by Keyword: Cognition

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Moulin-Frier, C., Fischer, T., Petit, M., Pointeau, G., Puigbo, J., Pattacini, U., Low, S. C., Camilleri, D., Nguyen, P., Hoffmann, M., Chang, H. J., Zambelli, M., Mealier, A., Damianou, A., Metta, G., Prescott, T. J., Demiris, Y., Dominey, P. F., Verschure, P. F. M. J., (2018). DAC-h3: A proactive robot cognitive architecture to acquire and express knowledge about the world and the self IEEE Transactions on Cognitive and Developmental Systems in press

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users.

Keywords: Autobiographical Memory., Biology, Cognition, Cognitive Robotics, Computer architecture, Distributed Adaptive Control, Grounding, Human-Robot Interaction, Humanoid robots, Robot sensing systems, Symbol Grounding

Fonollosa, Jordi, Solórzano, Ana, Marco, Santiago, (2018). Chemical sensor systems and associated algorithms for fire detection: A review Sensors 18, (2), 553

Indoor fire detection using gas chemical sensing has been a subject of investigation since the early nineties. This approach leverages the fact that, for certain types of fire, chemical volatiles appear before smoke particles do. Hence, systems based on chemical sensing can provide faster fire alarm responses than conventional smoke-based fire detectors. Moreover, since it is known that most casualties in fires are produced from toxic emissions rather than actual burns, gas-based fire detection could provide an additional level of safety to building occupants. In this line, since the 2000s, electrochemical cells for carbon monoxide sensing have been incorporated into fire detectors. Even systems relying exclusively on gas sensors have been explored as fire detectors. However, gas sensors respond to a large variety of volatiles beyond combustion products. As a result, chemical-based fire detectors require multivariate data processing techniques to ensure high sensitivity to fires and false alarm immunity. In this paper, we the survey toxic emissions produced in fires and defined standards for fire detection systems. We also review the state of the art of chemical sensor systems for fire detection and the associated signal and data processing algorithms. We also examine the experimental protocols used for the validation of the different approaches, as the complexity of the test measurements also impacts on reported sensitivity and specificity measures. All in all, further research and extensive test under different fire and nuisance scenarios are still required before gas-based fire detectors penetrate largely into the market. Nevertheless, the use of dynamic features and multivariate models that exploit sensor correlations seems imperative

Keywords: Fire detection, Gas sensor, Pattern recognition, Sensor fusion, Machine learning, Toxicants, Carbon monoxide, Hydrogen cyanide, Standard test fires, Transducers, Smoke

Grice, L. F., Gauthier, M. E. A., Roper, K. E., Fernàndez-Busquets, X., Degnan, S. M., Degnan, B. M., (2017). Origin and evolution of the sponge aggregation factor gene family Molecular Biology and Evolution 34, (5), 1083-1099

Although discriminating self from nonself is a cardinal animal trait, metazoan allorecognition genes do not appear to be homologous. Here, we characterize the Aggregation Factor (AF) gene family, which encodes putative allorecognition factors in the demosponge Amphimedon queenslandica, and trace its evolution across 24 sponge (Porifera) species. The AF locus in Amphimedon is comprised of a cluster of five similar genes that encode Calx-beta and Von Willebrand domains and a newly defined Wreath domain, and are highly polymorphic. Further AF variance appears to be generated through individualistic patterns of RNA editing. The AF gene family varies between poriferans, with protein sequences and domains diagnostic of the AF family being present in Amphimedon and other demosponges, but absent from other sponge classes. Within the demosponges, AFs vary widely with no two species having the same AF repertoire or domain organization. The evolution of AFs suggests that their diversification occurs via high allelism, and the continual and rapid gain, loss and shuffling of domains over evolutionary time. Given the marked differences in metazoan allorecognition genes, we propose the rapid evolution of AFs in sponges provides a model for understanding the extensive diversification of self-nonself recognition systems in the animal kingdom.

