Visualize Hand Motion in Real Time
Explore biomechanics through skeletal tracking and spatial computing.
OrthoHand Motion reconstructs a skeletal model of the hand and displays motion metrics while the hand moves.Using camera-based tracking, the application visualizes finger movement, grip formation, and spatial motion patterns.
On Apple Vision Pro the experience becomes immersive, allowing users to explore hand motion in three-dimensional space.
OrthoHand Motion is a motion visualization platform designed to explore hand movement using computer vision and spatial computing technologies.
The application reconstructs a skeletal representation of the hand and estimates biomechanical motion parameters such as finger joint angles, grip opening, and motion trajectories.
Users can observe these measurements updating in real time while moving their hands.
The application includes recording tools that allow motion sessions to be captured and exported for documentation or research purposes.
On Apple Vision Pro the experience becomes spatial.
Hand motion can be visualized in three-dimensional space through floating skeletal models and immersive motion dashboards.
OrthoHand Motion is designed for:
• biomechanics exploration
• education
• gesture research
• XR interaction studies
• motion visualization
ORTHOHAND MOTION
COMPLETE MEASUREMENT & RESEARCH DOCUMENTATION
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🔹 OVERVIEW
OrthoHand Motion is a motion visualization application that estimates hand movement using camera-based skeletal tracking and spatial computing.
The system reconstructs a digital model of the hand and calculates motion-related parameters based on detected anatomical landmarks.
All measurements are algorithm-derived estimations intended for:
• motion visualization
• education
• biomechanics exploration
• research
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🔹 OVERVIEW SESSION (GLOBAL METRICS)
What is shown
• Global flexion
• Hand opening
• Grip aperture
• Pinch aperture
• Symmetry
• Motion status
• Tracking confidence
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How measured
Derived from:
• joint angles
• fingertip distances
• temporal motion data
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Interpretation
These are composite and comparative metrics, not direct anatomical measurements.
They should be interpreted as:
• visual indicators
• session trends
• baseline comparisons
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🔹 FINGERS SESSION
MCP FLEXION
What it is:
Bending of the finger at the base joint.
How measured:
Angle between metacarpal and proximal phalanx vectors.
Reference range:
Approx. 0–90° (adult reference)
Implication:
Contributes to grip formation and object shaping.
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PIP FLEXION
What it is:
Bending of the middle finger joint.
How measured:
Angle between proximal and middle phalanx.
Reference range:
Approx. 0–100°
Implication:
Primary contributor to grip strength and closure.
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DIP FLEXION
What it is:
Bending of fingertip joint.
How measured:
Angle between middle and distal phalanx.
Reference range:
Approx. 0–70–80°
Implication:
Important for fine motor control and precision tasks.
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FINGER SPREAD
What it is:
Distance/angle between adjacent fingers.
How measured:
Angle between finger direction vectors.
Reference:
No universal fixed value.
Implication:
Represents finger independence and coordination.
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CASCADE PATTERN
What it is:
Natural progressive flexion across fingers.
How measured:
Relative MCP/PIP angles across digits.
Reference:
Qualitative pattern (not fixed numeric).
Implication:
Represents natural hand resting posture and dynamic closure.
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TOTAL ACTIVE MOTION (TAM)
What it is:
Sum of MCP + PIP + DIP motion.
Reference value:
Approx. 260° per finger (clinical reference)
Implication:
Overall finger mobility indicator.
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🔹 THUMB SESSION
THUMB MCP FLEXION
What it is:
Base joint movement of thumb.
Implication:
Grip stabilization.
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THUMB IP FLEXION
What it is:
Distal thumb bending.
Implication:
Fine pinch control.
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THUMB OPPOSITION
What it is:
Movement of thumb across palm.
How measured:
Distance/angle relative to palm plane and fingers.
Reference:
Functional scale (Kapandji concept)
Implication:
Essential for precision grip and manipulation.
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THUMB–FINGER DISTANCES
What it is:
Distances between thumb and each fingertip.
Implication:
Pinch and grip classification.
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🔹 WRIST / PALM SESSION
WRIST FLEXION
Reference: ~65–80°
Implication: bending toward palm.
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WRIST EXTENSION
Reference: ~55–75°
Implication: functional positioning of hand.
