Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: May 10, 2026

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

An optoelectronic based approach for handwriting capture.

Andrea Ancillao¹, Manuela Galli, Sara Laura Vimercati

¹IRCCS San Raffaele Pisana, San Raffaele SPA, via della Pisana 235, 00166 Roma, Italy. andrea.ancillao@hotmail.com

Computer Methods and Programs in Biomedicine

|June 8, 2013

Summary

A new non-invasive optoelectronic system accurately captures pen motion for evaluating motor and cognitive skills through handwriting and drawing analysis. This method improves upon existing technologies, offering greater precision and overcoming previous limitations.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Impaired pendulum-like mechanics during post-stroke walking: a biomechanical comparison with healthy individuals.

Frontiers in neurology·2026

Same author

A Multicenter Standardized Gait Database from the ORITEL Network for Cerebral Palsy Gait Analysis.

IEEE journal of biomedical and health informatics·2026

Same author

Effects of vibration frequency, amplitude, and direction on human gait metrics.

Journal of biomechanics·2025

Same author

Tracking Dynamic Functional Connectivity Using Time-Varying Multivariate Autoregressive Models: an EEG Study of Sensorimotor Processes.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same author

Analysis of Quasi-Simultaneous Laser Welding in T-Joint Configuration for PMMA-ABS Using Circular Wobble Geometry.

Materials (Basel, Switzerland)·2025

Same author

Using climbing to quantify motor asymmetry in children with cerebral palsy: a pilot study.

Frontiers in sports and active living·2025

Area of Science:

Biomechanics
Human-Computer Interaction
Neuroscience

Background:

Clinical evaluation of motor and cognitive functions frequently uses handwriting and drawing tests.
Existing methods for capturing pen movements have limitations, necessitating improved non-invasive techniques.

Purpose of the Study:

To develop and validate a novel non-invasive method for capturing pen motion using an optoelectronic motion capture system.
To overcome limitations of graphic tablet-based systems and previous marker-based approaches.

Main Methods:

An optoelectronic motion capture system tracked four infrared passive markers placed on a pen cap.
A numerical algorithm computed the pen tip's 3D trajectory using marker coordinates.
Tests were conducted to assess track reconstruction error and compare with prior methods.

Keywords:

Drawing Handwriting Motion capture Optoelectronic system

More Related Videos

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment

Published on: March 11, 2021

Related Experiment Videos

Last Updated: May 10, 2026

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment

Published on: March 11, 2021

Main Results:

The developed method demonstrated higher accuracy in track reconstruction compared to previous techniques.
The protocol effectively addressed issues of pen grasping and marker obstruction.
The system enables detailed kinematic and postural behavior analysis during writing and drawing.

Conclusions:

This novel optoelectronic system provides a more accurate and robust method for analyzing handwriting and drawing kinematics.
The technology has the potential to enhance clinical assessments of motor and cognitive capabilities.
It offers a significant advancement over existing pen-tracking technologies.