DICOM Basics using Java - Waveforms (ECG, EEG)

Nov 18, 2025

Introduction

This is part of my series of articles on the DICOM standard. In this tutorial, we'll explore DICOM waveform objects, which store physiological signals such as ECG (electrocardiogram), EEG (electroencephalogram), and other time-series data. This enables integrating waveform data with imaging in PACS.

DICOM waveforms bring cardiology, neurology, and other physiological monitoring data into the same standardized format used for medical imaging.

Prerequisites

Before you begin, ensure you have the following:

Java JDK installed (Java 8 or later)
PixelMed Java DICOM Toolkit
Basic understanding of ECG/physiological signals
You can find all the code demonstrated in this tutorial on GitHub here

“The heart has its reasons which reason knows not.” ~ Blaise Pascal

The Theory Behind DICOM Waveforms

DICOM Waveforms extend medical imaging standards into the realm of physiological signal acquisition. This unification addresses a long-standing fragmentation in healthcare IT where ECG systems, EEG systems, and imaging systems existed in isolated silos.

The Signal vs. Image Dichotomy

Medical data fundamentally divides into spatial (images) and temporal (signals) domains:

Images: 2D/3D spatial data, discrete pixels, anatomy-focused
Signals: 1D time-series, continuous sampling, physiology-focused

Despite this difference, both have the same workflow requirements: patient association, study organization, archival storage, and cross-enterprise sharing. DICOM Waveforms apply imaging workflows to signal data.

The Multi-Channel Data Model

Physiological signals are inherently multi-channel:

12-Lead ECG: 12 simultaneous electrical channels from different body positions
EEG: 21+ channels in standard 10-20 electrode placement
Polysomnography: ECG + EEG + EMG + respiratory + SpO2 channels

DICOM's Waveform Sequence stores all channels with shared timing, individual calibration, and channel-specific source identification codes. The Channel Definition Sequence provides metadata for each channel's physical meaning and scaling.

Sampling Theory Considerations

Waveform data acquisition must respect the Nyquist-Shannon sampling theorem: to accurately represent a signal, sampling frequency must exceed twice the highest frequency component:

ECG: ~100 Hz bandwidth → ≥500 Hz sampling typical
EEG: ~40 Hz bandwidth → ≥256 Hz sampling typical
EMG: ~500 Hz bandwidth → ≥1000 Hz sampling typical

DICOM stores the Sampling Frequency attribute, enabling receivers to correctly reconstruct the continuous signal from discrete samples.

The Lead Identification Challenge

For ECG data to be clinically useful, each channel must be unambiguously identified. Is this channel Lead I or Lead V1? DICOM addresses this through the Channel Source Sequence using standardized codes (MDC, medical device communication codes):

Lead I: MDC_ECG_LEAD_I
Lead II: MDC_ECG_LEAD_II
Lead V1: MDC_ECG_LEAD_V1

This coded identification enables automated analysis software to correctly interpret lead-specific patterns (e.g., inferior STEMI shows ST elevation in leads II, III, aVF).

Waveform SOP Classes

SOP Class	UID	Use Case
12-Lead ECG	1.2.840.10008.5.1.4.1.1.9.1.1	Standard 12-lead ECG
General ECG	1.2.840.10008.5.1.4.1.1.9.1.2	Other ECG formats
Ambulatory ECG	1.2.840.10008.5.1.4.1.1.9.1.3	Holter monitoring
Hemodynamic	1.2.840.10008.5.1.4.1.1.9.2.1	Blood pressure, cardiac output
Basic Cardiac EP	1.2.840.10008.5.1.4.1.1.9.3.1	Electrophysiology studies
General Audio	1.2.840.10008.5.1.4.1.1.9.4.1	Audio waveforms
Arterial Pulse	1.2.840.10008.5.1.4.1.1.9.5.1	Pulse waveforms
Respiratory	1.2.840.10008.5.1.4.1.1.9.6.1	Breathing patterns

Waveform IOD Structure

Waveform Sequence (5400,0100)
  +-- Number of Channels (003A,0005)
  +-- Number of Samples (003A,0010)
  +-- Sampling Frequency (003A,001A)
  +-- Channel Definition Sequence (003A,0200)
  |     +-- Channel Source
  |     +-- Channel Sensitivity
  |     +-- Channel Sensitivity Units
  +-- Waveform Data (5400,1010)

