Scanpath analysis provides a powerful window into visual behavior by jointly capturing the spatial organization and temporal dynamics of gaze. By linking perception, cognition, and oculomotor control, scanpaths offer rich insights into how individuals explore visual scenes and accomplish task goals. Despite decades of research, however, the field remains methodologically fragmented, with a wide diversity of representations and comparison metrics that complicate interpretation and methodological choice. This article reviews computational approaches for the characterization and comparison of scanpaths, with an explicit focus on their underlying assumptions, interpretability, and practical implications. We first survey representations and metrics designed to describe individual scanpaths, ranging from geometric descriptors and spatial density representations to more advanced approaches such as attention maps, recurrence quantification analysis, and symbolic string encodings that capture temporal regularities and structural patterns. We then review methods for comparing scanpaths across observers, stimuli, or tasks, including point-mapping metrics, elastic alignment techniques, string-edit distances, saliency-based measures, and hybrid approaches integrating spatial and temporal information. Across these methods, we highlight their respective strengths, limitations, and sensitivities to design choices such as discretization, spatial resolution, and temporal weighting. Rather than promoting a single optimal metric, this review emphasizes scanpath analysis as a family of complementary tools whose relevance depends on the research question and experimental context. Overall, this work aims to provide a unified conceptual framework to guide methodological selection, foster reproducibility, and support the meaningful interpretation of gaze dynamics across disciplines.

IntroductionFrailty reflects age-related decline across multiple physiological systems, reducing resilience and increasing risks of falls, hospitalization, disability, and mortality. Scalable approaches are needed to identify pre-frailty earlier in community-dwelling older adults and enable timely prevention in primary care.ObjectiveTo develop and evaluate a multivariable sensor-based framework for early frailty detection using standardized gait and balance assessments in general practice.MethodsWe conducted a prospective cohort study (2021–2024) in southern Réunion Island among retired adults aged ≥65 years recruited in primary care. The protocol included: (1) baseline general practitioner (GP) assessment with expert frailty rating, Fried phenotype, and WHO ICOPE Step 1; (2) telephone assessment of mental health, self-rated health, and quality of life; (3) outpatient instrumented evaluation combining IMU-based gait analysis, force-platform posturography, grip strength, and ICOPE Step 2 measures; (4) monthly falls surveillance over 6 months; and (5) repeat instrumented gait and balance assessment at 6 months. Correlation analyses and machine-learning models examined relationships between frailty measures and the discriminative value of sensor-derived and multimodal predictors.ResultsAmong 145 participants (mean age 71 ± 5 years), 98.5% had impairment in at least one intrinsic capacity domain at baseline, most commonly vision (77.7%), locomotion (53.1%), hearing (52.5%), and psychological (27.3%). Sedentary behavior was frequent (77%). Expert frailty scores correlated with the Fried phenotype, whereas associations with self-rated health were weaker. Models based on sensor parameters alone showed limited ability to reproduce Fried-defined frailty, while multimodal models integrating clinical and questionnaire variables improved discrimination. Over 6 months, kinesiotherapy and regular physical activity were associated with improved postural control metrics (including center-of-pressure features and mediolateral sway), while changes in gait speed were modest.ConclusionAn IoT-supported platform combining quantitative gait, balance, and grip strength measures with targeted questionnaires is feasible in outpatient primary care and yields frailty estimates broadly consistent with GP assessment. However, subjective and clinical inputs remain essential to capture psychological aspects of frailty not fully reflected by sensor signals alone. These findings support scalable frailty screening and longitudinal monitoring, and warrant validation in larger samples, including deployment by trained non-medical personnel and integration into precision-prevention pathways.

Eye movement analysis provides critical insights across domains such as perception, cognition, neurological diagnostics, and human-computer interaction. However, reliable quantification of oculomotor remains challenging due to the lack of clear boundaries between fixations, saccades, and smooth pursuits, or variability across individuals and contexts. This article reviews methods for segmenting oculometry data into canonical oculomotor events, and the computational tools that can be used to characterize them. Binary segmentation employs mostly threshold-based algorithms and learning-based algorithms to distinguish fixations from saccades. Ternary segmentation additionally considers smooth pursuits using primarily threshold-based approaches and deep learning techniques. The common challenges in the practical application of segmentation algorithms are highlighted, namely, parameter sensitivity, noise, and head movement artifacts in mobile eye trackers, and emphasize the need for standardized benchmarks. The usual oculomotor metrics that can be inferred from the canonical movements are described, encompassing temporal, spatial, and kinematic features. The critical insights they provide for cognitive and clinical research in fields such as reading comprehension, neurological disorder diagnostics, and sensorimotor development, are outlined. Finally, relatively underexplored methods from signal processing, including spectral, stochastic, and topological methods, are presented. Their potential in revealing oscillatory patterns and structural complexities in gaze dynamics is detailed. Together, these approaches enhance our understanding of eye movement behavior, with significant implications for psychology, neuroscience, and human-computer interaction.

