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.

Current blood pressure (BP) estimation methods have not achieved an accurate and adaptable approach for ambulatory diagnosis and monitoring applications of populations at risk of cardiovascular disease, generally due to a limited sample size. This paper introduces an algorithm for BP estimation solely reliant on photoplethysmography (PPG) signals and demographic features. It automatically obtains signal features and employs the Markov Blanket (MB) feature selection to discern informative and transmissible features, achieving a robust space adaptable to the population shift. This approach was validated with the Aurora-BP database, compromising ambulatory wearable cuffless BP measurements for over 500 individuals. After evaluating several machine-learning regression methods, Gradient Boosting emerged as the most effective. According to the MB feature selection, temporal, frequency, and demographic features ranked highest in importance, while statistical ones were deemed non-significant. A comparative assessment of a generic model (trained on unclassified BP data) and specialized models (tailored to each distinct BP population), demonstrated a consistent superiority of our proposed MB feature space with a mean absolute error of [Formula: see text] for systolic BP and [Formula: see text] for diastolic BP on the whole dataset. Moreover, we present a first comparison of in-clinic vs. ambulatory models, with performance significantly lower for the latter with a drop of [Formula: see text] in systolic ( ) and [Formula: see text] for diastolic ( ) estimation errors. This work contributes to the resilient understanding of BP estimation algorithms from PPG signals, providing causal features in the signal and quantifying the disparities between ambulatory and in-clinic measurements.

Efficient and safe multi-agent swarm coordination in environments where humans operate, such as warehouses, assistive living rooms, or automated hospitals, is crucial for adopting automation. In this paper, we augment the obstacle avoidance algorithm based on dynamical system modulation for a swarm of heterogeneous holonomic mobile agents. A smooth prioritization is proposed to change the reactivity of the swarm towards the specific agents. Further, a soft decoupling of the initial agent's kinematics is used to design an independent rotation control to ensure the agent reaches the desired position and orientation simultaneously. This decoupling allowed the introduction of a novel heuristic, the virtual drag. It minimizes the disturbance influence an agent has when moving through its surrounding. Additionally, the safety module adapts the velocity commands from the dynamical system modulation to avoid colliding trajectories between agents. The evaluation was performed in simulated assisted living and hospital environments. The prioritization successfully increased the minimum distance relative to a moving agent. The safety module is observed to create collision-free dynamics where alternative methods fail. Additionally, the repulsive nature of the safety module augments the convergence rate, thus making the proposed method better applicable to dense real-world scenarios.

Large efforts have focused on ensuring that the controllers for mobile service robots follow proxemics and other social rules to ensure both safe and socially acceptable distance to pedestrians. Nonetheless, involuntary contact may be unavoidable when the robot travels in crowded areas or when encountering adversarial pedestrians. Freezing the robot in response to contact might be detrimental to bystanders' safety and prevents it from achieving its task. Unavoidable contacts must hence be controlled to ensure the safe and smooth travelling of robots in pedestrian alleys. We present a force-limited and obstacle avoidance controller integrated into a time-invariant dynamical system (DS) in a closed-loop force controller that let the robot react instantaneously to contact or to the sudden appearance of pedestrians. Mitigating the risk of collision is done by modulating the velocity commands upon detecting a contact and by absorbing part of the contact force through active compliant control when the robot bumps inad-vertently against a pedestrian. We evaluated our method with a personal mobility robot -Qolo- showing contact mitigation with passive and active compliance. We showed the robot able to overcome an adversarial pedestrian within 9 N of the set limit contact force for speeds under 1 m/s. Moreover, we evaluated integrated obstacle avoidance proving the ability to advance without Incurring any other collision.