Creating a 12-Lead ECG

package com.saravanansubramanian.dicom.pixelmedtutorial;

import java.text.SimpleDateFormat;
import java.util.Date;

import com.pixelmed.dicom.*;

public class CreateEcgWaveformDemo {

    public static void main(String[] args) {

        try {

            System.out.println("=== DICOM ECG Waveform Creation ===\n");

            String outputFile = "C:\\temp\\ecg_waveform.dcm";

            // Generate sample ECG data (10 seconds at 500 Hz)
            short[] ecgData = generateSampleEcgData(5000, 500.0);

            // Create the waveform DICOM object
            AttributeList list = create12LeadEcg(
                ecgData,
                500.0,  // Sampling frequency (Hz)
                "Doe^John",
                "PAT123",
                "19700101",
                "M"
            );

            // Add file meta information
            FileMetaInformation.addFileMetaInformation(
                list,
                TransferSyntax.ExplicitVRLittleEndian,
                "ECG_SOURCE"
            );

            // Write the file
            list.write(outputFile);

            System.out.println("ECG Waveform created: " + outputFile);
            System.out.println("Duration: 10 seconds");
            System.out.println("Sampling Rate: 500 Hz");
            System.out.println("Channels: 12 leads");

        } catch (Exception e) {
            e.printStackTrace(System.err);
        }
    }

    private static AttributeList create12LeadEcg(
            short[] ecgData,
            double samplingFrequency,
            String patientName,
            String patientId,
            String patientBirthDate,
            String patientSex) throws Exception {

        AttributeList list = new AttributeList();

        SimpleDateFormat dateFormat = new SimpleDateFormat("yyyyMMdd");
        SimpleDateFormat timeFormat = new SimpleDateFormat("HHmmss");
        Date now = new Date();
        String currentDate = dateFormat.format(now);
        String currentTime = timeFormat.format(now);

        // === SOP Common Module ===
        Attribute sopClass = new UniqueIdentifierAttribute(
            TagFromName.SOPClassUID);
        sopClass.addValue(SOPClass.TwelveLeadECGStorage);
        list.put(sopClass);

        Attribute sopInstance = new UniqueIdentifierAttribute(
            TagFromName.SOPInstanceUID);
        sopInstance.addValue(UniqueIdentifierAttribute.createUID());
        list.put(sopInstance);

        // === Patient Module ===
        Attribute patNameAttr = new PersonNameAttribute(
            TagFromName.PatientName);
        patNameAttr.addValue(patientName);
        list.put(patNameAttr);

        Attribute patIdAttr = new LongStringAttribute(TagFromName.PatientID);
        patIdAttr.addValue(patientId);
        list.put(patIdAttr);

        // === General Series Module ===
        Attribute modality = new CodeStringAttribute(TagFromName.Modality);
        modality.addValue("ECG");
        list.put(modality);

        // === Waveform Sequence ===
        SequenceAttribute waveformSeq = new SequenceAttribute(
            TagFromName.WaveformSequence);
        AttributeList waveformItem = new AttributeList();

        // Number of channels (12-lead ECG)
        Attribute numChannels = new UnsignedShortAttribute(
            TagFromName.NumberOfWaveformChannels);
        numChannels.addValue(12);
        waveformItem.put(numChannels);

        // Number of samples per channel
        int samplesPerChannel = ecgData.length / 12;
        Attribute numSamples = new UnsignedLongAttribute(
            TagFromName.NumberOfWaveformSamples);
        numSamples.addValue(samplesPerChannel);
        waveformItem.put(numSamples);

        // Sampling frequency
        Attribute sampFreq = new DecimalStringAttribute(
            TagFromName.SamplingFrequency);
        sampFreq.addValue(String.valueOf(samplingFrequency));
        waveformItem.put(sampFreq);

        // Waveform bits allocated
        Attribute bitsAlloc = new UnsignedShortAttribute(
            TagFromName.WaveformBitsAllocated);
        bitsAlloc.addValue(16);
        waveformItem.put(bitsAlloc);

