Recent Publications

M. Portaz & A. Corbi & A. Casas-Ortiz & O.C. Santos (2024), «Exploring raw data transformations on inertial sensor data to model user expertise when learning psychomotor skills», in the User Modeling and User-Adapted Interaction. Accepted.

O. C. Santos & M. Portaz & A. Casas-Ortiz & J. Echeverria & L. F. Pérez-Villegas (2023), «Designing, Building and Evaluating Intelligent Psychomotor AIED Systems (IPAIEDS@AIED2023)«, in the International Conference on Artificial Intelligence in Education AIED 2023, Tokyo, Japan, July 2023, Pages 91–96

M. Portaz & A. Manjarrés & O. C. Santos (2023), «Towards Human-Centric Psychomotor Recommender Systems«, in UMAP ’23 Adjunct: Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, Limassol, Cyprus, June 2023, Pages 337–342

A. Casas-Ortiz, J. Echeverria, and O.C. Santos (2023), Chapter 18: Intelligent systems for psychomotor learning: a systematic review and two cases of study. Handbook of Artificial Intelligence in Education; du Boulay, B., Mitrovic, A., Yacef, K., Eds. Edward Edgar Publishing: Northampton, MA, USA, Pages 390–421.

M. Portaz & O. C. Santos (2022), «Towards Personalised Learning of Psychomotor Skills with Data Mining«, in Proceedings of the 15th International Conference on Educational Data Mining. Durham, United Kingdom, July 2022

J. Echeverria & O. C. Santos (2021), “Toward modeling psychomotor performance in Karate combats using computer vision pose estimation”, in Sensors (Basel), vol. 21, núm. 24, p. 8378.

A. Casas-Ortiz & O. C. Santos (2021), “KSAS: A Mobile App with Neural Networks to Guide the Learning of Motor Skills”, in Actas de la XIX Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 20/21), pp. 997–1000.

J. Echeverria & O. C. Santos (2021), “KUMITRON: Learning in Pairs Karate related skills with Artificial Intelligence support”, in 22nd International Conference on Artificial Intelligence in Education (AIED 2021).

A. Casas-Ortiz & O. C. Santos (2021), “KSAS: An AI Application to learn Martial Arts Movements in on-line Settings”, Interactive Events at AIED21 (Artificial Intelligence in Education), pp. 1–4.

J. Echeverria & O. C. Santos (2021), “KUMITRON: A Multimodal Psychomotor Intelligent Learning System to Provide Personalized Support when Training Karate Combats”, in 1st International Workshop on Multimodal Artificial Intelligence in Education, MAIED 2021, pp. 71–82.

J. Echeverria & O. C. Santos (2021), “KUMITRON: Artificial intelligence system to monitor karate fights that synchronize aerial images with physiological and inertial signals”, en 26th International Conference on Intelligent User Interfaces.

J. Echeverria & O. C. Santos (2021), “Punch Anticipation in a Karate Combat with Computer Vision”, en Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization.

M. A. Ronda-Carracao, O. C. Santos, G. Fernandez-Nieto, & R. Martinez-Maldonado (2021), “Towards Exploring Stress Reactions in Teamwork using Multimodal Physiological Data”, 1st International Workshop on Multimodal Artificial Intelligence in Education, MAIED 2021.

O. C. Santos (2019), “Artificial intelligence in psychomotor learning: Modeling human motion from inertial sensor data”Int. J. Artif. Intell. Tools, vol. 28, núm. 04, p. 1940006.

O. C. Santos & A. Corbi (2019), “Can aikido help with the comprehension of physics? A first step towards the design of intelligent psychomotor systems for STEAM kinesthetic learning scenarios”, IEEE Access, vol. 7, pp. 176458–176469.

A. Corbi, O. C. Santos, & D. Burgos (2019), “Intelligent framework for learning physics with aikido (martial art) and registered sensors”, Sensors (Basel), vol. 19, núm. 17, p. 3681.

A. Corbí & O. C. Santos (2018), “MyShikko: Modelling knee walking in aikido practice”, en Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization.

R. Martinez-Maldonado, V. Echeverria, O. C. Santos, A. D. P. D. Santos, & K. Yacef (2018), “Physical learning analytics: A multimodal perspective”, en Proceedings of the 8th International Conference on Learning Analytics and Knowledge.

Z. Sáenz-de-Urturi & O. C. Santos (2018), “User modelling in exergames for frail older adults”, en Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization.

O. C. Santos (2017), “Towards personalized vibrotactile support for learning aikido”, in Data Driven Approaches in Digital Education, Cham: Springer International Publishing, pp. 593–597.
 
O. C. Santos & M. H. Eddy (2017), “Modeling psychomotor activity: Current approaches and open issues”, in Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization – UMAP ’17.
 
O. C. Santos (2017), “Psychomotor learning in martial arts: An opportunity for user modeling, adaptation and personalization”, in Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization – UMAP ’17.
 
R. Martinez-Maldonado, K. Yacef, A. Dias Pereira Dos Santos, S. Buckingham Shum, V. Echeverria, O. C. Santos & M. Pechenizkiy (2017), “Towards proximity tracking and sensemaking for supporting teamwork and learning”, in 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT).
 
O. C. Santos (2017), “Toward personalized vibrotactile support when learning motor skills”, in Algorithms, vol. 10, núm. 1, p. 15.
 
O. C. Santos (2016), Guest Editor of the Special Issue “Algorithms for Psycho-Motor Training and Performance Using Wearable Technologies”. in Algorithms.
 
O. C. Santos (2016), “Training the body: The potential of AIED to support personalized motor skills learning”, in International Journal of Artificial Intelligence in Education, vol. 26, núm. 2, pp. 730–755.
 
O. C. Santos (2016), “Beyond cognitive and affective issues: Designing smart learning environments for psychomotor personalized learning”, in Learning, Design, and Technology, Cham: Springer International Publishing, pp. 1–24.
 
O. C. Santos (2015), “Education still needs Artificial Intelligence to support Personalized Motor Skill Learning: Aikido as a case study”Workshop 5: Should AI stay married to Ed? 17th International Conference on Artificial Intelligence in Education (AIED 2015). CEUR, vol. 1432, paper 9.