see
Figures B.1 and B.2). Diagnostic applications generally focus on the spectral content of EEG, that is, the
type of neural oscillations (popularly called "brain waves") that can be observed in EEG signals. EEG
is most often used to diagnose epilepsy, which causes abnormalities in EEG readings. It is also used to
diagnose sleep disorders, coma, encephalopathies, and brain death.
PSG examinations include monitoring the condition of the body during sleep at night. Confirmed diagnosis
of sleeping disorders and sleeping respiratory disorders is supported by recording neurophysiological
signals through electrodes. By measuring brain waves, eye movements, electromyogram movements,
etc., the depth of sleep (sleep stage), quality, presence or absence of midwake arousal, respiration by
breathing, snoring, oxygen saturation, etc., can be assessed.
To correctly interpret neurophysiological changes, medical device systems need to capture
these data, along with additional waveforms such as the respiration, SpO2, EOG (eye movement).
Healthcare providers and clinical specialists who perform these examinations greatly benefit from
interoperability – having all the examination data recorded in a single standardized package or file that
can be safely and securely managed and exchanged.
The purpose of this document is to describe the heterogeneous neurophysiological waveforms and
related data that can be normalized to a standard semantic representation and format and persisted
in a single package. The specification also supports the time synchronization of these waveforms and
related parametric data so that the clinician receiving the data package is able to better assess the
patient’s condition throughout the examination period.
About Medical waveform Format Encoding Rules (MFER)
The MFER standards address several challenges that are not limited to either EEG waveforms or the
neurophysiological assessments that are the main subject of this document:
— Simple and easy implementation: application of MFER is very simple and is designed to facilitate
understanding, easy installation, trouble-shooting, and low implementation cost.
— Using with other appropriate standards: it is recommended that MFER only describes
medical waveforms. Other information can be described using appropriate standards such as
1) 2) 3)
HL7® , DICOM® , IEEE® , etc. For example, clinical reports that include patient demographics,
order information, medication, etc. are supported in other standards such as HL7® Clinical
Document Architecture (CDA). By including references to MFER information in these documents,
implementation for message exchange, networking, database management that includes waveform
information becomes simple and easy.
— Separation between supplier and consumer of medical waveforms: the MFER specification
concentrates on data format instead of paper-based recording. For example, recorded ECG/EEG are
processed by filter, data alignment, and other parameters, so that the ECG waveform can be easily
displayed using an application viewer. However, it is not as useful for other purposes such as data
1) HL7 is the registered trademark of Health Level Seven International. This information is given for the convenience
of users of this document and does not constitute an endorsement by ISO of the product named.
2) DICOM is the registered trademark of the National Electrical Manufacturers Association for its standards
publications relating to digital communications of medical information. This information is given for the convenience
of users of this document and does not constitute an endorsement by ISO of the product named.
3) IEEE is a registered trademark of Institute of Electrical and Electronics Engineers, Inc. This information is given
for the convenience of users of this document and does not constitute an endorsement by ISO of the product named.
processing for research investigations. A design goal of MFER is that a waveform is described in
raw format with as complete as possible recording detail. When the waveform is used, appropriate
processing of the data are supported like filtering, view alignment and so on. In this way, the medical
waveform described in MFER can be used for multiple purposes.
— Product capabilities are not limited: standards often support only a minimum set of requirements,
so the expansion of product features can be greatly limited. MFER can describe medical waveform
information without constraining the potential features of a product. Also, medical waveform
display must be very flexible, and thus MFER has mechanisms supporting not only a machine-
readable coded system for abstract data, but also human-readable representation.
The MFER specification supports both present and future product implementations. MFER supports the
translation of stored waveform data that was encoded using other standards, enabling harmonization
and interoperability. This capability supports not only existing waveform format standards but can be
extended to support future formats as well.
vi © ISO 2021 – All rights reserved

TECHNICAL SPECIFICATION ISO/TS 22077-5:2021(E)
Health informatics — Medical waveform format —
Part 5:
Neurophysiological signals
1 Scope
This document specifies a heterogeneous format of neurophysiological waveform signals to support
recording in a single persistent record package as well as interoperable exchange. The document focuses
on electroencephalography (EEG) waveforms created during EEG examinations. Specific provision is
made for sleep polysomnography examinations (PSG), brain death determination, evoked potentials
(EP), and electromyography (EMG) studies.