        // Waveform sample interpretation
        Attribute sampleInterp = new CodeStringAttribute(
            TagFromName.WaveformSampleInterpretation);
        sampleInterp.addValue("SS"); // Signed Short
        waveformItem.put(sampleInterp);

        // Add channel definitions and waveform data...
        // (See full code example on GitHub)

        waveformSeq.addItem(waveformItem);
        list.put(waveformSeq);

        return list;
    }
}

12-Lead ECG Leads

Lead Type	Leads	Description
Limb	I, II, III	Standard limb leads
Augmented	aVR, aVL, aVF	Augmented unipolar leads
Precordial	V1-V6	Chest leads

Channel Definition Sequence

// === Channel Definition Sequence ===
SequenceAttribute channelDefSeq = new SequenceAttribute(
    TagFromName.ChannelDefinitionSequence);

// Standard 12-lead names
String[] leadNames = {"I", "II", "III", "aVR", "aVL", "aVF",
    "V1", "V2", "V3", "V4", "V5", "V6"};

for (int i = 0; i < 12; i++) {
    AttributeList channelItem = new AttributeList();

    // Channel Source Sequence (identifies the lead)
    SequenceAttribute channelSourceSeq = new SequenceAttribute(
        TagFromName.ChannelSourceSequence);
    AttributeList sourceItem = new AttributeList();

    Attribute codeValue = new ShortStringAttribute(TagFromName.CodeValue);
    codeValue.addValue("5.6.3-9-" + (i + 1)); // MDC codes for ECG leads
    sourceItem.put(codeValue);

    Attribute codingScheme = new ShortStringAttribute(
        TagFromName.CodingSchemeDesignator);
    codingScheme.addValue("MDC");
    sourceItem.put(codingScheme);

    Attribute codeMeaning = new LongStringAttribute(TagFromName.CodeMeaning);
    codeMeaning.addValue("Lead " + leadNames[i]);
    sourceItem.put(codeMeaning);

    channelSourceSeq.addItem(sourceItem);
    channelItem.put(channelSourceSeq);

    // Channel sensitivity
    Attribute sensitivity = new DecimalStringAttribute(
        TagFromName.ChannelSensitivity);
    sensitivity.addValue("1.0");
    channelItem.put(sensitivity);

    // Channel sensitivity units (microvolts)
    // ...

    channelDefSeq.addItem(channelItem);
}

waveformItem.put(channelDefSeq);

Key Waveform Attributes

Tag	Name	Description
(5400,0100)	Waveform Sequence	Contains waveform data
(003A,0005)	Number of Waveform Channels	Channel count
(003A,0010)	Number of Waveform Samples	Samples per channel
(003A,001A)	Sampling Frequency	Samples per second (Hz)
(5400,0102)	Waveform Bits Allocated	8 or 16 bits
(5400,1004)	Waveform Bits Stored	Actual bits used
(5400,1006)	Waveform Sample Interpretation	SS, US, SB, UB, etc.
(003A,0200)	Channel Definition Sequence	Per-channel metadata
(5400,1010)	Waveform Data	Raw waveform samples

Sample Interpretation Values

Value	Description
SS	Signed 16-bit integer
US	Unsigned 16-bit integer
SB	Signed 8-bit integer
UB	Unsigned 8-bit integer

Common Use Cases

Cardiology: 12-lead ECG, stress tests, Holter monitoring
Neurology: EEG recordings
Critical Care: Hemodynamic monitoring
Surgery: Intraoperative monitoring
Research: Clinical trials, physiological studies

Integration with PACS

DICOM waveforms can be:

Stored in PACS alongside imaging studies
Linked to patient records via Study/Patient IDs
Viewed in DICOM workstations that support waveform display
Queried and retrieved using standard DICOM services

Conclusion

DICOM waveform objects extend the DICOM standard beyond imaging to include physiological signals like ECG and EEG. This enables unified storage and retrieval of all patient diagnostic data within PACS infrastructure.

Understanding waveform IOD structure, channel definitions, and sampling parameters is essential for building applications that integrate cardiology, neurology, and other physiological monitoring systems with PACS. In the next tutorial in this series, I will cover multi-modality DICOM attributes for CT, MR, US, and other imaging types. See you then!