Keywords: Aggregation factor, Allorecognition, Intron phase, Polymorphism, Porifera, RNA editing

Pacheco, D., Sánchez-Fibla, M., Duff, A., Verschure, P. F. M. J., (2017). A spatial-context effect in recognition memory Frontiers in Behavioral Neuroscience 11, Article 143

We designed a novel experiment to investigate the modulation of human recognition memory by environmental context. Human participants were asked to navigate through a four-arm Virtual Reality (VR) maze in order to find and memorize discrete items presented at specific locations in the environment. They were later on tested on their ability to recognize items as previously presented or new. By manipulating the spatial position of half of the studied items during the testing phase of our experiment, we could assess differences in performance related to the congruency of environmental information at encoding and retrieval. Our results revealed that spatial context had a significant effect on the quality of memory. In particular, we found that recognition performance was significantly better in trials in which contextual information was congruent as opposed to those in which it was different. Our results are in line with previous studies that have reported spatial-context effects in recognition memory, further characterizing their magnitude under ecologically valid experimental conditions.

Keywords: Context effects, Recognition memory, Spatial behavior, Spatial memory and navigation, Virtual reality

Moulin-Frier, C., Puigbò, J.-Y., Arsiwalla, Xerxes D., Martì Sanchez-Fibla, M., Verschure, Paul F. M. J., (2017). Embodied artificial intelligence through distributed adaptive control: An integrated framework 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL-Epirob 2017) , IEEE (Lisbon, Portugal) , 1-8

In this paper, we argue that the future of Artificial Intelligence research resides in two keywords: integration and embodiment. We support this claim by analyzing the recent advances of the field. Regarding integration, we note that the most impactful recent contributions have been made possible through the integration of recent Machine Learning methods (based in particular on Deep Learning and Recurrent Neural Networks) with more traditional ones (e.g. Monte-Carlo tree search, goal babbling exploration or addressable memory systems). Regarding embodiment, we note that the traditional benchmark tasks (e.g. visual classification or board games) are becoming obsolete as state-of-the-art learning algorithms approach or even surpass human performance in most of them, having recently encouraged the development of first-person 3D game platforms embedding realistic physics. Building upon this analysis, we first propose an embodied cognitive architecture integrating heterogenous sub-fields of Artificial Intelligence into a unified framework. We demonstrate the utility of our approach by showing how major contributions of the field can be expressed within the proposed framework. We then claim that benchmarking environments need to reproduce ecologically-valid conditions for bootstrapping the acquisition of increasingly complex cognitive skills through the concept of a cognitive arms race between embodied agents.

Keywords: Cognitive Architectures, Embodied Artificial Intelligence, Evolutionary Arms Race, Unified Theories of Cognition

Mur, O., Frigola, M., Casals, A., (2015). Modelling daily actions through hand-based spatio-temporal features ICAR 2015 International Conference on Advanced Robotics , IEEE (Istanbul, Turkey) , 478-483

In this paper, we propose a new approach to domestic action recognition based on a set of features which describe the relation between poses and movements of both hands. These features represent a set of basic actions in a kitchen in terms of the mimics of the hand movements, without needing information of the objects present in the scene. They address specifically the intra-class dissimilarity problem, which occurs when the same action is performed in different ways. The goal is to create a generic methodology that enables a robotic assistant system to recognize actions related to daily life activities and then, be endowed with a proactive behavior. The proposed system uses depth and color data acquired from a Kinect-style sensor and a hand tracking system. We analyze the relevance of the proposed hand-based features using a state-space search approach. Finally, we show the effectiveness of our action recognition approach using our own dataset.

Keywords: Histograms, Joints, Robot sensing systems, Thumb, Tracking, Human activity recognition, Disable and elderly assistance

Vinagre, M., Aranda, J., Casals, A., Aranda, J., Casals, A., (2015). A new relational geometric feature for human action recognition Lecture Notes in Electrical Engineering (ed. Ferrier, J.L., Gusikhin, O., Madani, K., Sasiadek, J.), Springer (Lausanne, Switzerland) 325, 263-278

Pose-based features have demonstrated to outperform low-levelappearance features in human action recognition. New RGB-D cameras provide locations of human joints with which geometric correspondences can be easily calculated. In this article, a new geometric correspondence between joints called Trisarea feature is presented. It is defined as the area of the triangle formed by three joints. Relevant triangles describing human pose are identified and it is shown how the variation over time of the selected Trisarea features constitutes a descriptor of human action. Experimental results show a comparison with other methods and demonstrate how this Trisarea-based representation can be applied to human action recognition.

