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Sergio Escalera, David M.J. Tax, Oriol Pujol, Petia Radeva, & Robert P.W. Duin. (2008). Subclass Problem-Dependent Design for Error-Correcting Output Codes. IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.30(6):1041–1054.
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Sergio Escalera, Oriol Pujol, & Petia Radeva. (2008). Detection of Complex Salient Regions. EURASIP Journal on Advances in Signal Processing, vol. 2008, article ID451389, 11 pages.
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O. Rodriguez-Leor, Carlo Gatta, E Fernandez-Nofrerias, Oriol Pujol, Neus Salvatella, C. Bosch, et al. (2008). Computationally Efficient Image-based IVUS Pullbacks Gating. European Heart Journal, ESC Supplement, Munich, 2008, p. 775.
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Sergio Escalera. (2013). Multi-Modal Human Behaviour Analysis from Visual Data Sources. ERCIM - ERCIM News journal, 21–22.
Abstract: The Human Pose Recovery and Behaviour Analysis group (HuPBA), University of Barcelona, is developing a line of research on multi-modal analysis of humans in visual data. The novel technology is being applied in several scenarios with high social impact, including sign language recognition, assisted technology and supported diagnosis for the elderly and people with mental/physical disabilities, fitness conditioning, and Human Computer Interaction.
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Jordi Esquirol, Cristina Palmero, Vanessa Bayo, Miquel Angel Cos, Sergio Escalera, David Sanchez, et al. (2017). Automatic RBG-depth-pressure anthropometric analysis and individualised sleep solution prescription. JMET - Journal of Medical Engineering & Technology, 486–497.
Abstract: INTRODUCTION:
Sleep surfaces must adapt to individual somatotypic features to maintain a comfortable, convenient and healthy sleep, preventing diseases and injuries. Individually determining the most adequate rest surface can often be a complex and subjective question.
OBJECTIVES:
To design and validate an automatic multimodal somatotype determination model to automatically recommend an individually designed mattress-topper-pillow combination.
METHODS:
Design and validation of an automated prescription model for an individualised sleep system is performed through a single-image 2 D-3 D analysis and body pressure distribution, to objectively determine optimal individual sleep surfaces combining five different mattress densities, three different toppers and three cervical pillows.
RESULTS:
A final study (n = 151) and re-analysis (n = 117) defined and validated the model, showing high correlations between calculated and real data (>85% in height and body circumferences, 89.9% in weight, 80.4% in body mass index and more than 70% in morphotype categorisation).
CONCLUSIONS:
Somatotype determination model can accurately prescribe an individualised sleep solution. This can be useful for healthy people and for health centres that need to adapt sleep surfaces to people with special needs. Next steps will increase model's accuracy and analise, if this prescribed individualised sleep solution can improve sleep quantity and quality; additionally, future studies will adapt the model to mattresses with technological improvements, tailor-made production and will define interfaces for people with special needs.
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