Maxine Annel Pacheco-Ramírez

Maxine Annel Pacheco-Ramírez

orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 April 2024 in Sensors
Verified
Journal Article
Open access
PDF file
MHMaría A. Hernández-Mustieles
María A. Hernández-Mustieles
Yoshua Erenoldo Lima CarmonaYoshua Erenoldo Lima Carmona
Yoshua Erenoldo Lima Carmona
Maxine Annel Pacheco-RamírezMaxine Annel Pacheco-Ramírez
Maxine Annel Pacheco-Ramírez
Axel Amisaday Mendoza ArmentaAxel Amisaday Mendoza Armenta
Axel Amisaday Mendoza Armenta
JRJosé Esteban Romero-Gómez
José Esteban Romero-Gómez
Jorge de Jesús Lozoya-SantosJorge de Jesús Lozoya-Santos
Jorge de Jesús Lozoya-Santos
Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012–2022), highlighting the evolution of this field to address challenges in education by integrating technology to solve specific educational challenges, such as enhancing student engagement, monitoring stress and cognitive load, improving learning experiences, and providing real-time feedback for both students and educators. By exploring these aspects, this review sheds light on the potential implications of WBT on the future of learning. A rigorous and systematic search of major academic databases, including Google Scholar and Scopus, was conducted in accordance with the PRISMA guidelines. Relevant studies were selected based on predefined inclusion and exclusion criteria. The articles selected were assessed for methodological quality and bias using established tools. The process of data extraction and synthesis followed a structured framework. Key findings include the shift from theoretical exploration to practical implementation, with EEG being the predominant measurement, aiming to explore mental states, physiological constructs, and teaching effectiveness. Wearable biosensors are significantly impacting the educational field, serving as an important resource for educators and a tool for students. Their application has the potential to transform and optimize academic practices through sensors that capture biometric data, enabling the implementation of metrics and models to understand the development and performance of students and professors in an academic environment, as well as to gain insights into the learning process.

14 March 2024 in Preprints.org
Verified
Preprint
Open access
PDF file
MHMaría A. Hernández-Mustieles
María A. Hernández-Mustieles
Yoshua Erenoldo Lima CarmonaYoshua Erenoldo Lima Carmona
Yoshua Erenoldo Lima Carmona
Maxine Annel Pacheco-RamírezMaxine Annel Pacheco-Ramírez
Maxine Annel Pacheco-Ramírez
Axel Amisaday Mendoza ArmentaAxel Amisaday Mendoza Armenta
Axel Amisaday Mendoza Armenta
JRJosé Esteban Romero-Gómez
José Esteban Romero-Gómez
Jorge de Jesús Lozoya-SantosJorge de Jesús Lozoya-Santos
Jorge de Jesús Lozoya-Santos
Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012-2022), highlighting both the evolution of this field and its integration to address challenges in education by integrating technology to solve specific educational challenges, such as enhancing student engagement, monitoring stress and cognitive load, improving learning experiences, and providing real-time feedback for both students and educators. By exploring these aspects, the review sheds light on the potential implications of WBT for the future of learning. A rigorous and systematic search of major academic databases, including Google Scholar and Scopus, was conducted in accordance with PRISMA guidelines. Relevant studies were selected based on predefined inclusion and exclusion criteria. The articles selected were assessed for methodological quality and bias using established tools. The process of data extraction and synthesis followed a structured framework. Key findings include the shift from theoretical exploration to practical implementation with the EEG being the predominant measurement, aiming to explore mental states, physiological constructs, and teaching effectiveness. Wearable biosensors are significantly impacting the educational field, serving as an important resource for educators and a tool for students. Their application has the potential to transform and optimize academic practices through sensors that capture biometric data, enabling the implementation of metrics and models to understand the development and performance of students and professors in an academic environment, as well as to gain insights into the learning process.

