Movement Metrics Research Articles

Long-distance dispersal by a male sub-adult tiger in a human-dominated landscape.

Conservation of wide‐ranging species and their movement is a major challenge in an increasingly fragmented world. Long‐distance movement, such as dispersal, is a key factor for the persistence of population, enabling the movement of animals within and between populations. Here, we describe one of the longest dispersal journeys by a sub‐adult male tiger (Panthera tigris) through GPS telemetry in Central India. We analyzed movement metrics, directionality, and space use during three behavioral stages of dispersal. We also used the clustering method to identify resting and kill sites (n = 89). T1‐C1 dispersed a straight‐line distance of 315 km over 225 days, moving an average of 8.38 km/day and covering a cumulative displacement of ~3000 km. Movement rate during post‐dispersal was faster (mean = 0.47 km/h) than during dispersal (mean = 0.38 km/h) and pre‐dispersal (mean = 0.13 km/h), respectively. The overall movement rate during the night (0.44 km/h) was significantly faster than during the day (0.21 km/h). Likewise, during dispersal, the movement was faster (mean = 0.52 km/h) at night than day (0.24 km/h). The average size of clusters, signifying resting and kill sites, was 1.68 ha and primarily away from human habitation (mean = 1.89 km). The individual crossed roads faster (mean = 2.00 km/h) than it traveled during other times. During the post‐dispersal phase, T1‐C1 had a space use of 319.48 km2 (95% dBBMM) in the Dnyanganga Wildlife Sanctuary. The dispersal event highlights the long‐distance and multiscale movement behavior in a heterogeneous landscape. Moreover, small forest patches play a key role in maintaining large carnivore connectivity while dispersing through a human‐dominated landscape. Our study underlines how documenting the long‐distance movement and integrating it with modern technology can improve conservation management decisions.

Emotion recognition and eye tracking of static and dynamic facial affect: Acomparison of individuals with and without traumatic brain injury

ABSTRACT Diminished social functioning is often seen after traumatic brain injury (TBI). Mechanisms contributing to these deficits are poorly understood but thought to relate to impaired ability to recognize facial expressions. Static stimuli are often used to investigate ability post-TBI, and there is less evidence using more real-life dynamic stimuli. In addition, most studies rely on behavioral responses alone. The present study investigated the performance of a TBI group and matched non-TBI group on static and dynamic tasks using eye-tracking technology alongside behavioral measures. This is the first study to use eye tracking methodology alongside behavioral measures in emotion recognition tasks in people with brain injury. Eighteen individuals with heterogeneous TBI and 18 matched non-TBI participants were recruited. Stimuli representing six core emotions (Anger, Disgust, Fear, Happy, Sad, and Surprise faces) were selected from the Amsterdam Dynamic Facial Expression Set (ADFES). Participants were instructed to identify the emotion displayed correctly whilst eye movement metrics were recorded. Results Results of analyses showed that TBI patients had First Fixation to nose for all emotion stimuli, shorter Fixation Duration and lower Fixation Count to eyes, were generally slower to classify stimuli, and less accurate than non-TBI group for the static task. Those with TBI were also less accurate at identifying Angry, Disgust, and Fear stimulus faces compared to the non-TBI group during the dynamic unfolding of an emotion. Conclusion In the present study, those with TBI had atypical eye scan patterns during emotion identification in the static emotion recognition task compared to the non-TBI group and were associated with lower identification accuracy on behavioral measures in both static and dynamic tasks. Findings suggest potential disruption to oculomotor systems vital for first stage perceptual processing. Arguably, these impairments may contribute to diminished social functioning.

Investigating the Visual Behavior Characteristics of Architectural Heritage Using Eye-Tracking

The visual quality of architectural heritage is crucial to the preservation of architectural features, enhancement of the environmental quality, and conservation of the sustainable development and adaptive use of architectural heritage. Few studies have explored the visual behavior characteristics of rural architectural heritage and which elements influence visual perception. Our study used eye-tracking technology to explore this issue. The results indicate that participants have different visual behavior characteristics for architectural heritage in different scenarios, with five eye movement metrics showing statistical differences. Featured elements attracted more visual attention. The visual behavior characteristics were related to the area, relative area, distance from center, and perimeter. Based on the results, decision-makers can target the sustainable and virtuous development of architectural heritage and enhance environmental quality.

