Rodríguez, Jafet
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Preferred name
Rodríguez, Jafet
Official Name
Rodríguez Muñoz, Arturo Jafet
Main Affiliation
ORCID
Scopus Author ID
57192985100
Researcher ID
E-8210-2016

Research Output

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Affect-Driven VR Environment for Increasing Muscle Activity in Assisted Gait Rehabilitation

2024 , Rodríguez, Jafet , Del-Valle-Soto, Carolina , Gonzalez Sanchez, Javier

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On the characterization strategy of a voter transition method and its influence on social choice

2017 , Alcaraz Rivera, Miguel , Del-Valle-Soto, Carolina , Rodríguez, Jafet

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Affective States and Virtual Reality to Improve Gait Rehabilitation: A Preliminary Study

2022 , Rodríguez, Jafet , Del-Valle-Soto, Carolina , Javier Gonzalez-Sanchez

Over seven million people suffer from an impairment in Mexico; 64.1% are gait-related, and 36.2% are children aged 0 to 14 years. Furthermore, many suffer from neurological disorders, which limits their verbal skills to provide accurate feedback. Robot-assisted gait therapy has shown significant benefits, but the users must make an active effort to accomplish muscular memory, which usually is only around 30% of the time. Moreover, during therapy, the patients’ affective state is mostly unsatisfied, wide-awake, and powerless. This paper proposes a method for increasing the efficiency by combining affective data from an Emotiv Insight, an Oculus Go headset displaying an immersive interaction, and a feedback system. Our preliminary study had eight patients during therapy and eight students analyzing the footage using the self-assessment Manikin. It showed that it is possible to use an EEG headset and identify the affective state with a weighted average precision of 97.5%, recall of 87.9%, and F1-score of 92.3% in general. Furthermore, using a VR device could boost efficiency by 16% more. In conclusion, this method allows providing feedback to the therapist in real-time even if the patient is non-verbal and has a limited amount of facial and body expressions.

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AdaptiBrush

2021 , Rosales, Enrique , Chrystiano Araújo , Rodríguez, Jafet , Nicholas Vining , Dongwook Yoon , Alla Sheffer

Virtual reality drawing applications let users draw 3D shapes using brushes that form ribbon shaped, or ruled-surface, strokes. Each ribbon is uniquely defined by its user-specified ruling length, path, and the ruling directions at each point along this path. Existing brushes use the trajectory of a handheld controller in 3D space as the ribbon path, and compute the ruling directions using a fixed mapping from a specific controller coordinate-frame axis. This fixed mapping forces users to rotate the controller and thus their wrists to change ribbon normal or ruling directions, and requires substantial physical effort to draw even medium complexity ribbons. Since human ability to rotate their wrists continuously is heavily restricted, the space of ribbon geometries users can comfortably draw using these brushes is limited. These brushes can be unpredictable, producing ribbons with unexpectedly varying width or flipped and wobbly normals in response to seemingly natural hand gestures. Our AdaptiBrush ribbon brush system dramatically extends the space of ribbon geometries users can comfortably draw while enabling them to accurately predict the ribbon shape that a given hand motion produces. We achieve this by introducing a novel adaptive ruling direction computation method, enabling users to easily change ribbon ruling and normal orientation using predominantly translational controller, and thus wrist, motion. We facilitate ease-of-use by computing predictable ruling directions that smoothly change in both world and controller coordinate systems, and facilitate ease-of-learning by prioritizing ruling directions which are well-aligned with one of the controller coordinate system axes. Our comparative user studies confirm that our more general and predictable ruling computation leads to significant improvements in brush usability and effectiveness compared to all prior brushes; in a head to head comparison users preferred AdaptiBrush over the next-best brush by a margin of 2 to 1.

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Predictive Tool for Planning the Scaling and Interference of Wireless Sensor Networks

2018 , Rodríguez, Jafet , Del-Valle-Soto, Carolina

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Decentralization: The Failed Promise of Cryptocurrencies

2019 , Valdivia, Leonardo , Del-Valle-Soto, Carolina , Rodríguez, Jafet , Alcaraz Rivera, Miguel

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Neuromarketing in the Digital Age: The Direct Relation between Facial Expressions and Website Design

2022 , Guillermo González-Mena , Del-Valle-Soto, Carolina , Corona, Violeta , Rodríguez, Jafet

User experience (UX) is key in the immediate and future relationship between the client and business. Achieving a satisfying UX can only be achieved by understanding the wishes and user needs. The following study is carried out as an improvement tool for a Mexican coffee company. The objective is to achieve greater efficiency, attraction, and engagement on the part of the user. The main question is whether the new dynamic website design can directly increase the valence of user emotions compared to the static website design. To answer this question, 39 participants were exposed to the two different web page designs and elicited the following emotions using eye tracking and facial expression analysis (FEA) techniques: joy, anger, surprise, fear, contempt, disgust, sadness, neutral, positive, and negative. Through a Wilcoxon signed-rank test, the results showed a significant increase for the new dynamic design in the following emotions; joy, anger, surprise, disgust, fear and neutral. Thus, five of the seven basic emotions had a significant change that could lead to greater attraction and commitment on the part of the user and also influence, either consciously or unconsciously, their decision when interacting with the company.

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CML-WSN: A Configurable Multi-layer Wireless Sensor Network Simulator

2016 , Del-Valle-Soto, Carolina , Fernando Lezama , Rodríguez, Jafet , Carlos Mex-Perera , Enrique Munoz de Cote

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SurfaceBrush

2019 , Rosales, Enrique , Rodríguez, Jafet , ALLA SHEFFER

Popular Virtual Reality (VR) tools allow users to draw varying-width, ribbonlike 3D brush strokes by moving a hand-held controller in 3D space. Artists frequently use dense collections of such strokes to draw virtual 3D shapes. We propose SurfaceBrush , a surfacing method that converts such VR drawings into user-intended manifold free-form 3D surfaces, providing a novel approach for modeling 3D shapes. The inputs to our method consist of dense collections of artist-drawn stroke ribbons described by the positions and normals of their central polylines, and ribbon widths. These inputs are highly distinct from those handled by existing surfacing frameworks and exhibit different sparsity and error patterns, necessitating a novel surfacing approach. We surface the input stroke drawings by identifying and leveraging local coherence between nearby artist strokes. In particular, we observe that strokes intended to be adjacent on the artist imagined surface often have similar tangent directions along their respective polylines. We leverage this local stroke direction consistency by casting the computation of the user-intended manifold surface as a constrained matching problem on stroke polyline vertices and edges. We first detect and smoothly connect adjacent similarly-directed sequences of stroke edges producing one or more manifold partial surfaces. We then complete the surfacing process by identifying and connecting adjacent similarly directed edges along the borders of these partial surfaces. We confirm the usability of the SurfaceBrush interface and the validity of our drawing analysis via an observational study. We validate our stroke surfacing algorithm by demonstrating an array of manifold surfaces computed by our framework starting from a range of inputs of varying complexity, and by comparing our outputs to reconstructions computed using alternative means.

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