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Updated: Sep 22, 2025

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor

Published on: February 12, 2018

Hand Motion Analysis during the Execution of the Action Research Arm Test Using Multiple Sensors.

Jesus Fernando Padilla-Magaña^1,2, Esteban Peña-Pitarch¹, Isahi Sánchez-Suarez²

¹Escola Politècnica Superior d'Enginyeria de Manresa (EPSEM), Polytechnic University of Catalonia, 08242 Manresa, Barcelona, Spain.

Sensors (Basel, Switzerland)

|May 20, 2022

Summary

This study quantifies finger joint angles and forces during the Action Research Arm Test (ARAT) using sensors. Findings reveal objective hand function data, enhancing clinical assessments for therapists.

Keywords:

action research arm test finger joints fingertip force flexion angle hand

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Last Updated: Sep 22, 2025

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Area of Science:

Biomedical Engineering
Rehabilitation Science
Biomechanics

Background:

The Action Research Arm Test (ARAT) is a standard tool for assessing upper limb function.
Integrating sensor technology can enhance the objectivity and sensitivity of the ARAT.
Quantifying hand kinematics and kinetics provides deeper insights into functional performance.

Purpose of the Study:

To measure finger joint flexion angles and fingertip forces during ARAT subscales (Grasp, Grip, Pinch).
To evaluate the feasibility of using a data glove and force sensors for ARAT analysis.
To establish normative sensor data for healthy individuals performing the ARAT.

Main Methods:

An experimental study involving 25 healthy, right-handed subjects.
Simultaneous measurement of finger joint angles using a CyberGlove II data glove.
Measurement of fingertip forces using five force-sensing resistors (FSRs).

Main Results:

Detailed mean flexion angles for thumb, index, middle, ring, and little finger joints were recorded.
Average fingertip forces were 8.2 N (Grasp), 6.61 N (Grip), and 3.89 N (Pinch).
Significant variations in joint angles and forces were observed across different ARAT activities.

Conclusions:

Sensor integration provides a sensitive, objective, and quantitative method for assessing hand function via the ARAT.
This approach offers valuable data for clinicians and therapists in rehabilitation.
The findings support the clinical relevance of sensor-based kinematic and kinetic analysis in hand function evaluation.