A-37 Ocular Motor Impairments in Concussion Professional Football Players

Abstract Purpose: The purpose of this study was to examine baseline and post-concussion injury characteristics of ocular eye movements using the Sync Think visual eye tracking apparatus in professional football players in the Canadian Football League (CFL). Methods: The visual tracking testing protocol uses an integrated stimulus presentation-eye tracking apparatus (EyeLink CL; SR Research, Ontario, Canada) with which eye movements were recorded at 500 Hz using infrared video-oculography. The standard deviation of radial errors (SDRE) and tangential errors (SDTE) were used to determine poor visual tracking. Participants were (n = 748) rostered players in the Canadian Football League. All participants completed assessments at baseline. Sixteen players completed post-concussion assessments and 98 players completed post-exertional assessments during the 2021 season to evaluate the impact of physical exertion on ocular movement metrics. Results: Participants with diagnosed concussions (n = 16+) demonstrated significantly poorer performance on measures of both gaze stability and smooth pursuit (p < 0.001). The poorer results were correlated with significantly higher subjective ratings of dizziness (p < 0.01) and fogginess (p < 0.001). In contrast, healthy participants who completed the same ocular motor assessments demonstrated no significant differences compared to baseline test performance. Conclusions: Findings suggest that subtle differences in oculomotor functioning arise from sport concussion in professional football players. Further research with larger sample sizes and correlation with other cognitive and physical outcomes is warranted.

Similarities and Differences in the Outsiders and Insiders' Visual Preferences on Sacred Landscape

Previous studies have reported religious and non-religious people as having different psychological experiences when visiting sacred landscapes; however, the visual consensus and differences between diverse groups visiting them have rarely been considered. This study used subjective preference evaluation and experimental eye tracking to assess the visual preferences of different groups regarding sacred landscapes. Overall, 48 photos of the Han Chinese Buddhist temples were selected as stimulus materials, including the categories of squares, architecture, waterscapes, and plants. In all, 90 participants were classified into two groups of outsiders and insiders to view the photos. The consensus and differences in their visual preferences and eye movement metrics were evaluated. The results showed that the two groups were more inclined toward the visual preference of religious architectures than the natural landscape that people usually prefer. Another noteworthy discovery revealed the significant differences between the outsiders and the insiders in viewing and evaluating sacred landscapes; the immersion effect explains this result. Specifically, the group with a higher interaction with the environment had greater visual experiences, easier visual information coding, and larger visual exploration range. In addition, this study revealed familiarity with the religious background facilitated achieving a higher consistency between the landscape preference scores and the eye movement metrics. These findings expand the theory of religious environment perception and provided important insights for subsequent research on sacred landscape planning and management.

Understanding how diel and seasonal rhythms affect the movements of a small non‐migratory bird

AbstractDiel and seasonal rhythms affect an animal's environment and life history. Understanding how these rhythms influence movement increases our knowledge on how animals adjust to changing resources, environmental conditions, and risk to their survival. To better understand how diel and seasonal rhythms affect animals, we evaluated movements of Northern Bobwhite (Colinus virginianus, hereafter bobwhite). Because bobwhite are a small non‐migratory species that must cope with daily and seasonal changes in their environment year‐around, they are a model species to study how diel and seasonal rhythms influence animal movement of a non‐migratory species. GPS data from transmitters attached to bobwhite at four wildlife management sites across Oklahoma were collected during 2019–2021. We parsed the diel data as daytime (7:00 AM–7:00 PM Central Daylight Savings Time [CDT]) and nighttime (7:00 PM–7:00 AM CDT), and diurnal (sunrise–sunset) and nocturnal (sunset–sunrise), as well as by astronomical season. We calculated three movement metrics: net displacement (Euclidean distance from the starting fix to the ending fix of a path, which encompasses consecutive relocations in a time series of geographic fixes); cumulative distance (sum of all Euclidean distances between each consecutive fix along the path); and hourly movement. We modeled the data using a generalized linear mixed modeling approach. Across season, model predictions showed that net displacement was highest during spring, and daytime cumulative distance slowly increased as the year progressed. Bobwhite had two movement peaks during the diurnal period, one during 9:00 AM–10:00 AM and the other during 5:00 PM–8:00 PM depending on the season. Despite being diurnal, bobwhite occasionally made nocturnal movements, likely in response to a disturbance by a predator, inclement weather, or energetic demands. Movement peaks during the diurnal period may reflect changes in behavior in response to energy requirements, predator risk, and changes in air temperature. Life history events likely cause seasonal differences in movement. This study furthers our understanding of how animals move daily and seasonally, suggesting the importance of analyzing movement across the entire year because animals move differently across the day and year.

