Digitization

The process of converting analog video or identifying points in digital video for quantitative analysis.

Digitization in biomechanics refers to the process of converting visual movement information into numerical data that can be measured, analyzed, and interpreted. In modern practice, this primarily involves identifying and recording the coordinates of anatomical landmarks in digital video.

Historical Context

Originally, digitization referred to:

  • Converting analog film or video to digital format
  • Manually marking points on printed images
  • Using specialized digitizing tablets
  • Recording coordinates with pointing devices

Today, digitization commonly means:

  • Identifying anatomical landmarks in digital video
  • Recording x-y coordinates frame-by-frame
  • Creating time-series position data
  • Enabling quantitative biomechanical analysis

The Digitization Process

1. Video Preparation

  • Import video into analysis software
  • Select relevant portion of video (trial or cycle)
  • Set video quality and playback settings
  • Ensure proper calibration is established

2. Landmark Identification

Select anatomical landmarks based on analysis goals:

  • Standard landmarks (ankle, knee, hip, etc.)
  • Clearly identifiable on each frame
  • Relevant to movements of interest
  • Sufficient to calculate desired angles and distances

3. Coordinate Recording

For each frame and each landmark:

  • Identify exact position of landmark
  • Click or mark position in software
  • Software records x-y pixel coordinates
  • Repeat for all landmarks across all frames

4. Data Processing

Raw coordinate data is then:

  • Converted to real-world units using calibration
  • Filtered to reduce noise or digitizing errors
  • Used to calculate angles, velocities, distances
  • Exported for statistical analysis or visualization

Manual vs. Automated Digitization

Manual Digitization

  • Analyst marks each point on each frame
  • Most accurate for difficult cases
  • Time-intensive process
  • Full control and quality assurance
  • Requires trained analyst

Automated Digitization

  • Software automatically tracks landmarks
  • Much faster than manual methods
  • Requires clear visibility and good contrast
  • May need manual correction of errors
  • Improving with AI and machine learning

Semi-Automated (Hybrid)

  • Software suggests positions, analyst verifies
  • Balances speed and accuracy
  • Most common in modern practice
  • Efficient workflow
  • Quality assurance built in

Quality Considerations

Factors Affecting Digitization Accuracy

Video Quality

  • Higher resolution = more precise landmark identification
  • Higher frame rate = better temporal resolution
  • Good lighting = clearer landmark visibility
  • Stable camera = consistent coordinate system

Landmark Selection

  • Bony prominences more reliable than soft tissue
  • Consistent identification across frames
  • Visible throughout movement sequence
  • Anatomically appropriate for analysis goals

Analyst Skill

  • Understanding of anatomy
  • Consistency in landmark identification
  • Attention to detail
  • Recognition of errors or outliers

Digitization Errors

Common sources of error:

  • Landmark Identification Error: Inconsistent marking of same point
  • Perspective Error: 2D projection of 3D movement
  • Marker Occlusion: Temporary blocking of landmarks
  • Soft Tissue Artifact: Skin movement relative to underlying bone
  • Resolution Limitations: Pixel-level constraints on precision

Reliability and Validity

Intra-Rater Reliability

  • Consistency when same analyst digitizes same video multiple times
  • Should have high correlation (>0.95 for most applications)
  • Important for longitudinal studies

Inter-Rater Reliability

  • Agreement between different analysts
  • Critical when multiple people involved in project
  • Requires standardized protocols

Validity

  • Do digitized values represent true movement?
  • Compared against gold standard systems when possible
  • Affected by 2D vs. 3D considerations

Applications

Gait Analysis

  • Digitize ankle, knee, hip points
  • Calculate joint angles through gait cycle
  • Measure stride length and step width
  • Assess temporal and spatial parameters

Sports Technique

  • Track body and implement positions
  • Calculate joint angles at key events
  • Measure velocities and accelerations
  • Compare pre/post coaching changes

Clinical Assessment

  • Document movement patterns
  • Quantify range of motion
  • Track treatment outcomes
  • Provide objective measurements

Ergonomic Analysis

  • Assess workplace postures
  • Calculate joint angles during tasks
  • Identify high-risk positions
  • Evaluate intervention effectiveness

Data Output

Digitization produces:

  • Time-Series Data: Position of each point across time
  • Joint Angle Data: Calculated from three-point combinations
  • Velocity Profiles: Change in position over time
  • Acceleration Profiles: Change in velocity over time
  • Kinematic Graphs: Visual representation of movement patterns
  • Summary Statistics: Peak values, ranges, means, timing of events

Modern Software Features

Contemporary analysis software offers:

  • Automatic tracking with manual correction options
  • Template-based digitization for consistency
  • Real-time angle and velocity calculations
  • Filtering and smoothing tools
  • Export to various formats (Excel, CSV, MATLAB, etc.)
  • Visual overlays showing digitized points and calculated angles

Best Practices

  • Establish and follow consistent protocols
  • Use clear, standardized landmark definitions
  • Digitize multiple trials for reliability
  • Always review data for outliers or errors
  • Document procedures for reproducibility
  • Consider pilot testing before large studies
  • Use appropriate filtering/smoothing for data type

Digitization bridges the gap between qualitative video observation and quantitative biomechanical analysis, transforming visual information into precise numerical data that can be measured, compared, and interpreted objectively.

Related Terms