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RADIAL DEVIATION
Reference: ~15–25°
Movement toward thumb side.
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ULNAR DEVIATION
Reference: ~30–45°
Movement toward little finger side.
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PALM ORIENTATION
What it is:
3D orientation of palm.
How measured:
Plane defined by wrist and MCP joints.
Implication:
Important for spatial interaction and XR.
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CARPAL ORIENTATION
What it is:
Hand coordinate system base.
Implication:
Used for advanced spatial calculations.
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🔹 MOTION SESSION
RANGE OF MOTION (ROM)
Max – Min angle during recording.
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VELOCITY
Rate of angular change over time.
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ACCELERATION
Change in velocity over time.
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TIMING METRICS
• onset
• duration
• repetition rate
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SMOOTHNESS
Derived from motion variability.
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INTERPRETATION
These are performance and research metrics, not diagnostic values.
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🔹 SPATIAL SESSION (VISION PRO)
3D TRAJECTORIES
Path of movement in space.
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6-DoF HAND POSE
• X/Y/Z translation
• X/Y/Z rotation
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AXIS ORIENTATION
Hand orientation relative to world space.
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INTERPRETATION
These are advanced spatial kinematic metrics used for:
• XR interaction
• research
• motion analysis
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🔹 RESEARCH SESSION
WHAT IS RECORDED
• joint positions
• joint angles
• timestamps
• trajectories
• device type
• tracking confidence
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WHAT IS NOT RECORDED
• identity
• name
• face
• voice
• location
• medical data
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DATA STORAGE
• stored locally on device
• export by user
• optional future research contribution (opt-in only)
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DATA FORMAT
• CSV
• JSON
• time-series structure
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🔹 NORMAL VALUES POLICY
The app uses:
✔ reference ranges (where available)
✔ personal baseline comparison
✔ side-to-side comparison
The app DOES NOT classify:
❌ normal vs abnormal
❌ healthy vs diseased
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🔹 CLINICAL INTERPRETATION POLICY
Measurements:
• are estimates
• are visualization tools
• may vary based on tracking conditions
They are NOT medical conclusions.
These are observational tendencies, not classifications.
DISCLAIMER
OrthoHand Motion provides algorithm-derived motion estimates for visualization, education, and research.
The application does not provide medical diagnosis, treatment recommendations, or clinical decision support.
Reference values shown are general motion references and must not be interpreted as medical conclusions.
Users must not rely on the application as the sole basis for medical decisions.
Consult a qualified healthcare professional before making any health-related decisions.
USER GROUP PATTERNS (NON-DIAGNOSTIC)
The following observations describe general motion tendencies that may be seen in different user populations during hand movement tasks.
These patterns are not diagnostic, do not indicate any condition, and should be interpreted as behavioral and ergonomic observations only.
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🎮 Gamers
Users engaged in prolonged gaming sessions may demonstrate:
• repetitive finger activation patterns, particularly involving the index finger and thumb
• rapid alternating movements during input (e.g., clicking, tapping)
• fatigue-related variability over time in speed and motion consistency
• dominant-hand asymmetry depending on mouse or controller usage
• reduced hand opening during prolonged gripping of controllers
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🎹 Pianists and Musicians
Users with musical training (e.g., piano, string instruments) may demonstrate:
• refined finger independence across digits
• coordinated multi-joint motion during sequential tasks
• stable timing patterns and rhythmic consistency
• efficient distribution of motion across MCP, PIP, and DIP joints
• controlled thumb opposition and precision positioning
These patterns reflect motor training and coordination strategies.
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🕶️ XR / Spatial Interaction Users
Users frequently interacting with spatial computing systems may demonstrate:
• larger movement trajectories in three-dimensional space
• increased variability in wrist and palm orientation
• repeated pinch gestures (thumb–index interaction)
• fatigue effects during prolonged mid-air interaction
• preference for certain “rest zones” in spatial interaction
These patterns are relevant for human–computer interaction design and ergonomics.
