Abstract
We address the identification of discrete-time linear parameter varying systems in the state-space form with affine parameter dependence. In previous work, some of the authors have addressed this problem and an iterative algorithm that avoids the curse of dimensionality, inherent to this class of problems, was developed for the identification of multiple input multiple output systems. Although convergence of this algorithm has been assured for white noise sequences, it has also converged for other type of scheduling signals. Never less, its application is still not generalized to every class of scheduling parameters. In this paper, the algorithm is modified in order to identify multiple input single output systems with quasi-stationary scheduling signals. In every iteration, the system is modeled as a linear time invariant system driven by an extended input composed by the measured input, the Kronecker product between this signal and the scheduling parameter and the Kronecker product between the scheduling and the state estimated at the previous iteration. The remaining unknown signals are considered as "noise". Furthermore, the system is decomposed into a "deterministic" system driven by the known inputs and a "stochastic" subsystem driven by noise. The system is identified as a high order autoregressive exogeneous model. In order to whiten the noise, the input/output data is filtered by the inverse noise transfer function and a state-space model is estimated for the "deterministic" subsystem. Then, the output simulated by this system is subtracted from the measurements to obtain the output stochastic component. Finally, the state of the system is estimated using a Kalman filter and a deconvolution technique. Then, the state becomes an entry to the system for the next iteration, after being multiplied by the scheduling parameter. The whole process is repeated until convergence. The algorithm is tested using periodic scheduling signals and compared with other approaches developed by the same authors. © 2012 IFAC.

Abstract
This paper addresses the detection and classification of low amplitude signals within the QRS complex of the signal-averaged electrocardiogram. Linear and bilinear Kalman filter models are fitted using the subspace system identification family of algorithms. If the residuals from the models are a white noise process, then anything that cannot be modeled with the state-space models will show up in the residuals as low amplitude signal + noise. Diagnostic tests and analysis on the residuals will then lead to detection and classification of abnormalities in the intra-QRS complex. The end result is a diagnostic tool to aid the physician. © 2012 IFAC.

Abstract
In this paper the Wiener-Hammerstein Benchmark is identified as a bilinear discrete system. The bilinear approximation relies on both facts that the Wiener-Hammerstein system can be described by a Volterra series which can be approximated by bilinear systems. The identification is performed with an iterative bilinear subspace identification algorithm previously proposed by the authors. In order to increase accuracy, polynomial static nonlinearities were added to the bilinear model input. These Hammerstein type bilinear models are then identified using the same iterative subspace identification algorithm.

Abstract
Introduction: Current scientific knowledge reinforces that successful reorganization of surviving nervous tissue supports cognitive and motor recovery after stroke. The development of new neurorehabilitation tools to modulate this physiologic process is needed. In this context, vibratory stimuli are a noninvasive form of proprioceptive stimulation of the nervous system and are freely available and easy to use at a low cost. Objectives: To access the feasibility and tolerability of targeted vibratory stimuli delivered through a wearable device in an early post-stroke setting. Patients and methods: Five stroke patients were recruited from a stroke unit setting having a first ever medial cerebral artery ischemic stroke with motor deficit. The stimulation device developed delivered external vibratory stimuli to major joints at preprogrammed arrays of intensity, duration and interval of actuation. The tolerability test was set for five-hour duration and during that period data on vital parameters, cognitive, motor and sensitive performance as well as anxiety scores were recorded. Results: The device remained in place throughout and none of the patients or relatives asked to interrupt the tolerability test. There were no major complications during the trial or the ensuing days. Attention to the affected side during stimulation was increased in four patients, and two were reported as clearly more awake during the test. Discussion: This is the first tolerability test focused on the use of targeted vibratory stimulus as a neurorehabilitation tool in stroke patients. There were no hazards to report and most interestingly the majority of patients showed increased awareness to the affected side of the body. These findings will be further analyzed under functional MRI control and on long-term ambulatory use trials.

Abstract
Alternative splicing is the mechanism by which different combinations of exons in the pre-mRNA give rise to distinct mature mRNAs. This process is mediated by splicing factors that bind the pre-mRNA and affect the recognition of its splicing signals. Saccharomyces species lack many of the regulatory factors present in metazoans. Accordingly, it is generally assumed that the amount of alternative splicing is limited. However, there is recent compelling evidence that yeast have functional alternative splicing, mainly in response to environmental conditions. We have previously shown that sequence and structure properties of the pre-mRNA could explain the selection of 3' splice sites (ss) in Saccharomyces cerevisiae. In this work, we extend our previous observations to build a computational classifier that explains most of the annotated 3'ss in the CDS and 5' UTR of this organism. Moreover, we show that the same rules can explain the selection of alternative 3'ss. Experimental validation of a number of predicted alternative 3'ss shows that their usage is low compared to annotated 3'ss. The majority of these alternative 3'ss introduce premature termination codons (PTCs), suggesting a role in expression regulation. Furthermore, a genome-wide analysis of the effect of temperature, followed by experimental validation, yields only a small number of changes, indicating that this type of regulation is not widespread. Our results are consistent with the presence of alternative 3'ss selection in yeast mediated by the pre-mRNA structure, which can be responsive to external cues, like temperature, and is possibly related to the control of gene expression.

Abstract
In spite of the growing interest verified in the field of technology-based interventions for Stroke rehabilitation, there is still no global solution that is both successful and suitable for a widespread use [1,2]. In this article, we present a novel tele-rehabilitation tool designed to be used for ambulatory patients, and developed towards the motor recovery of the patient's upper-limb. The SWORD system combines a movement quantification system that analyzes the quality of the motor task performed with a biofeedback console. The proposed structure defines the SWORD system as a complete tele-rehabilitation framework that enables a direct connection between clinical and ambulatory settings. Currently a randomized clinical trial is being designed in order to assess the effectiveness of the SWORD tele-rehabilitation system.