21 February 2025 in Sensors
Verified
Journal Article
Open access
PDF file
JEJuan Jose Gonzalez Espana
Juan Jose Gonzalez Espana
LSLianne Sánchez-Rodríguez
Lianne Sánchez-Rodríguez
Maxine Annel Pacheco-RamírezMaxine Annel Pacheco-Ramírez
Maxine Annel Pacheco-Ramírez
JFJeff Feng
Jeff Feng
KNKathryn Nedley
Kathryn Nedley
Jose L Contreras-VidalJose L Contreras-Vidal
Jose L Contreras-Vidal
Background: Democratized access to safe and effective robotic neurorehabilitation for stroke survivors requires innovative, affordable solutions that can be used not only in clinics but also at home. This requires the high usability of the devices involved to minimize costs associated with support from physical therapists or technicians. Methods: This paper describes the early findings of the NeuroExo brain–machine interface (BMI) with an upper-limb robotic exoskeleton for stroke neurorehabilitation. This early feasibility study consisted of a six-week protocol, with an initial training and BMI calibration phase at the clinic followed by 60 sessions of neuromotor therapy at the homes of the participants. Pre- and post-assessments were used to assess users’ compliance and system performance. Results: Participants achieved a compliance rate between 21% and 100%, with an average of 69%, while maintaining adequate signal quality and a positive perceived BMI performance during home usage with an average Likert scale score of four out of five. Moreover, adequate signal quality was maintained for four out of five participants throughout the protocol. These findings provide valuable insights into essential components for comprehensive rehabilitation therapy for stroke survivors. Furthermore, linear mixed-effects statistical models showed a significant reduction in trial duration (p-value < 0.02) and concomitant changes in brain patterns (p-value < 0.02). Conclusions: the analysis of these findings suggests that a low-cost, safe, simple-to-use BMI system for at-home stroke rehabilitation is feasible.

9 November 2024 in Scientific Data
Verified
Journal Article
Open access
PDF file
Maxine Annel Pacheco-RamírezMaxine Annel Pacheco-Ramírez
Maxine Annel Pacheco-Ramírez
Mauricio Adolfo Ramírez-MorenoMauricio Adolfo Ramírez-Moreno
Mauricio Adolfo Ramírez-Moreno
KKKomal Kukkar
Komal Kukkar
NRNishant Rao
Nishant Rao
DHDerek Huber
Derek Huber
Jose L Contreras-VidalJose L Contreras-Vidal
Jose L Contreras-Vidal
This report contains a description of physiological and motion data, recorded simultaneously and in synchrony using the hyperscanning method from two professional dancers using wireless mobile brain-body imaging (MoBI) technology during rehearsals and public performances of “LiveWire” - a new composition comprised of five choreographed music and dance sections inspired by neuroscience principles. Brain and ocular activity were measured using 28-channel scalp electroencephalography (EEG), and 4-channel electrooculography (EOG), respectively; and head motion was recorded using an inertial measurement unit (IMU) placed on the forehead of each dancer. Video recordings were obtained for each session to allow for tagging of physiological and motion signals and for behavioral analysis. Data recordings were collected from 10 sessions over a 4-month period, in which the dancers rehearsed or performed (in front of an audience) choreographed expressive movements. A detailed explanation of the experimental set-up, the steps carried out for data collection, and an explanation on the usage are provided in this report.

27 February 2026
Verified
Book Chapter
Closed access
PDF file
AAAime J. Aguilar-Herrera
Aime J. Aguilar-Herrera
CHCarlos O. Hernández-Aguado
Carlos O. Hernández-Aguado
JMJoel A. Monarres-Sokolovskaya
Joel A. Monarres-Sokolovskaya
Maxine Annel Pacheco-RamírezMaxine Annel Pacheco-Ramírez
Maxine Annel Pacheco-Ramírez
BKBadie Khaleghian
Badie Khaleghian
Jose L Contreras-VidalJose L Contreras-Vidal
Jose L Contreras-Vidal

1 January 2026 in IEEE Data Descriptions
Verified
Journal Article
Open access
Maxine Annel Pacheco-RamírezMaxine Annel Pacheco-Ramírez
Maxine Annel Pacheco-Ramírez
AKAntonina Klatka
Antonina Klatka
AAAime J. Aguilar-Herrera
Aime J. Aguilar-Herrera
Yoshua Erenoldo Lima CarmonaYoshua Erenoldo Lima Carmona
Yoshua Erenoldo Lima Carmona
LSLianne Sánchez-Rodríguez
Lianne Sánchez-Rodríguez
Jose L Contreras-VidalJose L Contreras-Vidal
Jose L Contreras-Vidal