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⌨️ Keyboard Users / Secretarial and Office Work
Users engaged in repetitive keyboard-based tasks (e.g., typing, data entry, administrative work) may demonstrate:
• repetitive low-amplitude finger movements, especially in MCP and PIP joints
• relatively stable but high-frequency motion cycles
• limited full-range finger flexion during typing tasks
• reduced variability in movement patterns due to repetitive workflows
• sustained wrist positioning, often in slight extension
• gradual fatigue-related changes in speed, timing, or consistency over extended sessions
These patterns reflect task-specific motor behavior associated with sustained fine motor activity.
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🏭 Other Professions and Task-Based Patterns
Different occupational or task-related activities may produce characteristic motion patterns:
Manual Workers / Technicians
• stronger grip-related motion patterns
• higher engagement of full flexion ranges
• repeated force-related movements
Artists / Designers
• varied motion amplitude
• frequent fine motor adjustments
• mixed precision and exploratory movements
Healthcare Professionals / Surgeons (simulation or training contexts)
• controlled, precise, and often slower motion patterns
• stable trajectories with minimal unnecessary movement
• emphasis on accuracy over speed
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🔬 INTERPRETATION
All observed patterns:
• represent task-dependent motion behavior
• vary between individuals
• depend on experience, ergonomics, and fatigue
• are influenced by environment and input devices
They should be interpreted as:
✔ observational
✔ comparative
✔ exploratory
They are not classifications, diagnoses, or performance judgments.
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🚀 FUTURE RESEARCH AND OBJECTIVE STUDIES
The application may support future research directions including:
1. Motion Pattern Analysis
• identification of common movement signatures across tasks
• clustering of motion profiles for different activity types
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2. Ergonomic Studies
• analysis of repetitive motion patterns
• evaluation of fatigue-related changes over time
• comparison of different interaction methods (keyboard vs XR vs touch)
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3. Skill and Training Analysis
• comparison between trained and untrained users
• evaluation of coordination and timing consistency
• tracking improvement across repeated sessions
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4. Human–Computer Interaction (HCI)
• optimization of gesture-based interfaces
• evaluation of input efficiency and usability
• design of more ergonomic interaction systems
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5. Dataset Development
• collection of anonymized motion datasets
• time-series analysis of joint and trajectory data
• development of machine learning models for motion recognition
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6. Spatial Computing Research
• analysis of 3D movement strategies
• evaluation of mid-air interaction fatigue
• optimization of spatial UI placement and interaction zones
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⚠️ FINAL NOTE
All observations and potential research applications are based on algorithm-derived motion estimations.
They are intended for:
• research
• education
• motion visualization
They are not intended for medical evaluation, diagnosis, or treatment.
MEDICAL DISCLAIMER
OrthoHand Motion is not a medical device.
The application is intended solely for educational, research, and informational purposes.
The measurements generated by the software:
• are estimates based on computer-vision algorithms
• may contain errors
• should not be used for diagnosis
• should not be used for clinical decision making
• should not replace professional medical evaluation
Users should always consult qualified healthcare professionals for medical advice.
OrthoHand Motion does not provide diagnosis or treatment recommendations.
The application:
• does not claim to diagnose disease
• does not claim to monitor medical conditions
• does not claim to guide medical procedures
Because of this:
The software does not meet the definition of a regulated medical device under:
• EU MDR Article 2
• FDA Software as Medical Device definitions
Instead, the app is categorized as:
Biomechanical visualization and motion-analysis software for educational and research purposes.
Therefore regulatory clearance such as CE marking or FDA approval is not required.
The application does not provide medical diagnosis, treatment recommendations, or clinical decision support.
The application offers motion visualization and estimated parameters that may provide an early indication that further evaluation by a qualified healthcare professional may be warranted.
All outputs are algorithm-derived estimations and may contain inaccuracies.
Clinical judgment and professional expertise are required when interpreting any motion observations.
The application does not replace a medical doctor or specialist.
Users must not rely on the application as the sole basis for medical decisions.
The software is not intended for primary image interpretation.
Any decisions made based on the application remain the responsibility of the user.
Users should seek professional medical advice before making any health-related decisions.
PRIVACY POLICY
OrthoHand Motion processes motion data locally on the device.
The application does not collect personally identifiable information.
Motion measurements are generated in real time and remain on the device unless the user explicitly exports them.
No data is used for advertising or tracking.
Any future research data contribution features will require explicit user consent.