This document is intended for neurophysiology.
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 22077-1:2015, Health informatics — Medical waveform format — Part 1: Encoding rules
ISO/TS 22077-3:2015, Health informatics — Medical waveform format — Part 3: Long term
electrocardiography
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO 22077-1:2015 apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at http:// www .electropedia .org/
4 Symbols and abbreviated terms
CO2 Carbon dioxide
DC Direct Current
DICOM Digital Imaging and Communication in Medicine
ECG Electrocardiography
EEG Electroencephalography
EMG Electromyography
EOG Electrooculography
EP Evoked potentials
HPF High-frequency pass filter
IEEE Institute of Electrical and Electronic Engineers
4)
LOINC® Logical Observation Identifiers Names and Codes
LPF Low-frequency pass filter
MFER Medical waveform Format Encoding Rules
PSG Polysomnography
SEP Somatosensory evoked potential
5)
SNOMED-CT® Systematized Nomenclature of Medicine-Clinical Terms
SpO2 Saturation of peripheral oxygen
4)
LOINC is the registered trademark of Regenstrief Institute, Inc. This information is given for the con-
venience of users of this document and does not constitute an endorsement by ISO of the product named.
5)
SNOMED CT is the registered trademark of the International Health Terminology Standards Devel-
opment Organisation (IHTSDO). This information is given for the convenience of users of this document
and does not constitute an endorsement by ISO of the product named.
5 General
5.1 Overview of the rules
All MFER content (see ISO 22077-1:2015, 4.2.2), including the file header and waveform data, should be
encoded based on the encoding rules that are composed of the tag, length and value (TLV), 3-tuple as
shown in Figure 1.
Figure 1 — Data unit
— The tag (T) consists of one or more octets and indicates the attribute of the data value.
— The data length (L) is the length of data values indicated in one or more octets.
— The value (V) is contents which are indicated by tag (T); e.g. attribute definition, waveform data,
etc.
In order to make effective use of this document, a MFER conformance statement is provided in Annex A
and sample waveform description are provided in Annex C.
5.2 Configuration of waveform data
Medical waveform data described in accordance with the MFER is an aggregate of waveform frame data
that consists of a header section (encoding detailed information about the waveform) and a waveform
data section (main data of waveform). See Figure 2. The header and waveform data are encoded based
on the encoding rules that are composed of TLV (Tag - Data length - Value). One MFER waveform file can
include several waveforms. The content of an MFER waveform file is sequentially interpreted from the
beginning of the file, and a single file can contain multiple waveform definitions. Given the sequential
2 © ISO 2021 – All rights reserved

precedence processing for an MFER file, a waveform definition applies until another definition with the
same tag is encountered. In this case, the subsequent definition replaces the preceding definition for
the same waveform.
Additionally, the definition for one waveform can be used, by reference, to define additional waveforms
in the MFER file. For example, a 60 channel EEG might only require four core waveform specifications,
with the other channels referring to the same definition, providing simplification of the overall file
complexity.
When there are several waveforms in a MFER waveform file, each waveform can be located anywhere in
the file; however, in the specification of data generated during EEG and other examinations, waveform
frames should be located as shown in Figure 2 to enhance usability and avoid erroneous interpretation:
— The information about EEG examination and others should be described before description of
waveform [i.e. in (a) and (d) content should be included before (e)]. For this document, the waveform
class definition(s) (MWF_WFM) are for neurophysiological signals and should be set to one of the
appropriate values defined in Table 2.
— The same type waveforms should be described in a sequential, contiguous manner, and located
chronologically in the file.
Key
a EEG examination h frame #1 of waveform #1
b waveform (type #1) i frame #2 of waveform #1
c waveform (type #2) j header
d Explanation about neurophysiological signals k waveform data
e explanation (waveform class) l explanation about frame
f waveform #1 of type #1
g waveform #2 of type #1
Figure 2 — Waveform data configuration
5.3 Time synchronization
In EEG examination data, several types of neurophysiological signals and biomedical data, such
as SpO2 or respiration may be described together in the same MFER file, requiring support for time
synchronization between the waveform streams and these parametric observations. In addition, it is
necessary to capture the state of the photic stimulator at the time the data was acquired.