Modeling System-Wide Urban Rail Transit Energy Consumption: A Case Study of Boston

Rapid transit systems are critical components of urban public transportation networks in their impact, not only on personal mobility but also on the energy and environmental costs associated with network operations. To facilitate effective planning for current and future needs, a framework is required that provides important consumption metrics and also explains the various contributors to energy consumption, along with their interactions. To address this gap, we estimated models that utilized operational and ridership data for the Massachusetts Bay Transportation Authority’s rapid transit system, as well as ambient temperature, to accurately predict system-wide electricity consumption. The models were trained with data from 2019 and tested with data from 2020. The estimated multiple linear regression (MLR) and random forest (RF) models explained 93% and 95% of the variance in the data set, respectively. The MLR model provided predictions with a root mean squared error (RMSE) of 2.7 MWh and mean absolute percentage error (MAPE) of 4.68%, while the RF model resulted in an RMSE of 2.94 MWh and MAPE of 5.01%. We also investigated the impacts of COVID-19 on the transit system by exploring the effects on ridership, energy consumption, cost, and train movement metrics before and during the pandemic. We find that the models are robust and perform well, even with the significant disruptions associated with the COVID-19 pandemic.

Eye Movements as a Window into Decision-Making.

For over 100 years, eye movements have been studied and used as indicators of human sensory and cognitive functions. This review evaluates how eye movements contribute to our understanding of the processes that underlie decision-making. Eye movement metrics signify the visual and task contexts in which information is accumulated and weighed. They indicate the efficiency with which we evaluate the instructions for decision tasks, the timing and duration of decision formation, the expected reward associated with a decision, the accuracy of the decision outcome, and our ability to predict and feel confident about a decision. Because of their continuous nature, eye movements provide an exciting opportunity to probe decision processes noninvasively in real time.

P.028 Eye movement biomarkers for early detection of multiple sclerosis disease progression

Background: There is growing body of evidence linking abnormal eye movements in people with multiple sclerosis (MS) to disease severity and cognition which could better detect disease progression. The objective of this study is to determine if a novel eye-tracking tool can accurately predict disease severity and cognitive status based on eye movement metrics and characterize how they evolve with progression. Methods: Persons with MS (n=132) will be followed over 4 years with clinical assessments every 6 months. Eye movements are also assessed while performing oculomotor tasks using Innodem Neurosciences’ patented eye-tracking technology. The eye movement metrics will be inputted into machine learning classifying algorithms to identify which metrics can serve as reliable Eye Movement Biomarkers (EMB) for MS progression and cognitive status. Results: There were 16 participants recruited as of January 2022 with mean age 47. 3 (SD 10.4; range 26-67), gender (12F/4M), EDSS 2.59 (SD 1.49; range 1.5-6.5), SDMT 51.4 (SD 14.1, range 24-78). With current enrollment, there is a negative correlation between EDSS and SDMT (r = -0.47) as observed in the literature. Conclusions: This trial will demonstrate the utility of EMBs for monitoring MS progression by improving physicians’ access to a reliable, non-invasive, sensitive and accessible marker of disease progression.

Effects of temperature on the movement and feeding behaviour of the large lupine beetle, Sitona gressorius

Even though the effects of insect pests on global agricultural productivity are well recognised, little is known about movement and dispersal of many species, especially in the context of global warming. This work evaluates how temperature and light conditions affect different movement metrics and the feeding rate of the large lupine beetle, an agricultural pest responsible for widespread damage in leguminous crops. By using video recordings, the movement of 384 beetles was digitally analysed under six different temperatures and light conditions in the laboratory. Bayesian linear mixed-effect models were used to analyse the data. Furthermore, the effects of temperature on the daily diffusion coefficient of beetles were estimated by using hidden Markov models and random walk simulations. Results of this work show that temperature, light conditions, and beetles’ weight were the main factors affecting the flight probability, displacement, time being active and the speed of beetles. Significant variations were also observed in all evaluated metrics. On average, beetles exposed to light conditions and higher temperatures had higher mean speed and flight probability. However, beetles tended to stay more active at higher temperatures and less active at intermediate temperatures, around 20 °C. Therefore, both the diffusion coefficient and displacement of beetles were lower at intermediate temperatures. These results show that the movement behaviour and feeding rates of beetles can present different relationships in the function of temperature. It also shows that using a single diffusion coefficient for insects in spatially explicit models may lead to over- or underestimation of pest spread.

