Publications

2024

  1. L. I. Barona López, C. I. León Cifuentes, J. M. Muñoz Oña, A. L. Valdivieso Caraguay, and M. E. Benalcázar, “Hand Gesture Recognition Applied to the Interaction with Video Games,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 14391 LNAI, pp. 36–52, 2024, doi: 10.1007/978-3-031-47765-2_3.
  2. L. I. Barona López, F. M. Ferri, J. Zea, Á. L. Valdivieso Caraguay, and M. E. Benalcázar, “CNN-LSTM and post-processing for EMG-based hand gesture recognition,” Intell. Syst. with Appl., vol. 22, p. 200352, Jun. 2024, doi: 10.1016/J.ISWA.2024.200352.

2023

  1. R. E. Nogales and M. E. Benalcázar, “Analysis and Evaluation of Feature Selection and Feature Extraction Methods,” Int. J. Comput. Intell. Syst., vol. 16, no. 1, pp. 1–13, Dec. 2023, doi: 10.1007/S44196-023-00319-1.
  2. D. Díaz, M. E. Benalcázar, L. Barona, and Á. L. Valdivieso, “Development of a Hand Gesture Recognition Model Capable of Online Readjustment Using EMGs and Double Deep-Q Networks,” Lect. Notes Networks Syst., vol. 691 LNNS, pp. 361–371, 2023, doi: 10.1007/978-3-031-33258-6_34.
  3. G. Saggio, G. Saggio, and M. E. Benalcázar, “Sensor Systems for Gesture Recognition,” Sens. Syst. Gesture Recognit., p. 338, Dec. 2023, doi: 10.3390/BOOKS978-3-0365-8695-3.
  4. J. A. Zea, L. G. M. Santillán, L. I. B. López, Á. L. V. Caraguay, and M. E. Benalcázar, “Effects on Hand Gesture Recognition Accuracy after Severe Cranial Trauma,” ECTM 2023 - 2023 IEEE 7th Ecuador Tech. Chapters Meet., 2023, doi: 10.1109/ETCM58927.2023.10309078.
  5. J. P. Vásconez, L. I. Barona López, Á. L. Valdivieso Caraguay, and M. E. Benalcázar, “A comparison of EMG-based hand gesture recognition systems based on supervised and reinforcement learning,” Eng. Appl. Artif. Intell., vol. 123, p. 106327, Aug. 2023, doi: 10.1016/J.ENGAPPAI.2023.106327.
  6. Á. L. Valdivieso Caraguay, J. P. Vásconez, L. I. Barona López, and M. E. Benalcázar, “Recognition of Hand Gestures Based on EMG Signals with Deep and Double-Deep Q-Networks,” Sensors 2023, Vol. 23, Page 3905, vol. 23, no. 8, p. 3905, Apr. 2023, doi: 10.3390/S23083905.
  7. R. E. Nogales and M. E. Benalcázar, “Hand Gesture Recognition Using Automatic Feature Extraction and Deep Learning Algorithms with Memory,” Big Data Cogn. Comput. 2023, Vol. 7, Page 102, vol. 7, no. 2, p. 102, May 2023, doi: 10.3390/BDCC7020102.

2022

  1. J. P. Vásconez, L. I. Barona López, Á. L. Valdivieso Caraguay, and M. E. Benalcázar, “Hand Gesture Recognition Using EMG-IMU Signals and Deep Q-Networks,” Sensors 2022, Vol. 22, Page 9613, vol. 22, no. 24, p. 9613, Dec. 2022, doi: 10.3390/S22249613.
  2. R. Nogales and M. E. Benalcázar, “Analysis of Feature Selection Methods for Hand Gestures Recognition Based on Machine Learning and the Leap Motion Controller,” SSRN Electron. J., Jun. 2022, doi: 10.2139/SSRN.4144162.
  3. R. Romero et al., “Hand Gesture and Arm Movement Recognition for Multimodal Control of a 3-DOF Helicopter,” in Lecture Notes in Networks and Systems, 2022, vol. 429 LNNS, pp. 363–377. doi: 10.1007/978-3-030-97672-9_32.
  4. V. H. Vimos, Á. L. Valdivieso Caraguay, L. I. Barona López, D. Pozo Espín, and M. E. Benalcázar, “An Interface for Audio Control Using Gesture Recognition and IMU Data,” Lect. Notes Networks Syst., vol. 407 LNNS, pp. 168–180, 2022, doi: 10.1007/978-3-030-96147-3_14.