NOTE For EEG examinations, photic stimulators are used to investigate anomalous brain activity triggered
by specific visual stimuli, such as flashing lights or other patterns.
The reference time used for synchronization starts counting from the beginning of the examination
period. The data recording system shall establish the reference time for each data point using the
recorded examination time. The reading system can then establish synchronization between data
points by correlating the acquisition time for each data point.
The reference time of waveforms such as EEGs are described using the pointer tag (MWF_PNT). The
reference time of events such as photic stimulator information (stimulator period, frequency, mode,
duration, etc.) is described using "starting time" item of the event tag (MWF_EVT). The reference time
of measurements such as heart rate and respiration rate are described using the "time point" item of
the value tag (MWF_VAL). Reference time is indicated as a data pointer that depends on the sampling
rate of the waveform frame. The waveform reader system may also achieve data synchronization using
pointers of different sampling rate.
For example, in Figure 3, if the sampling interval of a photic stimulator event is 1 second and the
sampling interval of EEG waveform is 1 ms, then the point of photic stimulator event becomes 60 s and
the point of EEG waveform becomes 60 000 samples at the time of the start of the photic stimulator.
4 © ISO 2021 – All rights reserved

Key
1 Event information
tag: MWF_EVT
code:
starting time: 60 s
2 60 s
3 start of examination
4 stimulator begin
Figure 3 — Time synchronization
6 Waveform encoding
6.1 General
6.1.1 Application of EEG studies
This set of medical waveform format encoding rules (MFER) is aimed at ensuring that the waveforms
collected during EEG studies, including PSG examinations, are encoded together with the needed
contextual and descriptive information of the EEG examination. The waveforms recorded during EEG
studies include “full disclosure waveform” (i.e. comprehensive continuous waveform data covering
the entire period of the exam), and “intermittent record waveform” (i.e. waveform records in short
segments of particular interest during the exam). Intermittent waveforms are also commonly described
as, e.g. “one shot”, “window”, “snapshot”, “snippet”.
6.1.2 Full disclosure waveforms
This form is used when encoding all EEG waveforms during examinations, including the resting period,
and the loading period such as photic stimulation. This not only includes encoding of waveform signals
from all leads used in the examination but also encoding of a subset of waveforms selected from multiple
leads. Note that for full disclosure waveform recording, encoding waveforms for the entire period of
the examination within one frame (see Figure 2) significantly reduces the MFER file complexity and
simplifies reading of the EEG content.
Encoding of full disclosure waveform shall be done in accordance with ISO 22077-1. The waveform class
of these waveforms include EEG_REST (40), EEG_EP (41), EEG_LTRM (43) and others.
6.1.3 Intermittent record waveforms
Intermittent recording of waveforms is used when encoding the waveforms of EEG, etc., using
interval records to capture shorter periods of interest during the examination such as resting, photic
stimulation, hyperventilation periods or one-shot records taken at random during the examination.
The point of time when the record concerned was taken during the test shall be encoded with using the
pointer tag (MWF_PNT).
For example, in Figure 4, if the sampling interval is 1 ms, then the point of information event (point #1)
becomes 600 s and the point of EEG waveform becomes 600 000 samples at the time of the start of the
examination.
Using the same sampling interval, the point of information event (point #2) becomes 900 s and the
point of EEG waveform becomes 9 000 000 samples at the time of the start of the examination.
6 © ISO 2021 – All rights reserved

Key
1 600 s after examination starting
2 900 s after examination starting
3 sampling interval 1 ms
4 start of examination
Figure 4 — Intermittent record waveform
6.2 Waveform class
6.2.1 General
The waveform class indicates that this waveform data represents a neurophysiological signal.
Furthermore, the waveform class indicates the kind of waveform that is included in the MFER data. The
format is given in Table 1.
Table 1 — Waveform class
MWF_WFM Data length Default Remarks Duplicated definitions
2 Non-specific waveform — Override
08 08h
Str ≤ 32 Waveform description — Override
NOTE 1   See ISO 22077-1:2015, 5.1.3.
NOTE 2   See ISO 22077-1:2015, 4.3.3.2 and 4.3.3.3.
6.2.2 Waveform Class for EEG, PSG, EP, EMG
6.2.2.1 General
Each waveform class shall identify its Type based on Table 2 below.