Keywords: Action descriptor, Action recognition, Pose-based feature

Marco, Santiago, (2014). The need for external validation in machine olfaction: emphasis on health-related applications Analytical and Bioanalytical Chemistry Springer Berlin Heidelberg 406, (16), 3941-3956

Over the last two decades, electronic nose research has produced thousands of research works. Many of them were describing the ability of the e-nose technology to solve diverse applications in domains ranging from food technology to safety, security, or health. It is, in fact, in the biomedical field where e-nose technology is finding a research niche in the last years. Although few success stories exist, most described applications never found the road to industrial or clinical exploitation. Most described methodologies were not reliable and were plagued by numerous problems that prevented practical application beyond the lab. This work emphasizes the need of external validation in machine olfaction. I describe some statistical and methodological pitfalls of the e-nose practice and I give some best practice recommendations for researchers in the field.

Keywords: Chemical sensor arrays, Pattern recognition, Chemometrics, Electronic noses, Robustness, Signal and data processing

Urra, O., Casals, A., Jané, R., (2014). Evaluating spatial characteristics of upper-limb movements from EMG signals IFMBE Proceedings XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013 (ed. Roa Romero, Laura M.), Springer International Publishing (London, UK) 41, 1795-1798

Stroke is a major cause of disability, usually causing hemiplegic damage on the motor abilities of the patient. Stroke rehabilitation seeks restoring normal motion on the affected limb. However, normality’ of movements is usually assessed by clinical and functional tests, without considering how the motor system responds to therapy. We hypothesized that electromyographic (EMG) recordings could provide useful information for evaluating the outcome of rehabilitation from a neuromuscular perspective. Four healthy subjects were asked to perform 14 different functional movements simulating the action of reaching over a table. Each movement was defined according to the starting and target positions that the subject had to connect using linear trajectories. Bipolar recordings of EMG signals were taken from biceps and triceps muscles, and spectral and temporal characteristics were extracted for each movement. Using pattern recognition techniques we found that only two EMG channels were sufficient to accurately determine the spatial characteristics of motor activity: movement direction, length and execution zone. Our results suggest that muscles may fire in a patterned way depending on the specific characteristics of the movement and that EMG signals may codify such detailed information. These findings may be of great value to quantitatively assess post-stroke rehabilitation and to compare the neuromuscular activity of the affected and unaffected limbs, from a physiological perspective. Furthermore, disturbed movements could be characterized in terms of the muscle function to identify, which is the spatial characteristic that fails, e.g. movement direction, and guide personalized rehabilitation to enhance the training of such characteristic.

Keywords: EMG, Movement spatial characteristics, Pattern recognition, Stroke rehabilitation, Upper-limb

Vinagre, M., Aranda, J., Casals, A., (2014). An interactive robotic system for human assistance in domestic environments Computers Helping People with Special Needs (ed. Miesenberger, K., Fels, D., Archambault, D., Pe, Zagler), Springer International Publishing 8548, 152-155

This work introduces an interactive robotic system for assistance, conceived to tackle some of the challenges that domestic environments impose. The system is organized into a network of heterogeneous components that share both physical and logical functions to perform complex tasks. It consists of several robots for object manipulation, an advanced vision system that supplies in-formation about objects in the scene and human activity, and a spatial augmented reality interface that constitutes a comfortable means for interacting with the system. A first analysis based on users' experiences confirms the importance of having a friendly user interface. The inclusion of context awareness from visual perception enriches this interface allowing the robotic system to become a flexible and proactive assistant.

