Individual Movement Patterns Research Articles

Distinct Motion Control Strategy during Unanticipated Landing: Transitioning from Copers to Chronic Ankle Instability

Background: Patients with chronic ankle instability (CAI) demonstrated altered movement patterns during unanticipated landing compared to coper patients. Understanding the effects of kinematics, dynamics and energetics on individual movement patterns during landing could enhance motor control strategies for patients with ankle sprains while avoiding the transition of coper patients to CAI patients. Therefore, the purpose of this study was to investigate the differences in movement patterns of coper patients compared to CAI patients during the unanticipated landings; Methods: Fifteen individuals with CAI (age: 22.8±1.4 years; height: 180.1±4.2 cm; weight: 81.5±5.8 kg) and fifteen copers (age: 23.1±1.2 years; height: 179.8±4.4 cm, weight: 80.4±6.2 kg) participated in an unanticipated landing task, during which three-dimensional motion capture, ground reaction force (GRF), and muscle activation data were collected. A musculoskeletal model was used to estimate muscle force and joint power among these two groups. Joint power was calculated as the product of angular velocity in the sagittal plane and joint moment data, reflecting the energy transfer at the ankle, knee, and hip joints. Furthermore, energy dissipation and generation within these joints were determined by integrating specific regions of the joint power curve; Results: Individuals with CAI demonstrated a greater muscle force in the vastus lateralis compared copers during the unanticipated landing task, while copers exhibited higher peak muscle forces in the medial gastrocnemius (p=0.007), lateral gastrocnemius (p=0.002), soleus (p=0.004). The muscle activation patterns of CAI patients also differ from those of coper patients. Compared to copers, CAI patients exhibit earlier activation of the rectus femoris (p<0.001) and lateral gastrocnemius muscles (p=0.042). Conversely, copers demonstrate earlier activation of the soleus (p=0.004) and medial gastrocnemius (p=0.003) muscles. In addition, joint power in CAI individuals during unanticipated landing shifted from the ankle to the knee and hip (p<0.001); Conclusions: These findings suggest that individuals with CAI exhibit a change in motion control strategy during unanticipated landing tasks. The variations in peak forces and the ability of proximal muscles to generate force might enable them to offset the deficits noted in distal muscles. Energy redistribution issues observed in CAI patients may help to prevent the transition of coper patients towards developing CAI patients.

Integration of Building Information Model into a Game Engine Platform for Indoor Accessibility Analyses

Understanding the movement patterns of individuals within a structure is crucial for efficient simulation. This entails the examination of network accessibility based on insights into the intricate indoor three-dimensional network topology. The combination of Building Information Modeling with Game Engines can streamline this approach. Hence, this study proposes a pipeline integrating the A* shortest path algorithm and walkable three-dimensional navigation meshes to analyze indoor accessibility. The pipeline design was deployed in a public building, where scenario-based analyses were conducted to determine the average distance and time shifts based on blockages. According to the results, exits' positioning and availability significantly impact indoor navigation and accessibility, underscoring their significance in building design and emergency preparedness in complex buildings.

The Impact of Scale on Extracting Individual Mobility Patterns from Location-Based Social Media.

Understanding human movement patterns is crucial for comprehending how a city functions. It is also important for city planners and policymakers to create more efficient plans and policies for urban areas. Traditionally, human movement patterns were analyzed using origin-destination surveys, travel diaries, and other methods. Now, these patterns can be identified from various geospatial big data sources, such as mobile phone data, floating car data, and location-based social media (LBSM) data. These extensive datasets primarily identify individual or collective human movement patterns. However, the impact of spatial scale on the analysis of human movement patterns from these large geospatial data sources has not been sufficiently studied. Changes in spatial scale can significantly affect the results when calculating human movement patterns from these data. In this study, we utilized Weibo datasets for three different cities in China including Beijing, Guangzhou, and Shanghai. We aimed to identify the effect of different spatial scales on individual human movement patterns as calculated from LBSM data. For our analysis, we employed two indicators as follows: an external activity space indicator, the radius of gyration (ROG), and an internal activity space indicator, entropy. These indicators were chosen based on previous studies demonstrating their efficiency in analyzing sparse datasets like LBSM data. Additionally, we used two different ranges of spatial scales-10-100 m and 100-3000 m-to illustrate changes in individual activity space at both fine and coarse spatial scales. Our results indicate that although the ROG values show an overall increasing trend and the entropy values show an overall decreasing trend with the increase in spatial scale size, different local factors influence the ROG and entropy values at both finer and coarser scales. These findings will help to comprehend the dynamics of human movement across different scales. Such insights are invaluable for enhancing overall urban mobility and optimizing transportation systems.