2021

  1. M. E. Benalcázar Palacios et al., “An interactive system to improve cognitive abilities using electromyographic signals,” ACM Int. Conf. Proceeding Ser., pp. 84–90, Nov. 2021, doi: 10.1145/3505711.3505723.
  2. P. Marcillo, L. I. Barona López, A. Leonardo, V. Caraguay, and M. Hernández-´ Alvarez, “A Review of Learning-Based Traffic Accident Prediction Models and Their Opportunities to Improve Information Security,” Inf. Technol. Syst. (ICITS 2021), pp. 386–395, 2021, doi: 10.1007/978-3-030-68285-9_37.
  3. M. E. Benalcázar, L. Barona, Á. L. Valdivieso, V. H. Vimos, D. Velastegui, and C. J. Santacruz, “Educational Impact on Ecuadorian University Students Due to the COVID-19 Context,” Educ. Sci. 2022, Vol. 12, Page 17, vol. 12, no. 1, p. 17, Dec. 2021, doi: 10.3390/EDUCSCI12010017.
  4. R. Nogales, M. E. Benalcazar, B. Toalumbo, A. Palate, R. Martinez, and J. Vargas, “Construction of a Dataset for Static and Dynamic Hand Tracking Using a Non-invasive Environment,” Adv. Intell. Syst. Comput., vol. 1307 AISC, pp. 185–197, 2021, doi: 10.1007/978-981-33-4565-2_12/FIGURES/10.
  5. L. I. Barona-Lopez, A. L. Valdivieso-Caraguay, M. E. Benalcazar, X. Aguas, and J. A. Zea, “Feature Evaluation of EMG Signals for Hand Gesture Recognition Based on Mutual Information, Fuzzy Entropy and RES Index,” Adv. Intell. Syst. Comput., vol. 1307 AISC, pp. 101–119, 2021, doi: 10.1007/978-981-33-4565-2_7/TABLES/4.
  6. T. Borja, M. E. Benalcázar, Á. Leonardo, V. Caraguay, and L. I. Barona López, “Risk Analysis and Android Application Penetration Testing Based on OWASP 2016,” Inf. Technol. Syst. (ICITS 2021), pp. 461–478, 2021, doi: 10.1007/978-3-030-68285-9_44.
  7. R. E. Nogales and M. E. Benalcázar, “Hand gesture recognition using machine learning and infrared information: a systematic literature review,” Int. J. Mach. Learn. Cybern., vol. 12, no. 10, pp. 2859–2886, Oct. 2021, doi: 10.1007/S13042-021-01372-Y/METRICS.
  8. S. P. Vacacela and M. E. Benalcázar, “2D Semantic Segmentation of the Prostate Gland in Magnetic Resonance Images using Convolutional Neural Networks,” IFAC-PapersOnLine, vol. 54, no. 15, pp. 394–399, Jan. 2021, doi: 10.1016/J.IFACOL.2021.10.288.
  9. J. A. Ordóñez Flores et al., “A New Methodology for Pattern Recognition Applied to Hand Gestures Recognition Using EMG. Analysis of Intrapersonal and Interpersonal Variability,” ETCM 2021 - 5th Ecuador Tech. Chapters Meet., Oct. 2021, doi: 10.1109/ETCM53643.2021.9590695.
  10. J. Zea, M. E. Benalcázar, L. I. Barona López, and Á. L. Valdivieso Caraguay, “An Open-Source Data Acquisition and Manual Segmentation System for Hand Gesture Recognition based on EMG,” ETCM 2021 - 5th Ecuador Tech. Chapters Meet., Oct. 2021, doi: 10.1109/ETCM53643.2021.9590811.
  11. K. O. Chicaiza and M. E. Benalcázar, “A Brain-Computer Interface for Controlling IoT Devices using EEG Signals,” ETCM 2021 - 5th Ecuador Tech. Chapters Meet., Oct. 2021, doi: 10.1109/ETCM53643.2021.9590711.
  12. A. Chico et al., “Hand Gesture Recognition and Tracking Control for a Virtual UR5 Robot Manipulator,” ETCM 2021 - 5th Ecuador Tech. Chapters Meet., Oct. 2021, doi: 10.1109/ETCM53643.2021.9590677.
  13. J. P. Vásconez, L. I. B. López, Á. L. V. Caraguay, P. J. Cruz, R. Álvarez, and M. E. Benalcázar, “A Hand Gesture Recognition System Using EMG and Reinforcement Learning: A Q-Learning Approach,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 12894 LNCS, pp. 580–591, 2021, doi: 10.1007/978-3-030-86380-7_47/FIGURES/6.

