Murilo Santos de Castro

dblp:364/9242 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 1 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 2 since 2021
YearPublicationVenuePosition
2024 Interaction in Virtual Environments Using Smartwatches: A Comparative Usability Study Between Continuous Gesture Recognition and MDDTW
abstract
This work investigated the usability of two interaction techniques in low-cost virtual environments using smart-watches: on-screen continuous gesture recognition and the MDDTW algorithm for touchless gestures. While continuous gesture recognition requires direct interaction on the device's screen, MDDTW allows users to perform gestures in the air without the need for physical touch. Although users initially preferred continuous gesture recognition, the results revealed that MDDTW achieved slightly higher scores. This underscores the crucial importance of considering user experience in the development of new technologies. The comparative analysis between the two approaches contributes to the design and implementation of interactions in accessible virtual environments, especially concerning the integration of physical gestures as part of the interaction. This work contributes to understanding the factors influencing usability in virtual environments and highlights the need for user-centered approaches in designing interactive technologies.
Murilo Santos de Castro, Fabrízzio Alphonsus A. M. N. Soares, Luciana Cardoso, Renan V. Aranha, Thamer H. Nascimento
COMPSAC1
2024 Exploring Drum Percussion Simulation with Gesture Recognition and Smartwatches for Interactive Duets
abstract
In this work, we propose a method for recognizing percussive gestures using smartwatches with accelerometers and the MDDTW algorithm, incorporating an activation threshold to identify the beginning of gestures. We developed a system that allows simulating drum percussion in a musical duet, providing an interactive and engaging experience for users. Our method utilizes an activation threshold based on the value of gravity to identify the onset of percussive gestures, enabling precise and efficient detection of user movements. We conducted a controlled experiment where participants were instructed to perform predefined percussive gestures, which were captured by the smartwatch sensor and processed by the system. The results demonstrated good accuracy, with a consistent recall rate, indicating the system's ability to correctly identify performed gestures. The Fl-score, as a combined measure of precision and recall, confirmed the overall good performance of the method.
Murilo Santos de Castro, Fabrízzio Alphonsus A. M. N. Soares, Luciana Cardoso, Renan V. Aranha, Thamer H. Nascimento
COMPSAC2