Unveiling realistic mobility patterns with home–origin–destination data aggregation

The availability of increasingly abundant mobility data in recent years has opened up new avenues for researchers to unravel human mobility patterns. Data aggregation methods have been introduced to gain a quantitative understanding of collective individual movements using these data. Nevertheless, the widely adopted origin–destination (OD) aggregation method for human mobility data lacks an essential piece of information: home location, which plays a vital role in characterizing individual movement patterns. In this study, we propose a novel data aggregation approach called home–origin–destination (HOD) with the aim of improving the accuracy of human mobility estimation. We compare the performance of various data aggregation methods for estimating population distribution. Our experimental results reveal more realistic mobility patterns when incorporating estimated home information, where individuals move out in the morning and return home before midnight. To further evaluate the effectiveness of the HOD approach, we conduct an entropy analysis to measure the unpredictability of human mobility. The HOD results exhibit lower entropy values than those in the other two cases, OD and home–destination (HD). These findings underscore the importance of incorporating home information in understanding and modeling human mobility. By leveraging the HOD data aggregation method, we can achieve more accurate population distribution estimates and capture the inherent dynamics of human movement

Individual and temporal variation in movement patterns of wild alpine reindeer and implications for disease management

Animal behaviour is important for prevalence and outbreaks of infectious diseases, for instance by affecting individual interactions. Increasing the knowledge of individual movement patterns can provide better insight into disease prevalence and spread, helping to target efforts to minimise disease outbreaks. Chronic wasting disease (CWD) is a fatal prion disease affecting cervids. CWD is transmitted by animal‐to‐animal contact and through the environment, thus individual variation in space use and social associations may influence disease transmission patterns and infection risk. CWD was detected in Norwegian alpine reindeer Rangifer tarandus tarandus in 2016, and eradication of the infected population was implemented. A 3:1 infection rate between males and females suggests sex‐specific behavioural drivers. We utilised an extensive individual‐based dataset of 149 GPS‐marked wild reindeer to investigate individual variation in movement patterns in terms of inter‐ and intra‐annual home range size and site fidelity, and variation in home range overlap and distances between individuals. We aimed to identify patterns which could indicate higher potential disease risk. Females had larger annual and seasonal home ranges than males, except during calving and rut. Greater home range overlaps and shorter between‐individual distances were found between same‐sex individuals than different‐sex individuals, except during the rut. Accordingly, the rut season stands out with greater male home ranges, greater home range overlap and shorter distances between males and between males and females, which could indicate that this season is critical for disease transmission. Measures to prevent disease spread should lower contact rates, e.g. by reducing the abundance of adult males before they mix with other groups during the rut. This can be achieved for instance by allowing earlier hunt on adult males when they are distributed in small male groups, to reduce the transmission risk and keep disturbance of other individuals low.

Biomechanical comparison of hip and ankle kinematics among national and university-level field hockey players: An observational study

Abstract Background: The penalty corner stands out as a crucial scoring method in field hockey, with the Drag flick (DF) being the most frequently employed shot during this situation. The DF is more effective than the hit or push techniques. Purpose: This study aimed to explore variations in hip and ankle kinematics during different stages of the DF among field hockey players at national and university levels. Materials and Methods: The study adopted a cross-sectional design involving participation from professional male drag flickers, as well as national and university-level (UL) players, with reported mean ± SD values for height (172 ± 1.41 cm), weight (72.5 ± 2.12 kg), and BMI (24.4 ± 0.35 kg/m2). Following a specific warm-up, each player underwent the random recording of 10 trials on the hockey ground. XSENS inertial measuring unit was employed to acquire and analyze kinematics data. Thirty frames were extracted, spanning the DF technique’s initial phase to the final phase for subsequent analysis. Results: The findings revealed distinct variations in joint angle (XZY) range of motion (ROM) during different phases of the DF among national and UL players. Notably, significant (P < 0.05) and diverse changes were identified in various parameters of lower limb kinematics when comparing DF shots. Conclusion: The study’s conclusion emphasizes that comprehending the ROM variations in hockey players is crucial for sports scientists and coaches. NL and UL players showed different movement patterns in the same DF technique but at different extents. This knowledge enables them to understand the biomechanical responses necessary to attain optimal movement, mainly when aiming for the goal. It allows for a focused analysis of individual player movement patterns.

