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Respiratory Sound Classification

Classify lung and respiratory sounds for medical diagnosis following ICBHI 2017 Challenge format.

Get This Design

This design is available in our showcase. Copy the configuration below to get started.

Quick start:

bash
# Create your project folder
mkdir respiratory-sound-classification
cd respiratory-sound-classification
# Save config.yaml from this page into this folder
potato start config.yaml
Respiratory Sound Classification annotation interface preview

Configuration File

yaml
annotation_task_name: "Respiratory Sound Classification"
task_dir: "."

port: 8000

# Data configuration
data_files:
  - "data/respiratory_sounds.json"

item_properties:
  id_key: "id"
  text_key: "text"
instance_display:
  fields:
    - key: audio_url
      type: audio
      label: "Recording"
    - key: text
      type: text
      label: "Notes"

# Annotation schemes
annotation_schemes:
  # Overall classification
  - annotation_type: radio
    name: overall_classification
    description: "Overall respiratory sound classification"
    labels:
      - Normal (healthy breathing)
      - Abnormal (pathological sounds present)
      - Poor quality (cannot assess)

  # Adventitious sounds (abnormal sounds)
  - annotation_type: multiselect
    name: adventitious_sounds
    description: "What abnormal sounds are present? (Select all that apply)"
    labels:
      - Crackles (fine) - brief, discontinuous, high-pitched
      - Crackles (coarse) - louder, lower-pitched, longer
      - Wheezes - continuous, high-pitched, musical
      - Rhonchi - continuous, low-pitched, snoring
      - Stridor - high-pitched, inspiratory
      - Pleural friction rub - creaking/grating
      - None (normal breathing only)

  # Breathing phase affected
  - annotation_type: multiselect
    name: phase_affected
    description: "During which phase are abnormal sounds heard?"
    labels:
      - Inspiration
      - Expiration
      - Both phases
      - Cannot determine
      - Not applicable (normal)

  # Sound intensity
  - annotation_type: radio
    name: sound_intensity
    description: "Intensity of abnormal sounds (if present)"
    labels:
      - Subtle (barely audible)
      - Mild
      - Moderate
      - Severe (very pronounced)
      - Not applicable

  # Location (if known)
  - annotation_type: radio
    name: likely_location
    description: "Where might these sounds originate? (Based on characteristics)"
    labels:
      - Upper airways
      - Lower airways/bronchi
      - Lung parenchyma
      - Pleural
      - Cannot determine
      - Not applicable

  # Recording quality
  - annotation_type: likert
    name: recording_quality
    description: "Quality of the respiratory recording"
    size: 5
    min_label: "Very poor"
    max_label: "Excellent"

  # Artifacts present
  - annotation_type: multiselect
    name: artifacts
    description: "What artifacts or noise are present?"
    labels:
      - Heart sounds (normal)
      - Movement artifact
      - Talking/coughing
      - Equipment noise
      - Environmental noise
      - None

  # Clinical confidence
  - annotation_type: likert
    name: confidence
    description: "Confidence in your classification"
    size: 5
    min_label: "Low"
    max_label: "High"

  # Notes
  - annotation_type: text
    name: clinical_notes
    description: "Additional clinical observations (optional)"
    multiline: true
    required: false

# User settings

# Output
output_annotation_dir: "annotation_output/"
export_annotation_format: "jsonl"

Sample Data

json
[
  {
    "id": "respiratory_sound_classification_1",
    "audio_url": "https://upload.wikimedia.org/wikipedia/commons/3/37/The-description-of-cough-sounds-by-healthcare-professionals-1745-9974-2-1-S1.ogg",
    "text": "Cough recording from a clinical study"
  },
  {
    "id": "respiratory_sound_classification_2",
    "audio_url": "https://upload.wikimedia.org/wikipedia/commons/0/06/The-description-of-cough-sounds-by-healthcare-professionals-1745-9974-2-1-S2.ogg",
    "text": "Cough recording from a clinical study"
  }
]

// ... and 3 more items

Details

Annotation Types

radiomultiselect

Domain

AudioMedical

Use Cases

medical audiorespiratory soundsclinical diagnosis

Tags

audiomedicalrespiratorylung soundsdiagnosis