Linking wild turkey hen movement data to nesting behavior

AbstractMonitoring of wild turkey (Meleagris gallopavo) females to obtain representative measures of apparent nesting and nest survival rates has long been an important component of wild turkey management. In the interest of improving estimates of apparent nesting and nest survival rates, we assessed the feasibility of inferring reproductive behavior of wild turkeys from remotely acquired movement data. We ascertained detailed nesting stage chronologies using Global Positioning System (GPS) data downloaded from 44 females fitted with transmitters that had both a very high frequency (VHF) beacon and a GPS logger. Then we tracked females using VHF to confirm nest locations and nest fate in north and north‐central Florida. Using twice hourly GPS derived locations, we evaluated 3 predictive machine learning models (Chi‐squared automatic interactive detection [CHAID], exhaustive CHAID, and multivariate adaptive regression splines [MARSpline]) for their ability to accurately classify nesting behaviors (laying and incubating stages) that were confirmed via visual inspection of all potential nest sites. Incubation stage was readily identifiable by the spatial signatures present in each female's GPS‐based movement track across all models (up to 92% true positive and as low as 8% false positives in exhaustive CHAID models), whereas the laying stage was more difficult to identify (up to 65% true positive and as low as 35% false positives in exhaustive CHAID models). Daily averages of movement metrics generally achieved better performance in predictive models than data sets with more frequent sampling (i.e., 30‐minute daytime locations). Our results indicated that exhaustive CHAID models performed best in identifying nesting stages, using movement metrics from GPS data. With continued development, these models may facilitate and improve large‐scale wild turkey monitoring.

Quantifying Workload and Stress in Intensive Care Unit Nurses:PreliminaryEvaluation Using ContinuousEye-Tracking.

(1) To assess mental workloads of intensive care unit (ICU) nurses in 12-hour working shifts (days and nights) using eye movement data; (2) to explore the impact of stress on the ocular metrics of nurses performing patient care in the ICU. Prior studies have employed workload scoring systems or accelerometer data to assess ICU nurses' workload. This is the first naturalistic attempt to explore nurses' mental workload using eye movement data. Tobii Pro Glasses 2 eye-tracking and Empatica E4 devices were used to collect eye movement and physiological data from 15 nurses during 12-hour shifts (252 observation hours). We used mixed-effect models and an ordinal regression model with a random effect to analyze the changes in eye movement metrics during high stress episodes. While the cadence and characteristics of nurse workload can vary between day shift and night shift, no significant difference in eye movement values was detected. However, eye movement metrics showed that the initial handoff period of nursing shifts has a higher mental workload compared with other times. Analysis of ocular metrics showed that stress is positively associated with an increase in number of eye fixations and gaze entropy, but negatively correlated with the duration of saccades and pupil diameter. Eye-tracking technology can be used to assess the temporal variation of stress and associated changes with mental workload in the ICU environment. A real-time system could be developed for monitoring stress and workload for intervention development.

Range of Movement and Patient-Reported Outcomes in Shoulder Arthroplasty in the Elderly: A Comparison of Anatomical Versus Reverse Shoulder Replacements.