2020

  1. V. H. Vimos, M. Benalcázar, A. F. Oña, and P. J. Cruz, “A Novel Technique for Improving the Robustness to Sensor Rotation in Hand Gesture Recognition Using sEMG,” Adv. Intell. Syst. Comput., vol. 1078, pp. 226–243, 2020, doi: 10.1007/978-3-030-33614-1_16/TABLES/2.
  2. R. Nogales and M. E. Benalcázar, “A Survey on Hand Gesture Recognition Using Machine Learning and Infrared Information,” Commun. Comput. Inf. Sci., vol. 1194 CCIS, pp. 297–311, 2020, doi: 10.1007/978-3-030-42520-3_24/FIGURES/6.
  3. G. Saggio, P. Cavallo, M. Ricci, V. Errico, J. Zea, and M. E. Benalcázar, “Sign Language Recognition Using Wearable Electronics: Implementing k-Nearest Neighbors with Dynamic Time Warping and Convolutional Neural Network Algorithms,” Sensors 2020, Vol. 20, Page 3879, vol. 20, no. 14, p. 3879, Jul. 2020, doi: 10.3390/S20143879.
  4. A. Jaramillo-Yánez, M. E. Benalcázar, and E. Mena-Maldonado, “Real-Time Hand Gesture Recognition Using Surface Electromyography and Machine Learning: A Systematic Literature Review,” Sensors 2020, Vol. 20, Page 2467, vol. 20, no. 9, p. 2467, Apr. 2020, doi: 10.3390/S20092467.
  5. M. E. Benalcázar, Á. L. V. Caraguay, and L. I. B. López, “A User-Specific Hand Gesture Recognition Model Based on Feed-Forward Neural Networks, EMGs, and Correction of Sensor Orientation,” Appl. Sci. 2020, Vol. 10, Page 8604, vol. 10, no. 23, p. 8604, Dec. 2020, doi: 10.3390/APP10238604.
  6. L. I. B. López et al., “An Energy-Based Method for Orientation Correction of EMG Bracelet Sensors in Hand Gesture Recognition Systems,” Sensors 2020, Vol. 20, Page 6327, vol. 20, no. 21, p. 6327, Nov. 2020, doi: 10.3390/S20216327.
  7. R. Nogales and M. Benalcázar, “Real-Time Hand Gesture Recognition Using KNN-DTW and Leap Motion Controller,” Commun. Comput. Inf. Sci., vol. 1307, pp. 91–103, 2020, doi: 10.1007/978-3-030-62833-8_8/FIGURES/10.
  8. A. Ona, V. Vimos, M. Benalcazar, and P. J. Cruz, “Adaptive Non-linear Control for a Virtual 3D Manipulator,” 2020 IEEE ANDESCON, ANDESCON 2020, Oct. 2020, doi: 10.1109/ANDESCON50619.2020.9272154.
  9. M. E. Benalcazar, J. Gonzalez, A. Jaramillo-Yanez, C. E. Anchundia, P. Zambrano, and M. Segura, “A Model for Real-Time Hand Gesture Recognition Using Electromyography (EMG), Covariances and Feed-Forward Artificial Neural Networks,” 2020 IEEE ANDESCON, ANDESCON 2020, Oct. 2020, doi: 10.1109/ANDESCON50619.2020.9271979.
  10. J. A. Zea and M. E. Benalcázar, “Real-Time Hand Gesture Recognition: A Long Short-Term Memory Approach with Electromyography,” Adv. Intell. Syst. Comput., vol. 1078, pp. 155–167, 2020, doi: 10.1007/978-3-030-33614-1_11/FIGURES/4.