Characterizing Movement Patterns of Older Individuals with T2D in Free-Living Environments Using Wearable Accelerometers

(1) Background: Type 2 Diabetes (T2D) is associated with reduced muscle mass, strength, and function, leading to frailty. This study aims to analyze the movement patterns (MPs) of older individuals with T2D across varying levels of physical capacity (PC). (2) Methods: A cross-sectional study was conducted among individuals aged 60 or older with T2D. Participants (n = 103) were equipped with a blinded continuous glucose monitoring (CGM) system and an activity monitoring device for one week. PC tests were performed at the beginning and end of the week, and participants were categorized into three groups: low PC (LPC), medium PC (MPC), and normal PC (NPC). Group differences in MPs and physical activity were analyzed using non-parametric Kruskal–Wallis tests for both categorical and continuous variables. Dunn post-hoc statistical tests were subsequently carried out for pairwise comparisons. For data analysis, we utilized pandas, a Python-based data analysis tool, and conducted the statistical analyses using the scipy.stats package in Python. The significance level was set at p < 0.05. (3) Results: Participants in the LPC group showed lower medio-lateral acceleration and higher vertical and antero-posterior acceleration compared to the NPC group. LPC participants also had higher root mean square values (1.017 m/s2). Moreover, the LPC group spent less time performing in moderate to vigorous physical activity (MVPA) and had fewer daily steps than the MPC and NPC groups. (4) Conclusions: The LPC group exhibited distinct movement patterns and lower activity levels compared to the NPC group. This study is the first to characterize the MPs of older individuals with T2D in their free-living environment. Several accelerometer-derived features were identified that could differentiate between PC groups. This novel approach offers a manpower-free alternative to identify physical deterioration and detect low PC in individuals with T2D based on real free-living physical behavior.

Exploring crowd persistent dynamism from pedestrian crossing perspective: An empirical study

Crowd studies have gained increasing relevance due to the recurring incidents of crowd crush accidents. In addressing the issue of the crowd's persistent dynamism, this paper explored the macroscopic and microscopic features of pedestrians crossing in static and dynamic contexts, employing a series of systematic experiments. Firstly, empirical evidence has confirmed the existence of crowd’s persistent dynamism. Subsequently, the research delves into two aspects, qualitative and quantitative, to address the following questions: (1) Cross pedestrians tend to avoid high-density areas when crossing static crowds and particularly evade pedestrians in front to avoid deceleration, thus inducing the formation of cross-channels, a self-organization phenomenon. (2) In dynamic crowds, when pedestrian suffers spatial constrained, two patterns emerge: decelerate or detour. Research results indicate the differences in pedestrian crossing behaviors between static and dynamic crowds, such as the formation of crossing channels, backward detours, and spiral turning. However, the strategy of pedestrian crossing remains consistent: utilizing detours to overcome spatial constraints. Finally, the empirical results of this study address the final question: pedestrians detouring causes crowds’ persistent collective dynamism. These findings contribute to an enhanced understanding of pedestrian dynamics in extreme conditions and provide empirical support for research on individual movement patterns and crowd behavior prediction.

Combined influence of psychological and biomechanical factors in muscular loads in soccer : Anew approach for the prevention of muscle injuries

When mental stress and musculoskeletal loading interact, the risk for injury increases due to altered body kinematics and increased muscle tension. These changes can be detected with musculoskeletal models, and mental loading and stress must be analyzed at emotional, cognitive, and behavioral levels. To investigate these kinematic and loading changes under stress, competitive athletes were subjected to mental stress during highly dynamic movements, and musculoskeletal models were used to analyze the biomechanical loading. It was shown that under mental stress, independent of the subjective perception, astrong change in muscle forces can occur. Accordingly, competitive athletes should undergo screenings to assess individual movement patterns and promote general stress resilience.