In order to facilitate and assist the indoor mobility of people with special needs, the classically static objects in the environment, such as furniture, can be rendered mobile. The need for efficient and safe autonomous coordination of a mobile furniture swarm arises. We present a closed-form approach for mobile furniture obstacle avoidance and navigation within an indoor environment. The approach shows that each mobile furniture agent, defined by a polygonal surface, does not collide with any static or mobile obstacle (e.g., a person is moving around). All controllable mobile furniture converges towards a defined goal position and orientation. We showcase the application of this algorithm in simulation on mobile furniture for smart environments. Results demonstrate that the proposed method can coordinate a swarm of mobile furniture to get out of the way of a mobile agent representing a person with limited mobility passing through the room while avoiding obstacles and converging towards a predefined target pose.

Autonomous navigation in highly populated areas remains a challenging task for robots because of the difficulty in guaranteeing safe interactions with pedestrians in unstructured situations. In this work, we present a crowd navigation control framework that delivers continuous obstacle avoidance and post-contact control evaluated on an autonomous personal mobility vehicle. We propose evaluation metrics for accounting efficiency, controller response and crowd interactions in natural crowds. We report the results of over 110 trials in different crowd types: sparse, flows, and mixed traffic, with low- (< 0.15 ppsm), mid- (< 0.65 ppsm), and high- (< 1 ppsm) pedestrian densities. We present comparative results between two low-level obstacle avoidance methods and a baseline of shared control. Results show a 10% drop in relative time to goal on the highest density tests, and no other efficiency metric decrease. Moreover, autonomous navigation showed to be comparable to shared-control navigation with a lower relative jerk and significantly higher fluency in commands indicating high compatibility with the crowd. We conclude that the reactive controller fulfils a necessary task of fast and continuous adaptation to crowd navigation, and it should be coupled with high-level planners for environmental and situational awareness.

The evaluation of robot capabilities to navigate human crowds is essential to conceive new robots intended to operate in public spaces. This paper initiates the development of a benchmark tool to evaluate such capabilities; our long term vision is to provide the community with a simulation tool that generates virtual crowded environment to test robots, to establish standard scenarios and metrics to evaluate navigation techniques in terms of safety and efficiency, and thus, to install new methods to benchmarking robots’ crowd navigation capabilities. This paper presents the architecture of the simulation tools, introduces first scenarios and evaluation metrics, as well as early results to demonstrate that our solution is relevant to be used as a benchmark tool.

Since 2014, a specific standard has been dedicated for the safety certification of personal care robots, which operate in close proximity to humans. These robots serve as information providers, object transporters, personal mobility carriers, and security patrollers. In this article, we point out the shortcomings concerning EN ISO 13482:2014, which encompasses guidelines regarding the safety and design of personal care robots. In particular, we argue that the current standard is not suitable for guaranteeing people's safety when these robots operate in public spaces. Specifically, the standard lacks requirements to protect pedestrians and bystanders. The guideline implicitly assumes that private spaces, such as households and offices, present the same hazards as in public spaces. We highlight the existence of at least three properties pertaining to robots’ use in public spaces. These properties include (1) crowds, (2) social norms and proxemics rules, and (3) people's misbehaviours. We discuss how these properties impact robots’ safety. This article aims to raise stakeholders’ awareness on individuals’ safety when robots are deployed in public spaces. This could be achieved by integrating the gaps present in EN ISO 13482:2014 or by creating a new dedicated standard.

In this paper, we propose and evaluate a novel human-machine interface (HMI) for controlling a standing mobility vehicle or person carrier robot, aiming for a hands-free control through upper-body natural postures derived from gaze tracking while walking. We target users with lower-body impairment with remaining upper-body motion capabilities. The developed HMI bases on a sensing array for capturing body postures; an intent recognition algorithm for continuous mapping of body motions to robot control space; and a personalizing system for multiple body sizes and shapes. We performed two user studies: first, an analysis of the required body muscles involved in navigating with the proposed control; and second, an assessment of the HMI compared with a standard joystick through quantitative and qualitative metrics in a narrow circuit task. We concluded that the main user control contribution comes from Rectus Abdominis and Erector Spinae muscle groups at different levels. Finally, the comparative study showed that a joystick still outperforms the proposed HMI in usability perceptions and controllability metrics, however, the smoothness of user control was similar in jerk and fluency. Moreover, users' perceptions showed that hands-free control made it more anthropomorphic, animated, and even safer.

