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Hernández-Mustieles MA, Lima-Carmona YE, Pacheco-Ramírez MA, Mendoza-Armenta AA, Romero-Gómez JE, Cruz-Gómez CF, Rodríguez-Alvarado DC, Arceo A, Cruz-Garza JG, Ramírez-Moreno MA, Lozoya-Santos JDJ. Wearable Biosensor Technology in Education: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2024; 24:2437. [PMID: 38676053 PMCID: PMC11054421 DOI: 10.3390/s24082437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 03/31/2024] [Accepted: 04/02/2024] [Indexed: 04/28/2024]
Abstract
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.
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Affiliation(s)
- María A. Hernández-Mustieles
- Mechatronics Department, School of Engineering and Sciences, Monterrey Campus, Tecnologico de Monterrey, Monterrey 64700, Mexico; (M.A.H.-M.); (Y.E.L.-C.); (M.A.P.-R.); (A.A.M.-A.); (C.F.C.-G.); (D.C.R.-A.); (A.A.); (M.A.R.-M.)
| | - Yoshua E. Lima-Carmona
- Mechatronics Department, School of Engineering and Sciences, Monterrey Campus, Tecnologico de Monterrey, Monterrey 64700, Mexico; (M.A.H.-M.); (Y.E.L.-C.); (M.A.P.-R.); (A.A.M.-A.); (C.F.C.-G.); (D.C.R.-A.); (A.A.); (M.A.R.-M.)
| | - Maxine A. Pacheco-Ramírez
- Mechatronics Department, School of Engineering and Sciences, Monterrey Campus, Tecnologico de Monterrey, Monterrey 64700, Mexico; (M.A.H.-M.); (Y.E.L.-C.); (M.A.P.-R.); (A.A.M.-A.); (C.F.C.-G.); (D.C.R.-A.); (A.A.); (M.A.R.-M.)
| | - Axel A. Mendoza-Armenta
- Mechatronics Department, School of Engineering and Sciences, Monterrey Campus, Tecnologico de Monterrey, Monterrey 64700, Mexico; (M.A.H.-M.); (Y.E.L.-C.); (M.A.P.-R.); (A.A.M.-A.); (C.F.C.-G.); (D.C.R.-A.); (A.A.); (M.A.R.-M.)
| | - José Esteban Romero-Gómez
- Mechatronics Department, School of Engineering and Sciences, Guadalajara Campus, Tecnologico de Monterrey, Guadalajara 45201, Mexico;
| | - César F. Cruz-Gómez
- Mechatronics Department, School of Engineering and Sciences, Monterrey Campus, Tecnologico de Monterrey, Monterrey 64700, Mexico; (M.A.H.-M.); (Y.E.L.-C.); (M.A.P.-R.); (A.A.M.-A.); (C.F.C.-G.); (D.C.R.-A.); (A.A.); (M.A.R.-M.)
| | - Diana C. Rodríguez-Alvarado
- Mechatronics Department, School of Engineering and Sciences, Monterrey Campus, Tecnologico de Monterrey, Monterrey 64700, Mexico; (M.A.H.-M.); (Y.E.L.-C.); (M.A.P.-R.); (A.A.M.-A.); (C.F.C.-G.); (D.C.R.-A.); (A.A.); (M.A.R.-M.)
| | - Alejandro Arceo
- Mechatronics Department, School of Engineering and Sciences, Monterrey Campus, Tecnologico de Monterrey, Monterrey 64700, Mexico; (M.A.H.-M.); (Y.E.L.-C.); (M.A.P.-R.); (A.A.M.-A.); (C.F.C.-G.); (D.C.R.-A.); (A.A.); (M.A.R.-M.)
| | - Jesús G. Cruz-Garza
- Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA;
| | - Mauricio A. Ramírez-Moreno
- Mechatronics Department, School of Engineering and Sciences, Monterrey Campus, Tecnologico de Monterrey, Monterrey 64700, Mexico; (M.A.H.-M.); (Y.E.L.-C.); (M.A.P.-R.); (A.A.M.-A.); (C.F.C.-G.); (D.C.R.-A.); (A.A.); (M.A.R.-M.)
| | - Jorge de J. Lozoya-Santos
- Mechatronics Department, School of Engineering and Sciences, Monterrey Campus, Tecnologico de Monterrey, Monterrey 64700, Mexico; (M.A.H.-M.); (Y.E.L.-C.); (M.A.P.-R.); (A.A.M.-A.); (C.F.C.-G.); (D.C.R.-A.); (A.A.); (M.A.R.-M.)
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Ramírez-Moreno MA, Cruz-Garza JG, Acharya A, Chatufale G, Witt W, Gelok D, Reza G, Contreras-Vidal JL. Brain-to-brain communication during musical improvisation: a performance case study. F1000Res 2023; 11:989. [PMID: 37809054 PMCID: PMC10558998 DOI: 10.12688/f1000research.123515.3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/01/2023] [Indexed: 10/10/2023] Open
Abstract
Understanding and predicting others' actions in ecological settings is an important research goal in social neuroscience. Here, we deployed a mobile brain-body imaging (MoBI) methodology to analyze inter-brain communication between professional musicians during a live jazz performance. Specifically, bispectral analysis was conducted to assess the synchronization of scalp electroencephalographic (EEG) signals from three expert musicians during a three-part 45 minute jazz performance, during which a new musician joined every five minutes. The bispectrum was estimated for all musician dyads, electrode combinations, and five frequency bands. The results showed higher bispectrum in the beta and gamma frequency bands (13-50 Hz) when more musicians performed together, and when they played a musical phrase synchronously. Positive bispectrum amplitude changes were found approximately three seconds prior to the identified synchronized performance events suggesting preparatory cortical activity predictive of concerted behavioral action. Moreover, a higher amount of synchronized EEG activity, across electrode regions, was observed as more musicians performed, with inter-brain synchronization between the temporal, parietal, and occipital regions the most frequent. Increased synchrony between the musicians' brain activity reflects shared multi-sensory processing and movement intention in a musical improvisation task.
