Investigational research prototype for controlled measurement studies.
GripTrak 3D on the acquisition bench. Simulator code added to the secondary display.
Grip and trajectory simulatorSimulated
Move to
32 × 64Spatial sensing grid
IMUInertial signals
AprilTagCamera pose research
The research problem
Beyond a Single Grip-Strength Number
Two grips can produce the same peak strength while placing pressure in different areas. During a task such as picking up and placing an object, the grip can also change as the object moves.
Conventional grip-strength measurement
A dynamometer gives a force reading, often summarized as the peak. That answers how hard someone squeezed during the test.
Spatial grip-pressure and movement analysis
GripTrak 3D explores where contact occurs, how the sensor response changes over time, and how the object moves during a controlled task.
Interactive demonstration
Explore a pressure pattern
Change the pattern and intensity to see how spatial contact appears on a heatmap. The default pattern shows four finger contacts on one side and an offset thumb on the other. The contact locations stay fixed as simulated pressure rises and falls.
Technology
How GripTrak 3D Works
The cylinder streams sensor readings to a workstation. A separate camera workflow uses video to estimate where the cylinder moves.
Sensing surface
A flexible 32 × 64 grid responds to contact on the cylinder.
Electronics
The embedded controller scans the grid and reads inertial signals.
Wireless transmission
A gateway forwards the sensor data over Wi-Fi.
Data recording
The workstation reconstructs pressure frames and can record sessions for replay.
Pressure heatmap
The viewer maps relative sensor readings to colour.
Movement visualization
The viewer displays orientation. A separate camera workflow estimates the tagged cylinder’s trajectory.
Spatial pressure sensing
A flexible 32 × 64 matrix samples contact across the cylindrical gripping surface. The heatmap shows relative sensor response in ADC counts.
Pressure sensor layer design alongside the fabricated electrode sheet and top sheet.
Motion and orientation
Gyroscope, accelerometer and magnetometer streams support inspection of motion and visualization of device orientation.
Research viewer with inertial plots, orientation view and camera panel.
Research visualization
The Python tools reconstruct pressure frames, plot inertial channels and support recording and replay for analysis.
Pressure heatmap and inertial traces in the research visualizer. Screenshot input provenance is unconfirmed.
Camera-based tracking
An AprilTag on the device and a calibrated camera support per-frame position and orientation estimates in experimental recordings.
Tagged prototype on the marked lab recording surface.
Pressure-controlled interaction
A proposed game explores press, hold and release controls. Finger-specific mapping and gameplay validation are future work.
Illustrative interface for a proposed finger-pressure game.
Measurement capabilities
What We Can Measure
Demonstrated prototype
Pressure distribution
The 32 × 64 grid shows where contact changes across the grip. Heatmap values are relative sensor response in ADC counts. Force in newtons would require calibration.
Demonstrated prototype
IMU motion signals
Gyroscope, accelerometer and magnetometer traces describe angular motion, acceleration and magnetic field. The viewer uses inertial signals to visualize orientation.
Experimental workflow
Camera-based tracking
A calibrated camera and AprilTag yield per-frame position and orientation estimates. A sequence of estimates describes the object’s trajectory when the marker is visible.
Applications
Questions the platform could help investigate
Research directions build on the current handheld prototype. Future opportunities would require different sensing surfaces, integration and validation.
Current and near-term research
Prototype workflow
Hand grip pressure analysis
Map changes in spatial contact during a grasp.
Potential value · Compare where and when grip patterns change.
Research direction
Neurological motor-control research
Explore grip patterns during controlled research tasks.
Potential value · Develop candidate measurements for approved studies.
Experimental workflow
Grip coordination and movement
Capture pressure and camera pose during object placement.
Potential value · Investigate how contact changes while an object moves.
Research direction
Human–computer interaction
Explore sensing surfaces as an input channel.
Potential value · Compare pressure gestures and feedback designs.
Proposed game concept
Pressure-controlled games
Explore press, hold and release as game inputs.
Potential value · Study whether intentional finger inputs can be distinguished.
Research direction
Grip ergonomics
Investigate contact distribution on handheld objects.
Potential value · Compare alternative handles in controlled tasks.
Future pressure-sensing opportunities
Future opportunity
Plantar pressure and gait
Adapt a sensing layer to a foot-contact surface.
Potential value · Explore loading patterns across a step.
Future opportunity
Wheelchair seating
Explore pressure across a seated contact surface.
Potential value · Compare load distribution across cushion designs.
Future opportunity
Robotic tactile sensing
Adapt spatial sensing to gripper fingers.
Potential value · Observe contact during grasp experiments.
Future opportunity
Prosthetic contact pressure
Explore conformal sensing at a socket interface.
Potential value · Compare contact locations in fit experiments.
Future opportunity
Sports equipment grip
Explore pressure sensing on handles and implements.
Potential value · Compare grip patterns across techniques.
Future opportunity
Industrial ergonomics
Explore sensing on tool handles and contact surfaces.
Potential value · Measure how load is distributed during a task.
Research
Study where contact occurs and how it changes
A controlled object-placement task lets researchers compare grip changes as a person grasps, carries and releases the cylinder.
Research questions
Where does contact occur during pickup and placement?
How does the pressure pattern change as the object moves?
How consistent are the patterns across repeated trials?
Potential measurements
Contact location and relative sensor response over time.
Inertial signals and orientation during handling.
Camera-estimated paths and placement relative to marked targets.
Current limitations
Force calibration and repeatability need bench validation.
Camera estimates depend on calibration and marker visibility.
Timing alignment across pressure, inertial and video streams still needs validation.
Development
From bench hardware to recorded experiments
Early hardware
Bench acquisition
Flexible sensor sheets and an earlier controller documented in bench photos.
Controller iteration
Integrated prototype
Fabricated PCB, printed enclosure and spatial acquisition software.
Recorded experiments
Pose workflow
Tagged object-placement recordings and camera annotation output.
Proposed
Validation and interaction
Evaluate timing, repeatability and finger-specific interaction.
Gallery and demonstrations
See the prototype and workflow
Project photos, CAD, software screenshots and one labeled concept illustration. Select an image to enlarge it.
Two assembled GripTrak 3D research prototypes, including a tagged unit.Pressure sensor layer design alongside the fabricated electrode sheet and top sheet.Fabricated controller PCB with sensor connectors.CAD views of the cylindrical shell, end cap and internal board layout.Pressure heatmap and inertial traces in the research visualizer. Screenshot input provenance is unconfirmed.Research viewer with inertial plots, orientation view and camera panel.Tagged prototype on the marked lab recording surface.Illustrative interface for a proposed finger-pressure game.
GripTrak 3D viewer demonstration
See the research viewer’s pressure heatmap, inertial plots, and orientation display.
Local clip · Recorded AprilTag trial with an estimated pose overlay. Use the YouTube link for the full viewer demo.
Collaborate
Bring a research question
We welcome discussions with university labs, rehabilitation researchers, biomedical and robotics engineers, industry R&D teams, and potential funding or commercialization partners.
Research collaboration
Discuss task design, repeatability studies, sensor calibration, or comparison with a reference camera or instrument.
Research direction
Future opportunity
Future opportunity
Future opportunity
Future opportunity
Future opportunity
Future opportunity
