This paper provides a perspective on the use of RGB-D cameras and non-invasive brain–computer interfaces (BCIs) for human activity recognition (HAR). Then, it explores the potential of integrating both the technologies for active and assisted living. RGB-D cameras can offer monitoring of users in their living environments, preserving their privacy in human activity recognition through depth images and skeleton tracking. Concurrently, non-invasive BCIs can provide access to intent and control of users by decoding neural signals. The synergy between these technologies may allow holistic understanding of both physical context and cognitive state of users, to enhance personalized assistance inside smart homes. The successful deployment in integrating the two technologies needs addressing critical technical hurdles, including computational demands for real-time multi-modal data processing, and user acceptance challenges related to data privacy, security, and BCI illiteracy. Continued interdisciplinary research is essential to realize the full potential of RGB-D cameras and BCIs as AAL solutions, in order to improve the quality of life for independent or impaired people.

RGB-D Cameras and Brain–Computer Interfaces for Human Activity Recognition: An Overview / Iadarola, Grazia; Mengarelli, Alessandro; Iarlori, Sabrina; Monteriù, Andrea; Spinsante, Susanna. - In: SENSORS. - ISSN 1424-8220. - 25:20(2025). [10.3390/s25206286]

RGB-D Cameras and Brain–Computer Interfaces for Human Activity Recognition: An Overview

Iadarola, Grazia
Primo
Conceptualization
;
Mengarelli, Alessandro
Secondo
;
Iarlori, Sabrina;Monteriù, Andrea
Penultimo
;
Spinsante, Susanna
Ultimo
2025-01-01

Abstract

This paper provides a perspective on the use of RGB-D cameras and non-invasive brain–computer interfaces (BCIs) for human activity recognition (HAR). Then, it explores the potential of integrating both the technologies for active and assisted living. RGB-D cameras can offer monitoring of users in their living environments, preserving their privacy in human activity recognition through depth images and skeleton tracking. Concurrently, non-invasive BCIs can provide access to intent and control of users by decoding neural signals. The synergy between these technologies may allow holistic understanding of both physical context and cognitive state of users, to enhance personalized assistance inside smart homes. The successful deployment in integrating the two technologies needs addressing critical technical hurdles, including computational demands for real-time multi-modal data processing, and user acceptance challenges related to data privacy, security, and BCI illiteracy. Continued interdisciplinary research is essential to realize the full potential of RGB-D cameras and BCIs as AAL solutions, in order to improve the quality of life for independent or impaired people.
2025
RGB-D cameras; assisted living; brain–computer interfaces; human activity recognition; wearable devices
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/349736
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