IntroductionShoulder arthroplasty is in increasing demand in the elderly given the rising prevalence of glenohumeral osteoarthritis (OA) across the population. There is a dearth of evidence in the current literature comparing anatomical total shoulder arthroplasty and reverse total shoulder arthroplasty (RTSA) in the elderly population. This study compares patient-reported outcome measures and range of movement (ROM) between anatomical and reverse total shoulder replacements in matched patient cohorts over the age of 70 years.Materials and methodsThis retrospective cohort study compares range of movement and patient-reported outcomes between anatomical total shoulder arthroplasty and reverse total shoulder arthroplasty in matched cohorts over the age of 70 years at a single institution between 2011 and 2015. Overall, 75 patients were recruited, including 44 patients with anatomical total shoulder arthroplasty and 31 patients with reverse total shoulder arthroplasty. Cohorts were matched according to age, preoperative Oxford Shoulder Score (OSS), and preoperative range of movement. The minimum clinical follow-up was one year.ResultsAt one year, range of movement metrics in flexion, abduction, and external rotation all demonstrated greater improvements in the anatomical total shoulder arthroplasty cohort in comparison to the reverse total shoulder arthroplasty cohort (p<0.0001). No statistical difference in Oxford Shoulder Score was evident between cohorts.ConclusionAnatomical total shoulder arthroplasty demonstrates a significant improvement in range of movement in comparison to reverse total shoulder arthroplasty in matched elderly patient cohorts. However, there was no statistical difference in functional assessment scores between reverse shoulder replacement and anatomical shoulder replacement.

White-Tailed Deer Spatial Distribution in Relation to '4-Poster' Tick Control Devices in Suburbia.

Deer are keystone hosts for adult ticks and have enabled the spread of tick distributions. The ‘4-Poster’ deer bait station was developed by the United States Department of Agriculture to control ticks feeding on free-ranging deer. Although effective in certain scenarios, ‘4-Poster’ deer treatment stations require the use of bait to attract deer to one location, which may cause increased deer disease transmission rates and habitat damage. To better understand and manage the impact of baited ‘4-Poster’ stations on deer movements, we captured and GPS-monitored 35 deer as part of an integrated pest management project. Fifteen ‘4-Poster’ stations were deployed among three suburban county parks to control ticks. To quantify the effects of ‘4-Poster’ stations, we calculated deer movement metrics before and after feeders were filled with whole kernel corn, and we gathered information on visitation rates to feeders. Overall, 83.3% of collared deer visited a feeder and revisited approximately every 5 days. After feeders were refilled, collared deer were ~5% closer to feeders and conspecifics than before filling. Males used a higher percentage of available feeders and visited them more throughout the deployment periods. Although these nuanced alterations in behavior may not be strong enough to increase local deer abundance, in light of infectious diseases affecting deer populations and effective ‘4-Poster’ densities, the core range shifts and clustering after refilling bait may be a cause for concern. As such, trade-offs between conflicting management goals should be carefully considered when deploying ‘4-Poster’ stations.

Climate alters the movement ecology of a non-migratory bird.

Global climate change is causing increased climate extremes threatening biodiversity and altering ecosystems. Climate is comprised of many variables including air temperature, barometric pressure, solar radiation, wind, relative humidity, and precipitation that interact with each other. As movement connects various aspects of an animal's life, understanding how climate influences movement at a fine‐temporal scale will be critical to the long‐term conservation of species impacted by climate change. The sedentary nature of non‐migratory species could increase some species risk of extirpation caused by climate change. We used Northern Bobwhite (Colinus virginianus; hereafter bobwhite) as a model to better understand the relationship between climate and the movement ecology of a non‐migratory species at a fine‐temporal scale. We collected movement data on bobwhite from across western Oklahoma during 2019–2020 and paired these data with meteorological data. We analyzed movement in three different ways (probability of movement, hourly distance moved, and sinuosity) using two calculated movement metrics: hourly movement (displacement between two consecutive fixes an hour apart) and sinuosity (a form of tortuosity that determines the amount of curvature of a random search path). We used generalized linear‐mixed models to analyze probability of movement and hourly distance moved, and used linear‐mixed models to analyze sinuosity. The interaction between air temperature and solar radiation affected probability of movement and hourly distance moved. Bobwhite movement increased as air temperature increased beyond 10°C during low solar radiation. During medium and high solar radiation, bobwhite moved farther as air temperature increased until 25–30°C when hourly distance moved plateaued. Bobwhite sinuosity increased as solar radiation increased. Our results show that specific climate variables alter the fine‐scale movement of a non‐migratory species. Understanding the link between climate and movement is important to determining how climate change may impact a species’ space use and fitness now and in the future.

Deciphering heterogeneous populations of migrating cells based on the computational assessment of their dynamic properties.

