Objective: In this article, we present the conceptual development of a robotics platform, called ALICE (Assistive Lower Limb Controlled Exoskeleton), for kinetic and kinematic gait characterization. The ALICE platform includes a robotics wearable exoskeleton and an on-board muscle driven simulator to estimate the user’s kinetic parameters. Background: Even when the kinematics patterns of the human gait are well studied and reported in the literature, there exists a considerable intra-subject variability in the kinetics of the movements. ALICE aims to be an advanced mechanical sensor that allows us to compute real-time information of both kinetic and kinematic data, opening up a new personalized rehabilitation concept. Methodology: We developed a full muscle driven simulator in an open source environment and validated it with real gait data obtained from patients diagnosed with multiple sclerosis. After that, we designed, modeled, and controlled a 6 DoF lower limb exoskeleton with inertial measurement units and a position/velocity sensor in each actuator. Significance: This novel concept aims to become a tool for improving the diagnosis of pathological gait and to design personalized robotics rehabilitation therapies. Conclusion: ALICE is the first robotics platform automatically adapted to the kinetic and kinematic gait parameters of each patient.

In recent decades, the senior adults population worldwide has increased, as well as the medical conditions related to aging, such as cognitive decline. Virtual reality (VR) games are a valuable addition to conventional cognitive rehabilitation as they increase engagement to the therapy through customization, socialization, immersion, and feedback. This review, performed according to PRISMA protocol, addresses the following questions: How VR games have been used for cognitive rehabilitation?, What cognitive domains have been addressed by VR games and in which populations have these games been used?, Which features have been considered to improve engagement in VR games for cognitive rehabilitation?, How is the difficulty adjustment of exercises carried out in VR games for cognitive rehabilitation?. We found 25 scientific works related to these questions, 92% of them treating one cognitive domain at a time, despite the fact that the related literature recognizes the value of training multiple domains simultaneously. Our review indicates that, despite the existence of serious VR games for working memory training, such as those described in Flak et al. (Front Psychol 10:807, 2019. https://doi.org/10.3389/fpsyg.2019.00807), to our knowledge, there are no applications that simultaneously address multiple cognitive domains and incorporate dynamic difficulty adjustment, which are important to ensure ecological validity of therapy and therapy adherence, respectively. In addition, we found that games themselves could be used to monitor the user’s progression. It is also important to determine the impact of multiplayer interactions in the game, test difficulty adjustment approaches that use physiological variables, and define difficulty-skill relationships aligned with the user’s preferences. This paper concludes that the main barriers to implement dynamic difficulty adjustment in VR games for cognitive rehabilitation are: (i) the absence of metrics to estimate when the game offers to the players a challenge adapted their skills, and (ii) the lack of a conceptual framework that integrates relevant theories such as state of flow, cognitive load, cognitive rehabilitation, and feedback systems.

There is much evidence pointing out eye movement alterations in several neurological diseases. To the best of our knowledge, this is the first video-oculography study describing potential alterations of eye movements in the post-COVID-19 condition. Visually guided saccades, memory-guided saccades, and antisaccades in horizontal axis were measured. In all visual tests, the stimulus was deployed with a gap condition. The duration of the test was between 5 and 7 min per participant. A group of $n=9$ patients with the post-COVID-19 condition was included in this study. Values were compared with a group ($n=9$) of healthy volunteers whom the SARS-CoV-2 virus had not infected. Features such as centripetal and centrifugal latencies, success rates in memory saccades, antisaccades, and blinks were computed. We found that patients with the post-COVID-19 condition had eye movement alterations mainly in centripetal latency in visually guided saccades, the success rate in memory-guided saccade test, latency in antisaccades, and its standard deviation, which suggests the involvement of frontoparietal networks. Further work is required to understand these eye movements’ alterations and their functional consequences.

This paper presents a conceptual framework for the development of serious games aimed at cognitive rehabilitation in older adults. Following Jabareen’s methodology, a literature review was conducted to identify concepts and theories that are relevant in this field. The resulting framework comprises the use of virtual reality, integration of physical activity, incorporation of social interaction features, adaptability of difficulty levels, and customization of game content. The interconnections between these concepts and underlying cognitive theories, such as the cognitive reserve hypothesis and the scaffolding theory of aging and cognition, are highlighted. As we are in the early stages of our research, our goal is to introduce and test novel interpretations of current knowledge within this conceptual framework. Additionally, the practical implications of the conceptual framework are discussed, including its strengths and limitations, as well as its relevance for future research and clinical practice in the field of cognitive rehabilitation. It is hoped that this framework will provide a guide for the design and implementation of effective interventions to improve cognitive health and well-being in the older adult population.

Eye-movement analysis has grown exponentially in recent decades. The reason is that abnormalities in oculomotor movements are usually symptoms of injuries in the nervous system. This paper presents a novel regulated solution named OSCANN. OSCANN aims at providing an innovative tool for the control, management and visualization of oculomotor neurological examinations. This solution utilizes an eye-tracker sensor based on video electro-oculography (VOG) technology to capture eye movements and store them in video files. Such a sensor can store images at a rate of 100 frames per second. A characterization study was performed using twenty-two volunteers (13 male, 9 female, ages 22–45 years, mean 29.3 years, SD = 6.7) to assess the accuracy and precision specifications of OSCANN during oculomotor movement analysis. The accuracy was evaluated based on the offset, whereas precision was estimated with Root Means Square (RMS). Such a study reported values lower than 0.4 ${}^{\circ }$ and 0.03 ${}^{\circ }$ of accuracy and precision, respectively. These results suggest that OSCANN can be considered as a powerful tool to measure oculomotor movement alterations involved in some neurological disease progression.

The origin of life initiated an evolutionary continuum yielding biologically optimized systems capable of operating under extreme environmental constraints. Biomimetics, defined as the systematic abstraction and transfer of biological principles into engineering domains, has become a strategic design paradigm for addressing the multifactorial challenges of space systems. This study introduces two core contributions to formally establish the discipline of Aerospace Bionic Robotics (ABR): First, it elucidates the relevance of biologically derived functionalities such as autonomy, adaptability, and multifunctionality to enhance the efficiency of space robotic platforms operating in microgravity environments. Second, it proposed the BEAM-D (Biomimetic Engineering and Aerospace Mechatronics Design), a standard for the development of Aerospace Bionic Robotics. By integrating biological abstraction levels (morphological, functional, and behavioral) with engineering protocols including ISO, VDI, and NASA’s TRL, BEAM-D enables a structured design pathway encompassing subsystem specification, cyber–physical integration, in situ testing, and full-scale mission deployment. It is implemented through a modular BEAM-DX framework and reinforced by iterative BIOX design steps. This study thus establishes formalized bio-inspired design tools for advanced orbital and planetary robotic systems capable of sustained autonomous operations in deep space exploration scenarios.