Discovering urban mobility structure: a spatio-temporal representational learning approach

ABSTRACTThe urban mobility structure is a summary of individual movement patterns and the interaction between persons and the urban environment, which is extremely important for urban management and public transportation route planning. The majority of current research on urban mobility structure discovery utilizes the urban environment as a static network to detect the relationship between people groups and urban areas, ignoring the vital problem of how individuals affect urban mobility structure dynamically. In this paper, we propose a spatio-temporal representational learning method based on reinforcement learning for discovering urban mobility structures, in which the model can effectively consider the interaction knowledge graph of individuals with stations while accounting for the spatio-temporal heterogeneity of individual travel. The experimental results demonstrate the advantages of individual travel-based urban mobility structure discovery research in describing the interaction between individuals and urban areas, which can account for the intrinsic influence more thoroughly.

The relative importance of social information use for population abundance in group-living and non-grouping prey

Predator–prey relationships are fundamental components of ecosystem functioning, within which the spatial consequences of prey social organization can alter predation rates. Group-living (GL) species are known to exploit inadvertent social information (ISI) that facilitates population persistence under predation risk. Still, the extent to which non-grouping (NG) prey can benefit from similar processes is unknown. Here we built an individual-based model to explore and compare the population-level consequences of ISI use in GL and NG prey. We differentiated between GL and NG prey only by the presence or absence of social attraction toward conspecifics that drives individual movement patterns. We found that the extent of the benefits of socially acquired predator information in NG highly depends on the prey’s ability to detect nearby predators, prey density and the occurrence of false alarms. Conversely, even moderate probabilities of ISI use and predator detection can lead to maximal population-level benefits in GL prey. This theoretical work provides additional insights into the conditions under which ISI use can facilitate population persistence irrespective of prey social organisation.

Altered upper limb kinematics in individuals with dyskinetic cerebral palsy in comparison with typically developing peers – A statistical parametric mapping study

BackgroundDyskinetic cerebral palsy (DCP) is clinically characterized by involuntary movements and abnormal postures, which can aggravate with activity. While upper limb movement variability is often detected in the clinical picture, it remains unknown how movement patterns of individuals with DCP differ from typically developing (TD) peers. Research questionDo individuals with DCP show i) higher time-dependent standard deviations of upper limb joint angles and ii) altered upper limb kinematics in time and/or amplitude during functional upper limb tasks in comparison with TD individuals? MethodsThree-dimensional upper limb movement patterns were cross-sectionally compared in 50 individuals with and without DCP during three functional tasks: reach forward (RF), reach and grasp vertical (RGV) and reach sideways (RS). Mean and point-wise standard deviations of angular waveform of the upper limb joint angles were compared between groups to evaluate differences in time and/or amplitude using traditional and non-linear registration statistical parametric mapping. ResultsThirty-five extremities from 30 individuals (mean age 17y4m, range 5–25 y; MACS level I(n = 2); II(n = 15); III(n = 16); IV(n = 2)) with DCP and twenty TD individuals (mean age 16y8m, range 8–25 y) were evaluated. The DCP compared to TD group showed higher point-wise standard deviations at the level of all joints, which was time-dependent and varied between tasks. Mean wrist and elbow flexion was higher for the DCP group during RF (0–83 % wrist; 57–100 % elbow), RGV (0–82 % wrist; 12–100 % elbow) and RS (0–43 % wrist; 70–100 % elbow). SignificanceThis is the first study exploring the movement patterns of individuals with DCP during reaching using quantitative measures. Analyzing these individual movement patterns by statistical parametric mapping (SPM) allows us to focus on both specific joint or on specific timing during the movement cycle. The individual information that this method yields can guide individual therapy aiming to improve reaching function in different parts of the movement cycle or evaluate intervention effects on upper extremity treatment.

Spatial heterogeneity and infection patterns on epidemic transmission disclosed by a combined contact-dependent dynamics and compartmental model.