Eye-tracking research offers valuable insights into human gaze behavior by examining the neurophysiological mechanisms that govern eye movements and their dynamic interactions with external stimuli. This review explores the foundational principles of oculomotor control, emphasizing the neural subsystems responsible for gaze stabilization and orientation. Although controlled laboratory studies have significantly advanced our understanding of these mechanisms, their ecological validity remains a critical limitation. However, the emergence of mobile eye tracking technologies has enabled research in naturalistic environments, uncovering the intricate interplay between gaze behavior and inputs from the head, trunk, and sensory systems. Furthermore, rapid technological advancements have broadened the application of eye-tracking across neuroscience, psychology, and related disciplines, resulting in methodological fragmentation that complicates the integration of findings across fields. In response to these challenges, this review underscores the distinctions between head-restrained and naturalistic conditions, emphasizing the importance of bridging neurophysiological insights with experimental paradigms. By addressing these complexities, this work seeks to elucidate the diverse methodologies employed for recording eye movements, providing critical guidance to mitigate potential pitfalls in the selection and design of experimental paradigms.

OBJECTIVE:To study associations of newly proposed noninvasive central arterial wave reflection timing indices with age and reference indices of reflection magnitude, using superimposed MRI aortic flow and applanation tonometry carotid pressure waveforms. METHODS:Consecutively acquired MRI flow and tonometry pressure waveforms were superimposed in 113 volunteers [56 women, age: 43 ± 16 (19-81) years] free from overt cardiovascular disease except for hypertension, after registration and interpolation to averaged cardiac cycle duration using a custom interface to derive time to peak flow ( TQmax ) and pressure ( TPmax ). Conventional time to return of reflected pressure wave ( Ti ), augmentation index (AIx) and reflection magnitude (RM) were further measured and used as reference. RESULTS:TQmax occurred slightly earlier, whereas TPmax appeared later in the cardiac cycle with age, resulting in significant, independent age-related decrease in TQmax to Ti ( r  = -0.63, P  < 0.0001) and increase in TQmax to TPmax ( r  = 0.61, P  < 0.0001) delays. Such delays were further significantly and independently related to reference AIx ( Ti  -  TQmax : r  = -0.66, P  < 0.0001; TPmax  -  TQmax : r  = 0.78, P  < 0.0001) and RM ( Ti  -  TQmax : r  = -0.55, P  < 0.0001; TPmax  -  TQmax : r  = 0.76, P  < 0.0001). Correlations obtained with TPmax  -  TQmax were overall higher than those obtained with conventional Ti timing (age: r  = -0.52, P  < 0.0001; AIx: r  = -0.77, P  < 0.0001; RM: r  = -0.42, P  < 0.0001). CONCLUSION:Combination of noninvasive flow and pressure time domain waveforms was able to reliably capture central wave reflection timing indices as demonstrated by strong and independent associations with age and gold standard measures of reflection magnitude. Such timing, which was based on straightforward peaks detection, could be used to explore and better understand left ventricular-aortic coupling in cardiovascular conditions presenting increased reflections.

This paper introduces an innovative symbolic framework for task-related gaze classification. The proposed method encodes multivariate eye-tracking feature signals into symbolic string sequences, facilitating the computation of an interpretable and robust distance metric between recordings. Applied to the ETRA 2019 dataset, the symbolic representation enables accurate clustering of visual tasks without dependence on black-box models. Experimental results demonstrate that our approach achieves performance comparable with state-of-the-art deep learning methods.

The use of complex human-machine interfaces (HMIs) has grown rapidly over the last few decades in both industrial and personal contexts. Now more than ever, the study of mental workload (MWL) in HMI operators appears essential: when mental demand exceeds task load, cognitive overload arises, increasing the risk of work-related fatigue or accidents. In this paper, we propose a data-driven approach for the continuous estimation of the MWL of professional helicopter pilots in realistic simulated flights. Physiological and operational parameters were used to train a novel machine-learning model of MWL. Our algorithm achieves good performance (ROC AUC score 0.836 ± 0.081, the maximum F1 score 0.842 ± 0.078 and PR AUC score 0.820 ± 0.097) and shows that the operational information outperforms the physiological signals in terms of predictive power for MWL. Our results pave the way towards intelligent systems able to monitor the MWL of HMI operators in real time and question the relevancy of physiology-derived metrics for this task.