Table 2 — Classification of waveforms
Classification Type Value Description Remarks
Electrocardiography ECG_LTERM 2 Long-term ECG Holter ECG, monitoring ECG
Includes surgical monitoring
EEG_REST 40 Resting EEG
EEG
ABR
EEG_EP 41 Evoked EEG
SEP
Electroencephalography
EEG_CSA 42 Frequency analysis Reserved for future use.
(Neurophysiological signal)
EEG_LTRM 43 Long-term EEG Sleeping EEG
EMG 44 Electromyography —
EOG 45 Electrooculography —
Impedance resitatory, air-
Respiratory RESP 46 Respiratory
flow, Snore asnd others
NOTE 1   See ISO 22077-1:2015, section 5.1.3 [Waveform for general waveform type definitions (40) through (43)].
NOTE 2   EMG, EOG and RESP are uniquely defined in this document.
The following subsections provide additional detail for each of the waveforms identified in Table 2,
except those reserved for future use, such as EEG_CSA.
6.2.2.2 EEG_REST, EEG_LTRM
Electroencephalography (EEG) is a diagnostic technique recording the electrical activity of the
brain. Usually the electrodes are placed on the surface of the skull; special techniques use implanted
electrodes as well (see Annex B).
EEG data are used to diagnose epilepsy, to monitor encephalopathy, for anaesthesia and coma state
determination, and within sleep studies.
In clinical procedures, an EEG is typically is recorded for 20 minutes to 60 minutes using electrodes
placed on the patient’s scalp. Long term monitoring (e.g. to monitor epilepsy) may last from 6 hours to
several days. In both cases, video and audio recordings are often made as well.
Electrical potentials are in the range of 1 µV to 500 µV.
In sleep medicine, polysomnography (PSG), also called a “sleep study”, is an examination for diagnosing
sleep disorders. EEG data captured during PSG examinations are used as the primary indicator for
sleep stages, arousal, and wakefulness, but it is also used to aid in the diagnosis of parasomnia and
nocturnal epilepsy. Additional physiological parameters are recorded during sleep in order to identify
sleep stages, measure brain function, monitor respiratory control, and monitor patient movement and
body position.
A polysomnography consists of several measured quantities, with the most relevant for this document:
— brain activity (EEG);
— eye movements (EOG);
— activity of skeletal muscles (EMG).
Additionally, some of the following parameters are recorded:
— electrical activity of the heart (ECG);
— changes in blood oxygen levels (pulse oximetry);
— respiratory parameters like nasal and oral airflow via pressure transducers in front of nostrils and
mouth or chest and abdominal expansion during breathing (via belts);
8 © ISO 2021 – All rights reserved

— sound recordings to measure snoring.
Data acquisition is done via a multichannel recording unit which samples sensors attached to different
parts of the patient’s body. Study duration is typically up to 8 hours. Channel selection varies somewhat
between labs.
In many cases a video is taken to show the person’s movements during sleep, as well as audio recordings.
6.2.2.3 EMG, EEG_EP
Electromyography (EMG) is a diagnostic technique recording the electrical activity of skeletal muscles.
The electrical potential of the muscle cells changes on activation, due to a patient’s movement or
triggered by external stimulation. The data are used to detect neuromuscular abnormalities or to
monitor muscular activity. In polysomnography, electromyography is used to measure the muscle
tension and movement.
Two different techniques are used. Surface EMG assesses muscle function by recording electrical
potentials from muscle at the skin surface. Intramuscular EMG uses needle electrodes inserted through
the skin into the muscle, often in combination with surface electrodes as reference.
Within polysomnography, only surface EMG is used.
Measured values are in the range of 50 µV to 30 mV.
6.2.2.4 EOG
Electrooculography (EOG) is a diagnostic technique to record eye movement, which is an important
measure for classification of the sleep stage, for example slow-rolling eye movements in less deep sleep
stages and rapid, irregular eye movements indicating the REM phase.
Typically, two electrodes are used to measure the eye movement. They are placed above or below the
outer canthus of the eyes.
Measured values and sampling rates are approximately in the same range as EEG.
6.2.2.5 RESP
Respiratory are parameters like nasal and oral airflow via pressure transducers in front of nostrils and
mouth or chest and abdominal expansion during breathing (via belts).