Keywords: Accessibility, Activity Recognition, Ambient Intelligence, Human-Robot Interaction, Robot Assistance, Augmented reality, Complex networks, Computer vision, User interfaces, Accessibility, Activity recognition, Ambient intelligence, Domestic environments, Heterogeneous component, Interactive robotics, Robot assistance, Spatial augmented realities, Human assistance, Robotics

Penon, O., Novo, S., Duran, S., Ibanez, E., Nogues, C., Samitier, J., Duch, M., Plaza, J. A., Perez-Garcia, L., (2012). Efficient biofunctionalization of polysilicon barcodes for adhesion to the zona pellucida of mouse embryos Bioconjugate Chemistry 23, (12), 2392-2402

Cell tracking is an emergent area in nano-biotechnology, promising the study of individual cells or the identification of populations of cultured cells. In our approach, microtools designed for extracellular tagging are prepared, because using biofunctionalized polysilicon barcodes to tag cell membranes externally avoids the inconveniences of cell internalization. The crucial covalent biofunctionalization process determining the ultimate functionality was studied in order to find the optimum conditions to link a biomolecule to a polysilicon barcode surface using a self-assembled monolayer (SAM) as the connector. Specifically, a lectin (wheat germ agglutinin, WGA) was used because of its capacity to recognize some specific carbohydrates present on the surface of most mammalian cells. Self-assembled monolayers were prepared on polysilicon surfaces including aldehyde groups as terminal functions to study the suitability of their covalent chemical bonding to WGA. Some parameters, such as the polysilicon surface roughness or the concentration of WGA, proved to be crucial for successful biofunctionalization and bioactivity. The SAMs were characterized by contact angle measurements, time-of-flight secondary ion mass spectrometry (TOF-SIMS), laser desorption/ionization time-of-flight mass spectrometry (LDI-TOF MS), and atomic force microscopy (AFM). The biofunctionalization step was also characterized by fluorescence microscopy and, in the case of barcodes, by adhesion experiments to the zona pellucida of mouse embryos. These experiments showed high barcode retention rates after 96 h of culture as well as high embryo viability to the blastocyst stage, indicating the robustness of the biofunctionalization and, therefore, the potential of these new microtools to be used for cell tagging.

Keywords: Self-assembled monolayers, Wheat-germ-agglutinin, Protein immobilization strategies, Mass-spectrometry, Cell-surface, Petide, Binding, Identifications, Nanoparticles, Recognition

Antelis, J.M., Montesano, L., Giralt, X., Casals, A., Minguez, J., (2012). Detection of movements with attention or distraction to the motor task during robot-assisted passive movements of the upper limb Engineering in Medicine and Biology Society (EMBC) 34th Annual International Conference of the IEEE , IEEE (San Diego, USA) , 6410-6413

Robot-assisted rehabilitation therapies usually focus on physical aspects rather than on cognitive factors. However, cognitive aspects such as attention, motivation, and engagement play a critical role in motor learning and thus influence the long-term success of rehabilitation programs. This paper studies motor-related EEG activity during the execution of robot-assisted passive movements of the upper limb, while participants either: i) focused attention exclusively on the task; or ii) simultaneously performed another task. Six healthy subjects participated in the study and results showed lower desynchronization during passive movements with another task simultaneously being carried out (compared to passive movements with exclusive attention on the task). In addition, it was proved the feasibility to distinguish between the two conditions.

Keywords: Electrodes, Electroencephalography, Induction motors, Medical treatment, Robot sensing systems, Time frequency analysis, Biomechanics, Cognition, Electroencephalography, Medical robotics, Medical signal detection, Medical signal processing, Patient rehabilitation, Attention, Cognitive aspects, Desynchronization, Engagement, Motivation, Motor learning, Motor task, Motor-related EEG activity, Physical aspects, Robot-assisted passive movement detection, Robot-assisted rehabilitation therapies, Upper limb

Mir, M., (2011). Aptamers: The new biorecognition element for proteomic biosensing Biochemistry Research Updates (ed. Baginski, Simon J.), Nova Science Publishers, Inc (Hauppauge, USA) , -----

Aptamers are single stranded artificial nucleic acid ligands that can be generated against almost any kind of target, such as ions, metabolites aminoacids, drugs, toxins, proteins or whole cells. They are isolated from combinatorial libraries of synthetic nucleic acids by an iterative process of adsorption, recovery and amplification, know as SELEX (Systematic Evolution of Ligands by EXponential enrichment) process. Aptamers, the nucleic acid equivalent to antibodies, are easy to synthesise, is not required the use of animals for its synthesis, for this reason it can be developed again toxins and small molecules that do not produce immune response in animals and can be tuned for affinity in closer to assay conditions permitting recognition out of the physiological state. So, aptamers posses numerous advantages that make them preferred candidates as biorecognition elements. In view of the advantages and simple structure of aptamers, they have been used in a wide range of applications such as therapeutics, diagnosis, chromatography, environmental detection, among other.