BackgroundAscending thoracic aortic aneurysm (ATAA) is a silent and threatening dilation of the ascending aorta (AscAo). Maximal aortic diameter which is currently used for ATAA patients management and surgery planning has been shown to inadequately characterize risk of dissection in a large proportion of patients. Our aim was to propose a comprehensive quantitative evaluation of aortic morphology and pressure-flow-wall associations from 4D flow MRI data in healthy aging and in patients with ATAA.MethodsWe studied 17 ATAA patients (64.7±14.3 years, 5 females) along with 17 age- and sex-matched healthy controls (59.7±13.3 years, 5 females) and 13 younger healthy subjects (33.5±11.1 years, 4 females). All subjects underwent an MRI exam including 4D flow and 3D anatomical images of the aorta. This latter dataset was used for aortic morphology measurements including AscAo maximal diameter (iDMAX) and volume, indexed to body surface area. 4D flow MRI data were used to estimate: 1) cross-sectional local AscAo spatial (∆PS) and temporal (∆PT) pressure changes as well as the distance (∆DPS) and time duration (∆TPT) between local pressure peaks, 2) AscAo maximal wall shear stress (WSSMAX) at peak systole, 3) AscAo flow vorticity amplitude (VMAX), duration (VFWHM) and eccentricity (VECC).ResultsConsistency of flow and pressure indices was demonstrated through their significant associations with AscAo iDMAX (WSSMAX: r=-0.49, p<0.001; VECC:r=-0.29, p=0.045; VFWHM:r=0.48, p<0.001; ∆DPS:r=0.37, p=0.010; ∆TPT:r=-0.52, p<0.001) and indexed volume (WSSMAX:r=-0.63, VECC:r=-0.51, VFWHM:r=0.53, ∆DPS:r=0.54, ∆TPT:r=-0.63, p<0.001 for all). Intra-AscAo cross-sectional pressure difference, ∆PS, was significantly and positively associated with both VMAX (r=0.55, p=0.002) and WSSMAX (r=0.59, p<0.001) in the 30 healthy subjects (48.3±18.0 years). Associations remained significant after adjustment for iDMAX, age and systolic blood pressure. Superimposition of ATAA patients to normal aging trends between ∆PS and WSSMAX as well as VMAX allowed identifying patients with substantially high pressure differences concomitant with AscAo dilation.ConclusionLocal variations in pressures within ascending aortic cross-sections derived from 4D flow MRI were associated with flow changes, as quantified by vorticity, and with stress exerted by blood on the aortic wall, as quantified by wall shear stress. Such flow-wall and pressure interactions might help for the identification of at-risk patients.

In a recent review, we summarized the characteristics of perceptual-motor style in humans. Style can vary from individual to individual, task to task and pathology to pathology, as sensorimotor transformations demonstrate considerable adaptability and plasticity. Although the behavioral evidence for individual styles is substantial, much remains to be done to understand the neural and mechanical substrates of inter-individual differences in sensorimotor performance. In this study, we aimed to investigate the modulation of perceptual-motor style during locomotion at height in 16 persons with no history of fear of heights or acrophobia. We used an inexpensive virtual reality (VR) video game. In this VR game, Richie’s Plank, the person progresses on a narrow plank placed between two buildings at the height of the 30th floor. Our first finding was that the static markers (head, trunk and limb configurations relative to the gravitational vertical) and some dynamic markers (jerk, root mean square, sample entropy and two-thirds power law at head, trunk and limb level) we had previously identified to define perceptual motor style during locomotion could account for fear modulation during VR play. Our second surprising result was the heterogeneity of this modulation in the 16 young, healthy individuals exposed to moving at a height. Finally, 56% of participants showed a persistent change in at least one variable of their skeletal configuration and 61% in one variable of their dynamic control during ground locomotion after exposure to height.