SummaryNeuronal migration is a highly dynamic process, and multiple cell movement metrics can be extracted from time-lapse imaging datasets. However, these parameters alone are often insufficient to evaluate the heterogeneity of neuroblast populations. We developed an analytical pipeline based on reducing the dimensions of the dataset by principal component analysis (PCA) and determining sub-populations using k-means, supported by the elbow criterion method and validated by a decision tree algorithm. We showed that neuroblasts derived from the same adult neural stem cell (NSC) lineage as well as across different lineages are heterogeneous and can be sub-divided into different clusters based on their dynamic properties. Interestingly, we also observed overlapping clusters for neuroblasts derived from different NSC lineages. We further showed that genetic perturbations or environmental stimuli affect the migratory properties of neuroblasts in a sub-cluster-specific manner. Our data thus provide a framework for assessing the heterogeneity of migrating neuroblasts.

Behavioral states in space and time: understanding landscape use by an invasive mammal

AbstractAnimal movement models can be used to understand species behavior and assist with implementation of management activities. We explored behavioral states of an invasive wild pig (Sus scrofa) population that recently colonized central Michigan, USA, 2014–2018. To quantify environmental factors related to wild pig movement ecology and spatio‐temporal landscape use, we predicted wild pig behavioral states relative to land cover type, landscape structure (i.e., edge and patch cohesion), and weather conditions. We used global positioning system (GPS)‐collars and monitored 8 wild pigs from 2014–2018. We fit local convex hulls and calculated movement metrics revealing 3 wild pig behavioral states (resting, exploratory, and relocating) and constructed a 3‐level model to predict behavioral state probabilities relative to biotic and abiotic conditions. Probabilities of exploratory and resting behaviors were higher nearer to riparian and open herbaceous cover types (oftentimes emergent marsh), indicating that these cover types provided security cover during activity and bedding. Hard mast cover types had a strong positive association with relocating behaviors. More cohesive patches of agriculture and shrub cover types were associated with higher probabilities of exploratory behaviors, while resting was more likely in continuous patches of agriculture (mostly mid‐summer corn). The probability of exploratory behaviors increased exponentially with warming ambient temperature. Our results may be used by managers to develop control strategies conducive to landscape and environmental conditions where the likelihood of encountering wild pigs is highest or targeting wild pigs when in a behavioral state most vulnerable to a particular removal technique.

Automated assessment of hyoid movement during normal swallow using ultrasound.

BackgroundThe potential for using ultrasound by speech and language therapists (SLTs) as an adjunct clinical tool to assess swallowing function has received increased attention during the COVID‐19 pandemic, with a recent review highlighting the need for further research on normative data, objective measurement, elicitation protocol and training. The dynamic movement of the hyoid, visible in ultrasound, is crucial in facilitating bolus transition and protection of the airway during a swallow and has shown promise as a biomarker of swallowing function.AimsTo examine the kinematics of the hyoid during a swallow using ultrasound imaging and to relate the patterns to the different stages of a normal swallow. To evaluate the accuracy and robustness of two different automatic hyoid tracking methods relative to manual hyoid position estimation.Methods & ProceduresUltrasound data recorded from 15 healthy participants swallowing a 10 ml water bolus delivered by cup or spoon were analysed. The movement of the hyoid was tracked using manually marked frame‐to‐frame positions, automated hyoid shadow tracking and deep neural net (DNN) tracking. Hyoid displacement along the horizontal image axis (HxD) was charted throughout a swallow, and the maximum horizontal displacement (HxD max) and maximum hyoid velocity (HxV max) along the same axis were automatically calculated.Outcomes & ResultsThe HxD and HxV of 10 ml swallows are similar to values reported in the literature. The trajectory of the hyoid movement and its location at significant swallow event time points showed increased hyoid displacement towards the peak of the swallow. Using an interclass correlation coefficient, HxD max and HxV max values derived from the DNN tracker and shadow tracker are shown to be in high agreement and moderate agreement, respectively, when compared with values derived from manual tracking.Conclusions & ImplicationsThe similarity of the hyoid tracking results using ultrasound to previous reports based on different instrumental tools supports the possibility of using hyoid movement as a measure of swallowing function in ultrasound. The use of machine learning to automatically track the hyoid movement potentially provides a reliable and efficient way to quantify swallowing function. These findings contribute towards improving the clinical utility of ultrasound as a swallowing assessment tool. Further research on both normative and clinical populations is needed to validate hyoid movement metrics as a means of differentiating normal and abnormal swallows and to verify the reliability of automatic tracking.WHAT THIS PAPER ADDSWhat is already known on this subject There is growing interest in the use of ultrasound as an adjunct tool for assessing swallowing function. However, there is currently insufficient knowledge about the patterning and timing of lingual and hyoid movement in a typical swallow. We know that movement of the hyoid plays an essential role in bolus transition and airway protection. However, manual tracking of hyoid movement is time‐consuming and restricts the extent of large‐scale normative studies. What this study adds We show that hyoid movement can be tracked automatically, providing measurable continuous positional data. Measurements derived from this objective data are comparable with similar measures previously reported using videofluoroscopy and of the two automatic trackers assessed, the DNN approach demonstrates better robustness and higher agreement with manually derived measures. Using this kinematic data, hyoid movement can be related to different stages of swallowing. Clinical implications of this study This study contributes towards our understanding of the kinematics of a typical swallow by evaluating an automated hyoid tracking method, paving the way for future studies of typical and disordered swallow. The challenges of image acquisition highlight issues to be considered when establishing clinical protocols. The application of machine learning enhances the utility of ultrasound swallowing assessment by reducing the labour required and permitting a wider range of hyoid measurements. Further research in normative and clinical populations is facilitated by automatic data extraction allowing the validity of prospective hyoid measures in differentiating different types of swallows to be rigorously assessed.