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Affiliation(s)
- Mauricio A. Ramírez-Moreno
- School of Engineering and Sciences, Mechatronics Department, Tecnologico de Monterrey, Monterrey, Nuevo Leon, 64849, Mexico
- Noninvasive Brain-Machine Interface Systems Laboratory, NSF IUCRC BRAIN, University of Houston, Houston, Texas, 77004, USA
| | - Jesús G. Cruz-Garza
- Noninvasive Brain-Machine Interface Systems Laboratory, NSF IUCRC BRAIN, University of Houston, Houston, Texas, 77004, USA
| | - Akanksha Acharya
- Noninvasive Brain-Machine Interface Systems Laboratory, NSF IUCRC BRAIN, University of Houston, Houston, Texas, 77004, USA
| | - Girija Chatufale
- Noninvasive Brain-Machine Interface Systems Laboratory, NSF IUCRC BRAIN, University of Houston, Houston, Texas, 77004, USA
- University of California, Los Angeles, Los Angeles, California, 90095, USA
| | - Woody Witt
- Moores School of Music, University of Houston, Houston, Texas, 77004, USA
- Houston Community College, Houston, Texas, 77004, USA
| | - Dan Gelok
- Moores School of Music, University of Houston, Houston, Texas, 77004, USA
| | | | - José L. Contreras-Vidal
- Noninvasive Brain-Machine Interface Systems Laboratory, NSF IUCRC BRAIN, University of Houston, Houston, Texas, 77004, USA
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Rao N, Paek A, Contreras-Vidal JL, Parikh PJ. Lateralized Neural Entropy modulates with Grip Force during Precision Grasping. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.07.539751. [PMID: 37214821 PMCID: PMC10197571 DOI: 10.1101/2023.05.07.539751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
When holding a coffee mug filled to the brim, we strive to avoid spilling the coffee. This ability relies on the neural processes underlying the control of finger forces on a moment-to-moment basis. The brain activity lateralized to the contralateral hemisphere averaged over a trial and across the trials is known to be associated with the magnitude of grip force applied on an object. However, the mechanistic involvement of the variability in neural signals during grip force control remains unclear. In this study, we examined the dependence of neural variability over the frontal, central, and parietal regions assessed using noninvasive electroencephalography (EEG) on grip force magnitude during an isometric force control task. We hypothesized laterally specific modulation in EEG variability with higher magnitude of the grip force exerted during grip force control. We utilized an existing EEG dataset (64 channel) comprised of healthy young adults, who performed an isometric force control task while receiving visual feedback of the force applied. The force magnitude to be exerted on the instrumented object was cued to participants during the task, and varied pseudorandomly among 5, 10, and 15% of their maximum voluntary contraction (MVC) across the trials. We quantified neural variability via sample entropy (sequence-dependent measure) and standard deviation (sequence-independent measure) of the temporal EEG signal over the frontal, central, and parietal electrodes. The EEG sample entropy over the central electrodes showed lateralized, nonlinear, localized, modulation with force magnitude. Similar modulation was not observed over frontal or parietal EEG activity, nor for standard deviation in the EEG activity. Our findings highlight specificity in neural control of grip forces by demonstrating the modulation in sequence-dependent but not sequence-independent component of EEG variability. This modulation appeared to be lateralized, spatially constrained, and functionally dependent on the grip force magnitude. We discuss the relevance of these findings in scenarios where a finer precision is essential to enable grasp application, such as prosthesis and associated neural signal integration, and propose directions for future studies investigating the mechanistic role of neural entropy in grip force control.
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Hu Y, Ouyang J, Wang H, Zhang J, Liu A, Min X, Du X. Design Meets Neuroscience: An Electroencephalogram Study of Design Thinking in Concept Generation Phase. Front Psychol 2022; 13:832194. [PMID: 35310227 PMCID: PMC8928580 DOI: 10.3389/fpsyg.2022.832194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 02/09/2022] [Indexed: 11/25/2022] Open
Abstract
Extant research on design thinking is subjective and limited. This manuscript combines protocol analysis and electroencephalogram (EEG) to read design thoughts in the core design activities of concept generation phase. The results suggest that alpha band power had event related synchronization (ERS) in the scenario task and divergent thinking occupies a dominant position. However, it had event related desynchronization (ERD) in analogy and inference activities, etc., and it is stronger for mental pressure and exercised cognitive processing. In addition, the parietooccipital area differs significantly from other brain areas in most design activities. This study explores the relationship of different design thinking and EEG data, which is innovative and professional in the field of design, providing a more objective data basis and evaluation method for future applied research and diverse educational practices.
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Affiliation(s)
- Ying Hu
- School of Design, Hunan University, Changsha, China
| | | | - Huazhen Wang
- School of Design, Hunan University, Changsha, China
| | - Juan Zhang
- School of Statistics, Capital University of Economics and Business, Beijing, China
| | - An Liu
- College of Furniture and Design, Central South University of Forestry and Technology, Changsha, China
| | - Xiaolei Min
- School of Design, Hunan University, Changsha, China
| | - Xing Du
- School of Design, Hunan University, Changsha, China
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