Background Ascending thoracic aortic aneurysm (ATAA) is a silent and threatening dilation of the ascending aorta (AscAo). Maximal aortic diameter which is currently used for ATAA patients management and surgery planning has been shown to inadequately characterize risk of dissection in a large proportion of patients. Our aim was to propose a comprehensive quantitative evaluation of aortic morphology and pressure-flow-wall associations from four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) data in healthy aging and in patients with ATAA. Methods We studied 17 ATAA patients (64.7 +/- 14.3 years, 5 females) along with 17 age- and sex-matched healthy controls (59.7 +/- 13.3 years, 5 females) and 13 younger healthy subjects (33.5 +/- 11.1 years, 4 females). All subjects underwent a CMR exam, including 4D flow and three-dimensional anatomical images of the aorta. This latter dataset was used for aortic morphology measurements, including AscAo maximal diameter (iD(MAX)) and volume, indexed to body surface area. 4D flow MRI data were used to estimate 1) cross-sectional local AscAo spatial (triangle P-S) and temporal (triangle P-T) pressure changes as well as the distance (triangle D-PS) and time duration (triangle T-PT) between local pressure peaks, 2) AscAo maximal wall shear stress (WSSMAX) at peak systole, and 3) AscAo flow vorticity amplitude (V-MAX), duration (V-FWHM), and eccentricity (V-ECC). Results Consistency of flow and pressure indices was demonstrated through their significant associations with AscAo iD(MAX) (WSSMAX:r = -0.49, p < 0.001; V-ECC:r = -0.29, p = 0.045; V-FWHM:r = 0.48, p < 0.001; triangle D-PS:r = 0.37, p = 0.010; triangle T-PT:r = -0.52, p < 0.001) and indexed volume (WSSMAX:r = -0.63, V-ECC:r = -0.51, V-FWHM:r = 0.53, triangle D-PS:r = 0.54, triangle T-PT:r = -0.63, p < 0.001 for all). Intra-AscAo cross-sectional pressure difference, triangle P-S, was significantly and positively associated with both V-MAX (r = 0.55, p = 0.002) and WSSMAX (r = 0.59, p < 0.001) in the 30 healthy subjects (48.3 +/- 18.0 years). Associations remained significant after adjustment for iD(MAX), age, and systolic blood pressure. Superimposition of ATAA patients to normal aging trends between triangle P-S and WSSMAX as well as V-MAX allowed identifying patients with substantially high pressure differences concomitant with AscAo dilation. Conclusion Local variations in pressures within ascending aortic cross-sections derived from 4D flow MRI were associated with flow changes, as quantified by vorticity, and with stress exerted by blood on the aortic wall, as quantified by wall shear stress. Such flow-wall and pressure interactions might help for the identification of at-risk patients.

The prevalence of physical inactivity after stroke is high and exercise training improves many outcomes. However, access to community training protocols is limited, especially in low-income settings.To investigate the feasibility and efficacy of a new intervention: Circuit walking, balance, cycling and strength training (CBCS) on activity of daily living (ADL) limitations, motor performance, and social participation restrictions in people after stroke.Forty-six community-dwelling individuals with chronic stroke who were no longer in conventional rehabilitation were randomized into an immediate CBCS group (IG; initially received CBCS training for 12 weeks in phase 1), and a delayed CBCS group (DG) that first participated in sociocultural activities for 12 weeks. In phase 2, participants crossed over so that the DG underwent CBCS and the IG performed sociocultural activities. The primary outcome was ADL limitations measured with the ACTIVLIM-Stroke scale. Secondary outcomes included motor performance (balance: Berg Balance Scale [BBS], global impairment: Stroke Impairment Assessment Set [SIAS] and mobility: 6-minute and 10-metre walk tests [6MWT and 10mWT] and psychosocial health [depression and participation]). Additional outcomes included feasibility (retention, adherence) and safety.ADL capacity significantly improved pre to post CBCS training (ACTIVLIM-stroke, +3,4 logits, p < 0.001; effect size [ES] 0.87), balance (BBS, +21 points, p < 0.001; ES 0.9), impairments (SIAS, +11 points, p < 0.001; ES 0.9), and mobility (+145 m for 6MWT and +0.37 m/s for 10mWT; p < 0.001; ES 0.7 and 0.5 respectively). Similar improvements in psychosocial health occurred in both groups. Adherence and retention rates were 95% and 100%, respectively.CBCS was feasible, safe and improved functional independence and motor abilities in individuals in the chronic stage of stroke. Participation in CBCS improved depression and social participation similarly to participation in sociocultural activities. The benefits persisted for at least 3 months after intervention completion.PACTR202001714888482

