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Related Experiment Video

Updated: Dec 18, 2025

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes

Published on: September 6, 2024

Using UHF RFID Properties to Develop and Optimize an Upper-Limb Rehabilitation System.

Walter Baccinelli^1,2, Maria Bulgheroni¹, Carlo Albino Frigo²

¹R&D Department, Ab.Acus Srl, via F. Caracciolo 77, 20155 Milano, Italy.

Sensors (Basel, Switzerland)

|June 11, 2020

Summary

This study introduces a new radiofrequency (RF) system for effective home-based upper limb telerehabilitation. The system reliably extracts key performance metrics, improving therapy for neuromotor diseases.

Keywords:

RFID movement analysis rehabilitation upper limb

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Last Updated: Dec 18, 2025

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Published on: September 6, 2024

Author Spotlight: Enhancing Upper Limb Rehabilitation in Stroke Patients Through Advanced Robotic and Neuromodulation Technologies

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Published on: October 11, 2024

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Area of Science:

Biomedical Engineering
Rehabilitation Technology
Neuromotor Disease Therapy

Background:

Upper limb rehabilitation is crucial for daily living activities (ADLs) in patients with neuromotor diseases.
High therapy costs and patient numbers necessitate innovative, accessible solutions.
Technology-based approaches, specifically telerehabilitation, offer a promising avenue.

Purpose of the Study:

To present a novel radiofrequency (RF) based system for home-based upper limb telerehabilitation.
To demonstrate the system's capability in extracting meaningful performance metrics during therapy.
To optimize hardware, communication, and software for effective rehabilitation delivery.

Main Methods:

Development of a specialized RF system tailored for rehabilitation needs.
Implementation of a communication protocol and software control for home-based therapy.
Methodology for extracting task execution time, hand movement distance, and velocity profiles.

Main Results:

A highly usable RF-based system for upper limb rehabilitation was successfully developed.
Reliable extraction of performance metrics, including execution time and movement kinematics, was achieved.
The system facilitates effective home-based telerehabilitation for neuromotor conditions.

Conclusions:

RF technology provides a viable and effective platform for home-based upper limb telerehabilitation.
The developed system enables reliable monitoring and data extraction for therapy assessment.
This approach addresses the need for cost-effective and accessible rehabilitation solutions.