Self-tracking aims to increase awareness, decrease undesired behaviors, and ultimately lead towards a healthier lifestyle. However, inappropriate communication of self- tracking results might cause the opposite effect. Subtle self- tracking feedback is an alternative that can be provided with the aid of an artificial agent representing the self. Hence, we propose a wearable pet that reflects the user's affective states through visual and haptic feedback. By eliciting empathy and fostering helping behaviors towards it, users would indirectly help themselves. A wearable prototype was built, and three user studies performed to evaluate the appropriateness of the proposed affective representations. Visual representations using facial and body cues were clear for valence and less clear for arousal. Haptic interoceptive patterns emulating heart-rate levels matched the desired feedback urgency levels with a saturation frequency. The integrated visuo-haptic representations matched to participants own affective experience. From the results, we derived three design guidelines for future robot mirroring wearable systems: physical embodiment, interoceptive feedback, and customization.

In this paper, we propose the design of an exoskeleton with support at the knee joint and lower torso for sit-to-stand and stand-to-sit (STS) posture transitions; devised for users with spinal cord injury and other complete lower-body impairments. The STS transitions assistance is achieved through a power transfer mechanism that synchronizes knees and lumbar motion through a cable-driven pulley system. We analyze the human body dynamics in the posture transition with a rigid link model and the interaction interface with the exoskeleton through an impedance model for producing a passive system voluntarily controlled by natural motions of the upper body. Therefore, allowing the potential users to achieve STS transitions with their body residual capabilities without an external power source. Instead, transferring power from their upper-body to lower-body, herewith, controlling a passive energy storage. A prototype was constructed and evaluated with seven healthy subjects observing the proposed motion and muscle activity during the STS transitions. The results show a significant reduction in the muscle activity evaluated, at the erector spinae, gluteus maximus and rectus femoris, with reductions between 30% to 50% at the p <; 0.01 level comparing STS transitions with and without the exoskeleton support. Concluding that the STS transitions support is feasible with the passive exoskeleton envisioned for applications in upright locomotion, STS training, and rehabilitation.

This paper describes a novel passive exoskeleton for voluntary sitting-standing posture transition for children with lower limb impairment. The design of the exoskeleton is based on the utilization of the center of gravity transition through the user's upper body motion. The passive exoskeleton powered by gas springs allows the user to realize a natural-like posture transition by the user's voluntary upper body motion. We designed the posture transition model such that the user can realize the posture transition in a natural manner based on a minimum jerk criterion. The proposed design aims to permit toilet usage without transferring seating positions between the exoskeleton and toilet seat. Furthermore, the developed mechanism can be integrated with a regular wheelchair, which would allow users to have locomotion capability. We believe that the design can improve children's self-reliant social activities by supporting their voluntary posture transition and toilet use. In this paper, we describe the detailed design process of the exoskeleton and preliminary experiments to investigate its effectiveness through evaluation with a healthy participant.

In this paper, we introduce a concept of passive knee exoskeleton for cycling assistance. Considering a knee moment and a knee angle varying with a pedal crank angle, the knee extension moment can be supported by a torsion spring storing energy from knee flexion in order to release it as the knee is extended. The reduction of knee extension effort is corresponding to the torsion spring stiffness and activation range. Exoskeleton prototypes were developed for the concept validation. A crossing four-bar mechanism was chosen for the knee joint to provide kinematic compatibility covering extreme knee flexion. Constant power cycling experiment was performed on a cycling trainer by a healthy subject wearing the exoskeletons on both legs. With the torsion spring support, the surface electromyography recorded from some major leg muscles shows the decrease of knee extensor muscle activity as the leg is moving around the pedal crank top dead center. Verifying the reduction of leg muscle fatigue over repetitive contractions in multiple subjects is our future plan of study.