6.3 Waveform attributes (lead names)
6.3.1 Waveform code
Lead name means the waveform code that is one of waveform attributes. The format is as in Table 3.
Table 3 — Definition of waveform attributes
Data Duplicated
MWF_LDN Default Remarks
length definitions
Data length = 2,
Waveform code 2 Override
if waveform information is
09 09h undefined encoded
Waveform
Str ≤ 32 — Override
information
NOTE 1   See ISO 22077-1:2015, Table 11 for general specifications.
6.3.2 EEG
Since the EEG becomes bipolar, it is described as follows.
Generation of waveform codes by combination of electrodes (see Figure 5).

NOTE  See ISO 22077-1:2015, Figure 8 for additional specifications.
Figure 5 — Generation of waveform code by combination of electrodes
Waveform codes can be generated by combination of electrode codes, as shown in Table 4 and Table 5.
The electrode code is given in Annex B (additional specifications are in ISO 22077-1:2015, Table 14).
Table 4 — Electrode code
Name Abbreviation Electrode code
Left front polar FP1 12
Right front polar FP2 13
Left ear A1 74
Right ear A2 75
Table 5 — Example of waveform code generation
Lead − electrode + electrode Waveform code
FP1 - A1 12 74 17994(464A)
FP2 - A2 13 75 18123(46CB)
6.3.3 PSG, EOG, EMG, EP, RESP
Waveform codes can be generated by parameters of PSG, EOG, EMG, EP, RESP as shown in Table 6.
Table 6 — Waveform code
Code Lead Remarks
31 Pulse —
175 SpO2 —
4161 Body position —
4162 Body movement —
4180 Impedance respiratory —
4181 Airflow Nostril and Mouth Respiration
4182 Snore —
4183 Rib Cage movement —
4184 Abdominal movement —
4185 Leg movement(Left) —
4186 Leg movement(Right) —
NOTE 1   See ISO 22077-1:2015, Tables 10 and 22 for additional electrode code specifications.
NOTE 2   Leads (4180) and following are newly defined in this document.
10 © ISO 2021 – All rights reserved

Table 6 (continued)
Code Lead Remarks
4187 EMG1 —
4188 EMG2 —
4189 EMG3 —
4190 EMG4 —
4191 EOG(Left eye movement) —
4192 EOG(Right eye movement) —
4193 EOG3 —
4194 EOG4 —
4195 CO2 —
4196 DC1 DC input channel 1
4197 DC2 DC input channel 2
4198 DC3 DC input channel 3
4199 DC4 DC input channel 4
NOTE 1   See ISO 22077-1:2015, Tables 10 and 22 for additional electrode code specifications.
NOTE 2   Leads (4180) and following are newly defined in this document.
6.3.4 ECG
Encoding of ECG waveform attribute is done in accordance with the long-term ECG specification,
ISO/TS 22077-3:2015, Annex D. Lead name means the waveform code used in long-term ECGs. This
code shall be used in 12-lead ECG and/or Vector lead ECG. The lead code is encoded by the number 0 to
127 in Table 7.
Lead code later than 4160 is defined in the long-term ECG standard such as Table 8. For more detailed
lead name other than the definition in the long-term ECG standard, see ISO/TS 22077-3.
Table 7 — Lead name-1
Code lead Code Lead
1 I — —
2 II — —
3 V1 — —
4 V2 — —
5 V3 — —
6 V4 — —
7 V5 — —
8 V6 — —
9 V7 — —
a
10 (V2R) — —
11 V3R 61 III
12 V4R 62 aVR
13 V5R 63 aVL
14 V6R 64 aVF
a
Although V2R (10) is defined in other rules such as SCP-ECG, the definition shall not be used in MFER.
b
-aVR lead shall not be encoded according to MFER. The users (viewer) should make a calculation to derive –aVR when
required.
NOTE 1   See ISO/TS 22077-3:2015, Table 21.
Table 7 (continued)
Code lead Code Lead
b
15 V7R 65 -aVR
16 X 66 V8
17 Y 67 V9
18 Z 68 V8R
19 CC5 69 V9R
20 CM5 70 D(Nehb Dosal)
— — 71 A(Nehb Anterior)
31 NASA 72 J(Nehb Inferior)
32 CB4 — —
33 CB5 — —
34 CB6 91 MCL
a
Although V2R (10) is defined in other rules such as SCP-ECG, the definition shall not be used in MFER.
b
-aVR lead shall not be encoded according to MFER. The users (viewer) should make a calculation to derive –aVR when
required.