AbstractNeurophysiological tests probing the vestibulo‐ocular, colic and spinal pathways are the gold standard to evaluate the vestibular system in clinics. In contrast, vestibular perception is rarely tested despite its potential usefulness in professional training and for the longitudinal follow‐up of professionals dealing with complex man–machine interfaces, such as aircraft pilots. This is explored here using a helicopter flight simulator to probe the vestibular perception of pilots. The vestibular perception of nine professional helicopter pilots was tested using a full flight helicopter simulator. The cabin was tilted six times in roll and six times in pitch (−15°, −10°, −5°, 5°, 10° and 15°) while the pilots had no visual cue. The velocities of the outbound displacement of the cabin were kept below the threshold of the semicircular canal perception. After the completion of each movement, the pilots were asked to put the cabin back in the horizontal plane (still without visual cues). The order of the 12 trials was randomized with two additional control trials where the cabin stayed in the horizontal plane but rotated in yaw (−10° and +10°). Pilots were significantly more precise in roll (average error in roll: 1.15 ± 0.67°) than in pitch (average error in pitch: 2.89 ± 1.06°) (Wilcoxon signed‐rank test: p < 0.01). However, we did not find a significant difference either between left and right roll tilts (p = 0.51) or between forward and backward pitch tilts (p = 0.59). Furthermore, we found that the accuracies were significantly biased with respect to the initial tilt. The greater the initial tilt was, the less precise the pilots were, although maintaining the direction of the tilt, meaning that the error can be expressed as a vestibular error gain in the ability to perceive the modification in the orientation. This significant result was found in both roll (Friedman test: p < 0.01) and pitch (p < 0.001). However, the pitch trend error was more prominent (gain = 0.77 vs gain = 0.93) than roll. This study is a first step in the determination of the perceptive‐motor profile of pilots, which could be of major use for their training and their longitudinal follow‐up. A similar protocol may also be useful in clinics to monitor the aging process of the otolith system with a simplified testing device.

The standard paired-sample testing approach in the multidimensional setting applies multiple univariate tests on the individual features, followed by p-value adjustments. Such an approach suffers when the data carry numerous features. A number of studies have shown that classification accuracy can be seen as a proxy for two-sample testing. However, neither theoretical foundations nor practical recipes have been proposed so far on how this strategy could be extended to multidimensional paired-sample testing. In this work, we put forward the idea that scoring functions can be produced by the decision rules defined by the perpendicular bisecting hyperplanes of the line segments connecting each pair of instances. Then, the optimal scoring function can be obtained by the pseudomedian of those rules, which we estimate by extending naturally the Hodges-Lehmann estimator. We accordingly propose a framework of a two-step testing procedure. First, we estimate the bisecting hyperplanes for each pair of instances and an aggregated rule derived through the Hodges-Lehmann estimator. The paired samples are scored by this aggregated rule to produce a unidimensional representation. Second, we perform a Wilcoxon signed-rank test on the obtained representation. Our experiments indicate that our approach has substantial performance gains in testing accuracy compared to the traditional multivariate and multiple testing, while at the same time estimates each feature's contribution to the final result.

Abstract Background: Evaluating executive dysfunction in brain-damaged patients remains a significant challenge in neurology. Current standard neuropsychological tests, although internally valid, often lack ecological validity. The SDS2 study aims to address this limitation and to improve the understanding of executive dysfunction by collecting multi-modal data including results from ecological and semi-ecological tests. These tests are designed to be more reflective of real-world challenges faced by individuals with executive dysfunction. Methods: The study relies on a longitudinal, non-randomized design, focusing on the results of the Arc de Triomphe Construction Test as the primary outcome. Various statistical methods, including Receiver Operating Characteristic curves, logistic regression models, and intraclass correlation coefficients, will be used to assess the performance and validity of this test. Missing data will be handled using multiple imputation techniques. Secondary, subgroup, and exploratory analyses will focus on various aspects of the collected dataset. Discussion: The SDS2 study's comprehensive statistical framework will contribute to refining the understanding of executive dysfunction. The proposed use of established statistical methods originating from various fields and state-of-the-art machine learning algorithms seems particularly suited for the complex and heterogeneous multi-modal data involved. These data also represent a valuable opportunity to develop new statistical and machine learning analysis methods. Trial registration: ClinicalTrials.gov Identifier: NCT05017051. IDRCB: 2021-A00087-34.

Building upon previously published research, this study assesses and compares the vestibular stimuli experienced by healthy subjects in natural tasks and during the interaction with a complex machine: a helicopter simulator. Our results suggest the existence of an anatomical filter, meaning that body posture shapes vestibular spectral content. Our findings further indicate that operators control their machine within a constrained operating range such that they experience vestibular stimulations that are as ecological as possible.

