Blood pressure (BP) is a critical biomarker for cardiovascular health. Several proposals of surrogate measurements and methods, such as Pulse Arrival Time (PAT), aim to provide non-invasive cuffless alternatives to traditional BP monitoring. However, the reliability of PAT-based models remains uncertain due to calibration challenges and the complex nature of BP regulation. This study investigated the performance of PAT-based models using portable electrocardiograms and photoplethysmography to estimate systolic (SBP) and diastolic (DBP) BP in ambulatory settings with 307 participants from the AuroraBP dataset. The best-performing PAT-based models achieved a mean absolute error (MAE) of$\mathbf{1 4. 2 3 ~ m m H g}$for SBP and 9.67 mmHg for DBP estimation. Both models failed to meet current international standards for BP monitoring. Additionally, the baseline models outperformed the best PAT-based model for SBP (MAE:$\mathbf{1 3. 0 4 ~ m m H g}$) and achieved comparable performance to the top PAT-based model for DBP (MAE: 9.67). Despite promising results in previous studies, our findings highlight the poor performance of PAT-based models, particularly in dynamic and ambulatory conditions. These results highlight the limitation of multi-signal time-based models, which fail to generalize in complex dynamic situations. More advanced approaches that succeed in capturing the nonlinearities of BP variations and provide reliable, continuous BP monitoring in real-life settings are necessary.

This study evaluates the impact of immersive (Head-Mounted Display, HMD) and non-immersive (2D conventional monitor) visual displays on user performance in a haptic-enabled virtual reality (VR) platform. Fourteen healthy participants completed three interactive tasks—Pick and place (P&P), Canvas, and Box and Block Test (BBT)—under both display conditions. A counterbalanced design was employed to minimize order effects. Statistical analysis revealed that display type significantly influenced performance in the P&P task ($\mathbf{p}=\mathbf{0. 0 0 3}$), where users performed better with the HMD, likely due to enhanced depth perception. However, no significant differences were observed in Canvas ($\mathbf{p}=0.258$) or BBT ($\mathbf{p}=0.634$), where depth perception plays a less critical role. Despite its potential effectiveness for rehabilitation, the platform does have limitations, such as the constrained workspace of the Touch${ }^{T M}$haptic device. Future studies should involve clinical populations to evaluate its therapeutic potential. These findings underscore the influence of display modality on VR-based tasks and its implications for humancomputer interaction, particularly in rehabilitation contexts.

Robotics constitutes a multidisciplinary area, congregating knowledge from different scientific domains. The learning of robotic systems requires the acquisition of multidisciplinary scientific bases, and high integration and synthesis abilities, which is not an easy task. This paper describes the implementation of a lifelong course that aims to provide a global insight on robotics field, introducing the concepts and technologies for different domain applications, namely industrial robotics, autonomous mobile robotics and robotics applied in medicine. This is accomplished in an international framework where individual knowledge and experiences will be confronted in a multidisciplinary level and intercultural environment.

In a multirobot system (MRS) several robots can operate simultaneously on the same product. We propose the use of timed Petri nets to evaluate the efficiency of the system. The throughput and utilization of robots allows us to evaluate the benefits of the MRS. A methodology has been developed that, given a set of robots and platforms, allows what the optimum operation mode is, under different conditions, to be decided.

In a multirobot system (MRS) several robots can operate simultaneously on the same product, and allow the accomplishment of tasks that a single robot could not approach due to restrictions associated to the product and/or the robot. We propose a MRS consisting of three robots and four different working platforms, that allows the characteristics of joint operation to be maintained even if a robot is out of service. In order to make a detailed analysis of the operating characteristics of the MRS we propose to use timed Petri nets (GSPN and DSPN), than allow the efficiency of the system to be evaluated. This paper analyses the influence of the robot maintenance and failures on the throughput of an MRS, under different conditions of operative configuration, number of subtasks, degree of interference, operation mode on the product, etc.