Keywords: Aptamers, Biosensors, Protein recognition

Darwish-, N., Caballero, D., Moreno, M., Errachid, A., Samitier, J., (2010). Multi-analytic grating coupler biosensor for differential binding analysis Sensors and Actuators B: Chemical 144, (2), 413-417

In this paper, a multiple-channel extension of a dual-grating Coupler biosensor is presented as a Solution for the problem of resolving different selectivities, Usual when heterogeneous samples are analyzed. Several differently functionalized channels can perform quantitative analysis of competiting recognition events, Suppress shifts due to buffer changes and even monitorize drifts coming from the light Source. Here, the multiple-channel approach is developed and proven for a four-channel configuration, providing a resolution limit of 10(-5) Refractive index Units (RIU) and with an a potentially Unlimited scalability. Finally, a differential HSA recognition event is monitored, at both an IgG functionalized channel and at a blocked one.

Keywords: Optical grating coupler, Multi-channel biorecognition, On-chip reference

Hofer, M., Adamsmaier, S., van Zanten, T. S., Chtcheglova, L. A., Manzo, C., Duman, M., Mayer, B., Ebner, A., Moertelmaier, M., Kada, G., Garcia-Parajo, M. F., Hinterdorfer, P., Kienberger, F., (2010). Molecular recognition imaging using tuning fork-based transverse dynamic force microscopy Ultramicroscopy 110, (6), 605-611

We demonstrate simultaneous transverse dynamic force microscopy and molecular recognition imaging using tuning forks as piezoelectric sensors. Tapered aluminum-coated glass fibers were chemically functionalized with biotin and anti-lysozyme molecules and attached to one of the prongs of a 32 kHz tuning fork. The lateral oscillation amplitude of the tuning fork was used as feedback signal for topographical imaging of avidin aggregates and lysozyme molecules on mica substrate. The phase difference between the excitation and detection signals of the tuning fork provided molecular recognition between avidin/biotin or lysozyme/anti-lysozyme. Aggregates of avidin and lysozyme molecules appeared as features with heights of 1-4 nm in the topographic images, consistent with single molecule atomic force microscopy imaging. Recognition events between avidin/biotin or lysozyme/anti-lysozyme were detected in the phase image at high signal-to-noise ratio with phase shifts of 1-2 degrees. Because tapered glass fibers and shear-force microscopy based on tuning forks are commonly used for near-field scanning optical microscopy (NSOM), these results open the door to the exciting possibility of combining optical, topographic and biochemical recognition at the nanometer scale in a single measurement and in liquid conditions.

Keywords: Tuning fork, Atomic force microscopy, Shear-force microscopy, Molecular recognition, Avidin-biotin

Correa, L. S., Laciar, E., Mut, V., Giraldo, B. F., Torres, A., (2010). Multi-parameter analysis of ECG and Respiratory Flow signals to identify success of patients on weaning trials Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) -----, 6070-6073

Statistical analysis, power spectral density, and Lempel Ziv complexity, are used in a multi-parameter approach to analyze four temporal series obtained from the Electrocardiographic and Respiratory Flow signals of 126 patients on weaning trials. In which, 88 patients belong to successful group (SG), and 38 patients belong to failure group (FG), i.e. failed to maintain spontaneous breathing during trial. It was found that mean values of cardiac inter-beat and breath durations give higher values for SG than for FG; Kurtosis coefficient of the spectrum of the rapid shallow breathing index is higher for FG; also Lempel Ziv complexity mean values associated with the respiratory flow signal are bigger for FG. Patients were then classified with a pattern recognition neural network, obtaining 80% of correct classifications (81.6% for FG and 79.5% for SG).