NOTE 1   See ISO/TS 22077-3:2015, Table 21.
Table 8 — Lead name-2
Code Lead Remarks
4166 ECG1
4167 ECG2
These shall be used in case lead name is not defined.
4168 ECG3
4169 ECG4
NOTE 1   See ISO/TS 22077-3:2015, Table 22 for additional specifications.
6.4 Sampling attributes
6.4.1 General
"Sampling interval (MWF_IVL)" and "Sampling resolution (MWF_SEN)" should be described in
accordance with ISO 22077-1. If multiple types of waveform are present, the sampling attributes
described immediately before description of their waveform data are used. See 5.3 for additional use
information.
6.4.2 MWF_IVL (0Bh): Sampling rate
This tag indicates the frequency or interval the medical waveform is sampled (see Table 9).
Table 9 — Sampling rate
Encoding range/re- Duplicated
MWF_IVL Data length Default
marks definitions
Sampling rate unit 1 -
th -128~+127
11 0Bh Exponent(10 power) 1 1 000 Hz 10 Override
Mantissa ≤4 e.g. signed 16-bit integer
The unit can be frequency in Hertz, time in seconds or distance metres (see Table 10).
12 © ISO 2021 – All rights reserved

Table 10 — Sampling rate unit
Unit Value Remarks
Frequency Hz 0 Including power
Time interval s 1 —
Distance m 2 —
6.4.3 MWF_SEN (0Ch): Sampling resolution
This tag indicates the resolution of least significant bit, medical waveform sampled (generally, digitized)
(see Table 11).
Table 11 — Sampling resolution
Data Encoding range/ Duplicated
MWF_SEN Default
length remarks definitions
Sampling resolution unit 1
th -128~+127
Exponent(10 power) 1 10
12 0Ch See Table 12 Override
e.g. signed 16-bit
Mantissa ≤4
integer
Table 12 — Sampling units
Unit Value Default Remarks
Voltage V 0 0,000 001 V —
mm Hg(Torr) 1 — —
Pa 2 — —
Pressure
cm H O 3 — —
mm Hg/s 4 — —
Ratio % 7 — Include volume fraction (%)
l 19 — —
Flow rate, flow, volume l/s 20 — —
l/min 21 — —
Sampling attributes shall conform to ISO 22077-1:2015, Tables 2, 3, 4 and 5.
6.5 Frame attributes
"Data block length (MWF_BLK)", "Number of channels (MWF_CHN)" and "Number of sequences (MWF_
SEQ)" should be described in accordance with ISO 22077-1. If multiple types of waveform are present,
the frame attributes described immediately before description of their waveform data are used.
Frame attributes shall conform to ISO 22077-1:2015, Table 6.
6.6 Pointer
This tag indicates the waveform data pointer, which is represented by the sampling rate of the root
level, in the frame. If no pointer is designated, the pointer of the first frame is initialized as zero. The
pointer for the next frame is deemed to be a value adding the number of data length of the virtual root
level channel in the previous frame.
Pointer references shall conform to ISO 22077-1:2015, Table 28.
In electrocardiogram test, the pointer can be used to indicate the position of waveform in the
examination.
The format is provided in Table 13.
Table 13 — Pointer
MWF_PNT Data length Default Remarks Duplicated definitions
Zero or pointer of previous
07 07h ≤4 — Override
frame
6.7 Filter
"Filter information (MWF_FLT)" should be described in accordance with ISO 22077-1. Table 14 and
Table 15 provide the format and some examples.
Filters shall conform to ISO/TS 22077-3:2015, Tables 26 and 27.
Neurophysiological signal often uses special filters to eliminate the influence of various artefacts during
examination. Because some filters cause distortion or delay of neurophysiological signal waveform, a
clear description of attenuation rate, delayed time, etc. is recommended if care is deemed necessary.
In electroencephalography, HPF and LPF have the following settings.
HPF: 0.001, 0.003, 0.03, 0.1, 0.3, 0.6, 1.0, 2.0, 5.0, 10 s
LPF:15, 30, 35, 60, 70, 120, 300, 600, 1 200, 3 000 Hz
Table 14 — Filter information
MWF_FLT Data length Default Remarks Duplicated definitions
17 11h Str ≤ 128 unused — Possible
Table 15 — Filter description example
Filter function Abbreviation Example Meaning
Hum filter (characteristics, etc. not specified).