The influence of tactical and match context on player movement in football

ABSTRACT Player movement metrics in football such as speed and distance are typically analysed as aggregates, sometimes outside of any specific tactical or match context. This research adds context to a player’s movement over the course of a match by analysing movement profiles s and bringing together tools from the sport science and sports analytics literature. Position-specific distributions of player movement metrics: speed, acceleration and tortuosity were compared across phases of play and in-game win probability using 25 Hz optical player tracking data from all 52 matches at the 2019 FIFA Women’s World Cup. Comparing the distributions using the Kolmogorov–Smirnov test and Wasserstein distances, differences were identified in these movement profiles across, in and out of possession phases, with small negligible overall positional trends across in-game win probabilities. In-game win probabilities are used in tandem with phases to present a player specific case study. The results demonstrate how sports analytics metrics can be used to contextualise a subset of movement metrics from sport science and provide a framework for analysis of further movement metrics and sports analytics modelling approaches.

Application of telemetry and stable isotope analyses to inform the resource ecology and management of a marine fish

Abstract Animal movement and resource use are essential considerations for effective environmental management, but they are challenging to quantify in expansive natural ecosystems such as oceans. We used a novel combination of fish tracking with expansive acoustic telemetry networks, stable isotope analysis and integrated modelling techniques to characterize the spatial and trophic ecology of a marine fish species, permit Trachinotus falcatus, and to address specific resource management needs in the Florida Keys. Tracking‐based movement patterns indicated that permit remained primarily within the designated fisheries management unit (92% of individuals), but they moved frequently among distinct habitat types and fisheries. Movement metrics from 109 individuals were integrated into Bayesian isotope mixing models, revealing variable reliance on seagrass‐ versus offshore/pelagic‐based energy channels amongst individuals. Variance was driven mainly by fish habitat use and home range size (km2). A telemetry‐based regional isoscape, informed by individual‐level estimates of resource use (% seagrass reliance; median = 70%, 29%–100% range), illustrated connectivity among habitats and fisheries. Specifically, seagrass flats were highly connected with the Florida reef tract, with frequent movements between these habitat types and a high reliance on seagrass‐based prey. There was a distinction between these fish and those occupying artificial reefs, with the latter showing high use of pelagic/offshore (i.e. planktonic) energy channels. Synthesis and applications. This study used a novel combination of telemetry, stable isotope analysis and integrated modelling techniques to identify two distinct ecotypes of a nearshore fish species, permit, in the Florida Keys. Of the two ecotypes, nearshore Florida Keys permit support multiple valuable fisheries; for these fish management should prioritize conservation of seagrass flats as a key permit food source, as well as fisheries protection measures at spawning sites on the Florida reef tract. This study highlights the capacity for integrated telemetry‐isotope models to provide key insights into animal ecology that has direct implications for applied environmental management.