Keywords: Electrocardiography, Medical signal processing, Neural nets, Pattern recognition, Pneumodynamics, Signal classification, Statistical analysis, ECG, Kurtosis coefficient, Lempel Ziv complexity, Breath durations, Cardiac interbeat durations, Electrocardiography, Multiparameter analysis, Pattern recognition neural network, Power spectral density, Respiratory flow signals, Signal classification, Spontaneous breathing, Statistical analysis, Weaning trials

Calvo, D., Salvador, J. P., Tort, N., Centi, F., Marco, M. P., Marco, S., (2009). Multidetection of anabolic androgenic steroids using immunoarrays and pattern recognition techniques Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 547-550

A first step towards the multidetection of anabolic androgenic steroids by Enzyme-linked immunosorbent assays (ELISA) has been performed in this study. This proposal combines an array of classical ELISA assays with different selectivities and multivariate data analysis techniques. Data has been analyzed by principal component analysis in conjunction with a k-nearest line classifier has been used. This proposal allows to detect simultaneously four different compounds in the range of concentration from 10(-1.5) to 10(3) mM with a total rate of 90.6% of correct detection.

Keywords: Immunoarray, Anabolic androgenic steroid, Multidetection, Pattern recognition, K-nearlest line

Diez, Pablo F., Laciar, Eric, Mut, Vicente, Avila, Enrique, Torres, Abel, (2008). A comparative study of the performance of different spectral estimation methods for classification of mental tasks IEEE Engineering in Medicine and Biology Society Conference Proceedings 30th Annual International Conference of the Ieee Engineering in Medicine and Biology Society (ed. IEEE), IEEE (Vancouver, Canada) 1-8, 1155-1158

In this paper we compare three different spectral estimation techniques for the classification of mental tasks. These techniques are the standard periodogram, the Welch periodogram and the Burg method, applied to electroencephalographic (EEG) signals. For each one of these methods we compute two parameters: the mean power and the root mean square (RMS), in various frequency bands. The classification of the mental tasks was conducted with a linear discriminate analysis. The Welch periodogram and the Burg method performed better than the standard periodogram. The use of the RMS allows better classification accuracy than the obtained with the power of EEG signals.

Keywords: Adult, Algorithms, Artificial Intelligence, Cognition, Electroencephalography, Female, Humans, Male, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity, Task Performance and Analysis, User-Computer Interface

Rodriguez, Segui, Bucior, I., Burger, M. M., Samitier, J., Errachid, A., Fernàndez-Busquets, X., (2007). Application of a bio-QCM to study carbohydrates self-interaction in presence of calcium Transducers '07 & Eurosensors Xxi, Digest of Technical Papers 14th International Conference on Solid-State Sensors, Actuators and Microsystems , IEEE (Lyon, France) 1-2, 1995-1998

In the past years, the quartz crystal microbalance (QCM) has been successfully applied to follow interfacial physical chemistry phenomena in a label free and real time manner. However, carbohydrate self adhesion has only been addressed partially using this technique. Carbohydrates play an important role in cell adhesion, providing a highly versatile form of attachment, suitable for biologically relevant recognition events in the initial steps of adhesion. Here, we provide a QCM study of carbohydrates' self-recognition in the presence of calcium, based on a species-specific cell recognition model provided by marine sponges. Our results show a difference in adhesion kinetics when varying either the calcium concentration (with a constant carbohydrate concentration) or the carbohydrate concentration (with constant calcium concentration).

Keywords: Biomedical materials, Calcium, Cellular biophysics, Microbalances, Porous materials, Quartz, Surface chemistry/ bio-QCM, Carbohydrates self-interaction, Quartz crystal microbalance, Interfacial physical chemistry phenomena, Carbohydrate self adhesion, Biologically relevant recognition events, Marine sponges, Adhesion kinetics, Calcium concentration, Carbohydrate concentration, Biosensors, Biomedical materials, Surface chemistry, Cellular biophysics