Filter information
None Hum filter ON Combining line frequency information can
only
provide specific filter information.
Indefinite characteristics 0,5 Hz low
High-frequency pass HPF=0,5^delay
frequency cut-off (high-pass) filter used.
HPF
filter time=1 023 ms
Delay time is 1 023 ms.
Butterworth secondary characteristics
Low-frequency pass LPF=150^secondary
LPF 150 Hz high frequency cut-off (low-pass)
filter Butterworth filter
filter used.
Band elimination 50 Hz Hum filter used. Cut-off characteristics
BEF BEF=50^Hum filter
filter not known.
7 Event information
7.1 General
The event information as EEG, PSG, EOG, EMG and EP should be described using with “Event (MWF_
EVT)” and “ Value (MWF_VAL)”.
Event information shall conform to ISO 22077-1:2015, Table 32.
14 © ISO 2021 – All rights reserved

7.2 Measurement status – related events
Measurement status-related events such as photic stimulation and hyperventilation, etc. is described
as event. The format is Table 16. Events include those listed in Table 17.
Table 16 — Measurement-related events
Duplicated
MWF_EVT Data length Encoding range/Remarks
definitions
Event code 2 See Table 17
Starting time (point) 4 Number of samples acquired at the Multiple
65 41h sampling interval defined in the root definitions
Duration 4
definition. available
Event information Str ≤ 256 See Table 17
NOTE 1   See ISO 22077-1:2015, 4.3.3.2.
Table 17 — Measurement-related event code
CODE
Explanation/
Reference ID Event
Event information
DEC HEX
MWF_CAL 4701 125D Calibration —
MWF_EVENT1 4702 125E Event1 —
MWF_EVENT2 4703 125F Event2 —
MWF_PHOTO_STIM 4704 1260 Photic stimulation —
MWF_HYPERVENT 4705 1261 Hyperventilation —
Skin-Electrode Impedance
MWF_IMP_CHECK 4706 1262 —
Check
MWF_RESET 4707 1263 Reset —
MWF_EYES_OPEN 4708 1264 Eye open —
MWF_EYES_CLOSED 4709 1265 Eye closed —
MWF_EYE_MOVEMENT 4710 1266 Eye movement —
MWF_BODY_MOVMENT 4711 1267 Body movement —
MWF_EMG 4712 1268 EMG —
MWF_ARTTIFACT 4713 1269 Artifact —
MWF_NOISE 4714 126A Noise —
MWV_WAKING 4715 126B Waking —
MWF_APNEA 4716 126C Apnea —
MWF_HYPOPNEA 4717 126D Hppopnea —
MWF_NREM1 4718 126E Stage1 Non-REM
MWF_NREM2 4719 126F Stage2 Non-REM
See Reference [5]
MWF_NREM3 4720 1270 Stage3 Non-REM
MWF_REM 4721 1271 Stage REM
Turn on the lights in the
MWF_LIGHTS_ON 4722 1272 —
room
Turn off the lights in the
MWF_LIGHTS_OFF 4723 1273 —
room
NOTE 1   See ISO 22077-1:2015, Table 32 for additional specifications.
Annex A
(informative)
MFER conformance statement
Each implementer should provide a specification sheet of their specific MFER waveform format as
a conformance statement (Table A.1). Use of non-default values should be identified clearly. If the
extension part of the MFER description is used, an additional sheet with other optional extensions
should also be provided.
Table A.1 — Conformance statement template
MFER specification Frame / Ver.
Manufacturer Date
Producer Model
Author Edited date
Waveform title Specification
Preamble Endianity •Default(big endian) •Big endian •Little endian
Version . Character
Sampling rate Unit Exponent Mantissa
Sampling at-
tributes
Sampling resolution Unit Exponent Mantissa
Data type •Default •( ) NULL •Not used •( ) Offset value •Not used •( )
Frame number Block Channel Sequence
Channel No. Lead or Waveform Condition Remarks

Note
16 © ISO 2021 – All rights reserved

Annex B
(informative)
EEG electrode code
B.1 Electrode positioning
Small meta
...