Vestibular schwannomas (VS) are benign tumors of the vestibular nerve that may trigger hearing loss, tinnitus, rotatory vertigo, and dizziness in patients. Vestibular and auditory tests can determine the precise degree of impairment of the auditory nerve, and superior and inferior vestibular nerves. However, balance is often poorly quantified in patients with untreated vestibular schwannoma, for whom validated standardized assessments of balance are often lacking. Balance can be quantified with the EquiTest. However, this device was developed a long time ago and is expensive, specific, and not sensitive enough to detect early deficits because it assesses balance principally in the sagittal plane on a firm platform. In this study, we assessed postural performances in a well-defined group of VS patients. We used the Dizziness Handicap Inventory (DHI) and a customized device consisting of a smartphone, a mask delivering a fixed or moving visual scene, and foam rubber. Patients were tested in four successive sessions of 25 s each: eyes open (EO), eyes closed (EC), fixed visual scene (VR0), and visual moving scenes (VR1) delivered by the HTC VIVE mask. Postural oscillations were quantified with sensors from an android smartphone (Galaxy S9) fixed to the back. The results obtained were compared to those obtained with the EquiTest. Vestibulo-ocular deficits were also quantified with the caloric test and vHIT. The function of the utricle and saccule were assessed with ocular and cervical vestibular-evoked myogenic potentials (o-VEMPs and c-VEMPs), respectively. We found that falls and abnormal postural oscillations were frequently detected in the VS patients with the VR/Foam device. We detected no correlation between falls or abnormal postural movements and horizontal canal deficit or age. In conclusion, this new method provides a simpler, quicker, and cheaper method for quantifying balance. It will be very helpful for (1) determining balance deficits in VS patients; (2) optimizing the optimal therapy indications (active follow-up, surgery, or gamma therapy) and follow-up of VS patients before and after treatment; (3) developing new rehabilitation methods based on balance training in extreme conditions with disturbed visual and proprioceptive inputs.

Scientific research requires that results can be accessed, tested, and replicated by other researchers. In general, performing reproducible research is not simple and it can be even impossible (for example, in the case of astrophysics replicating singular events if even out of the control of the researcher). However, in computational sciences there is no special hindrance to reproduce, repeat, and compare results. In 2009 the Image Processing On Line (IPOL) journal was founded as a modest contribution to implement reproducible research in the Image Processing field, and then expanded to more general signal-processing algorithms, such as video or physiological signal processing, among others. We re-defined the concept of publication, which is no longer just the article, but the combination of the article, its source code, and any associated data needed to reproduce the results, everything as an indivisible whole. In this article, we present the concept of IPOL, our approach to reproducible research, the challenges we had to address and solve, and some applications other than image processing in IPOL (biomedical, educational). We also present other IPOL inspired initiatives before discussing the opportunity of performing reproducible research in these fields, as well as the advantages and difficulties.

Nowadays, it becomes of paramount societal importance to support many frail-prone groups in our society (elderly, patients with neurodegenerative diseases, etc.) to remain socially and physically active, maintain their quality of life, and avoid their loss of autonomy. Once older people enter the prefrail stage, they are already likely to experience falls whose consequences may accelerate the deterioration of their quality of life (injuries, fear of falling, reduction of physical activity). In that context, detecting frailty and high risk of fall at an early stage is the first line of defense against the detrimental consequences of fall. The second line of defense would be to develop original protocols to detect future fallers before any fall occur. This paper briefly summarizes the current advancements and perspectives that may arise from the combination of affordable and easy-to-use non-wearable systems (force platforms, 3D tracking motion systems), wearable systems (accelerometers, gyroscopes, inertial measurement units-IMUs) with appropriate machine learning analytics, as well as the efforts to address these challenges.

We review epidemiological models for the propagation of the COVID-19 pandemic during the early months of the outbreak: from February to May 2020. The aim is to propose a methodological review that highlights the following characteristics: (i) the epidemic propagation models, (ii) the modeling of intervention strategies, (iii) the models and estimation procedures of the epidemic parameters and (iv) the characteristics of the data used. We finally selected 80 articles from open access databases based on criteria such as the theoretical background, the reproducibility, the incorporation of interventions strategies, etc. It mainly resulted to phenomenological, compartmental and individual-level models. A digital companion including an online sheet, a Kibana interface and a markdown document is proposed. Finally, this work provides an opportunity to witness how the scientific community reacted to this unique situation.