2019

  1. P. Zambrano et al., “Technical mapping of the grooming anatomy using machine learning paradigms: An information security approach,” IEEE Access, vol. 7, pp. 142129–142146, 2019, doi: 10.1109/ACCESS.2019.2942805.
  2. R. Nogales and M. Benalcazar, “Real-Time Hand Gesture Recognition Using the Leap Motion Controller and Machine Learning,” 2019 IEEE Lat. Am. Conf. Comput. Intell. LA-CCI 2019, Nov. 2019, doi: 10.1109/LA-CCI47412.2019.9037037.
  3. A. Jaramillo-Yanez, L. Unapanta, and M. E. Benalcazar, “Short-Term Hand Gesture Recognition using Electromyography in the Transient State, Support Vector Machines, and Discrete Wavelet Transform,” 2019 IEEE Lat. Am. Conf. Comput. Intell. LA-CCI 2019, Nov. 2019, doi: 10.1109/LA-CCI47412.2019.9036757.
  4. E. A. Chung and M. E. Benalcázar, “Real-time hand gesture recognition model using deep learning techniques and EMG signals,” Eur. Signal Process. Conf., vol. 2019-Septe, Sep. 2019, doi: 10.23919/EUSIPCO.2019.8903136.
  5. N. R. Jhon, Q.-E. Ambato -Ecuador, B. Marco, and Q. -Ecuador, “Reconocimiento de Gestos de la Mano en Tiempo Real Usando Leap Motion Controller y Machine Learning,” Conf. Proc., vol. 3, no. 1, pp. 823–835, Sep. 2019, Accessed: Apr. 15, 2024. [Online]. Available: https://investigacion.utmachala.edu.ec/proceedings/index.php/utmach/article/view/420.
  6. M. E. Benalcázar, “Machine learning for computer vision: A review of theory and algorithms,” RISTI - Rev. Iber. Sist. e Tecnol. Inf., vol. 2019, no. 19, pp. 608–618, 2019, [Online]. Available: https://www.proquest.com/openview/ca355d43bc1ac0d2de7e41da8d0de38e/1?pq-origsite=gscholar&cbl=1006393.

2018

  1. M. E. Benalcázar, C. E. Anchundia, J. A. Zea, P. Zambrano, A. G. Jaramillo, and M. Segura, “Real-time hand gesture recognition based on artificial feed-forward neural networks and EMG,” Eur. Signal Process. Conf., vol. 2018-September, pp. 1492–1496, Nov. 2018, doi: 10.23919/EUSIPCO.2018.8553126.
  2. C. Motoche and M. E. Benalcázar, “Real-Time Hand Gesture Recognition Based on Electromyographic Signals and Artificial Neural Networks,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 11139 LNCS, pp. 352–361, 2018, doi: 10.1007/978-3-030-01418-6_35.
  3. M. A. León et al., “Virtual Rehabilitation System for Fine Motor Skills Using a Functional Hand Orthosis,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 10851 LNCS, pp. 78–94, 2018, doi: 10.1007/978-3-319-95282-6_6.
  4. L. A. Dalton, M. E. Benalcazar, and E. R. Dougherty, “Optimal clustering under uncertainty,” PLoS One, vol. 13, no. 10, p. e0204627, Oct. 2018, doi: 10.1371/JOURNAL.PONE.0204627.
  5. F. E. Ramirez, M. Segura-Morales, and M. Benalcazar, “Design of a Software Architecture and Practical Applications to Exploit the Capabilities of a Human Arm Gesture Recognition System,” 2018 IEEE 3rd Ecuador Tech. Chapters Meet. ETCM 2018, Dec. 2018, doi: 10.1109/ETCM.2018.8580267.

ADDRESS

  • Ladrón de Guevara E11-253, Quito – Ecuador
    • “José Rubén Orellana” polytechnic campus
    Faculty of Systems Engineering
    Fourth floor

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