Epidemics, such as COVID-19, have caused significant harm to human society worldwide. A better understanding of epidemic transmission dynamics can contribute to more efficient prevention and control measures. Compartmental models, which assume homogeneous mixing of the population, have been widely used in the study of epidemic transmission dynamics, while agent-based models rely on a network definition for individuals. In this study, we developed a real-scale contact-dependent dynamic (CDD) model and combined it with the traditional susceptible-exposed-infectious-recovered (SEIR) compartment model. By considering individual random movement and disease spread, our simulations using the CDD-SEIR model reveal that the distribution of agent types in the community exhibits spatial heterogeneity. The estimated basic reproduction number R0 depends on group mobility, increasing logarithmically in strongly heterogeneous cases and saturating in weakly heterogeneous conditions. Notably, R0 is approximately independent of virus virulence when group mobility is low. We also show that transmission through small amounts of long-term contact is possible due to short-term contact patterns. The dependence of R0 on environment and individual movement patterns implies that reduced contact time and vaccination policies can significantly reduce the virus transmission capacity in situations where the virus is highly transmissible (i.e., R0 is relatively large). This work provides new insights into how individual movement patterns affect virus spreading and how to protect people more efficiently.

Predicting Autism from Head Movement Patterns during Naturalistic Social Interactions.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized in part by difficulties in verbal and nonverbal social communication. Evidence indicates that autistic people, compared to neurotypical peers, exhibit differences in head movements, a key form of nonverbal communication. Despite the crucial role of head movements in social communication, research on this nonverbal cue is relatively scarce compared to other forms of nonverbal communication, such as facial expressions and gestures. There is a need for scalable, reliable, and accurate instruments for measuring head movements directly within the context of social interactions. In this study, we used computer vision and machine learning to examine the head movement patterns of neurotypical and autistic individuals during naturalistic, face-to-face conversations, at both the individual (monadic) and interpersonal (dyadic) levels. Our model predicts diagnostic status using dyadic head movement data with an accuracy of 80%, highlighting the value of head movement as a marker of social communication. The monadic data pipeline had lower accuracy (69.2%) compared to the dyadic approach, emphasizing the importance of studying back-and-forth social communication cues within a true social context. The proposed classifier is not intended for diagnostic purposes, and future research should replicate our findings in larger, more representative samples.

The discrimination of expressions in facial movements by infants: A study with point-light displays

Perceiving facial expressions is an essential ability for infants. Although previous studies indicated that infants could perceive emotion from expressive facial movements, the developmental change of this ability remains largely unknown. To exclusively examine infants’ processing of facial movements, we used point-light displays (PLDs) to present emotionally expressive facial movements. Specifically, we used a habituation and visual paired comparison (VPC) paradigm to investigate whether 3-, 6-, and 9-month-olds could discriminate between happy and fear PLDs after being habituated with a happy PLD (happy-habituation condition) or a fear PLD (fear-habituation condition). The 3-month-olds discriminated between the happy and fear PLDs in both the happy- and fear-habituation conditions. The 6- and 9-month-olds showed discrimination only in the happy-habituation condition but not in the fear-habituation condition. These results indicated a developmental change in processing expressive facial movements. Younger infants tended to process low-level motion signals regardless of the depicted emotions, and older infants tended to process expressions, which emerged in familiar facial expressions (e.g., happy). Additional analyses of individual difference and eye movement patterns supported this conclusion. In Experiment 2, we concluded that the findings of Experiment 1 were not due to a spontaneous preference for fear PLDs. Using inverted PLDs, Experiment 3 further suggested that 3-month-olds have already perceived PLDs as face-like stimuli.

Movement Regularity Differentiates Specialized and Nonspecialized Athletes in a Virtual Reality Soccer Header Task.

Young athletes who specialize early in a single sport may subsequently be at increased risk of injury. While heightened injury risk has been theorized to be related to volume or length of exposure to a single sport, the development of unhealthy, homogenous movement patterns, and rigid neuromuscular control strategies may also be indicted. Unfortunately, traditional laboratory assessments have limited capability to expose such deficits due to the simplistic and constrained nature of laboratory measurement techniques and analyses. To overcome limitations of prior studies, the authors proposed a soccer-specific virtual reality header assessment to characterize the generalized movement regularity of 44 young female athletes relative to their degree of sport specialization (high vs low). Participants also completed a traditional drop vertical jump assessment. During the virtual reality header assessment, significant differences in center of gravity sample entropy (a measure of movement regularity) were present between specialized (center of gravity sample entropy: mean = 0.08, SD = 0.02) and nonspecialized center of gravity sample entropy: mean = 0.10, SD = 0.03) groups. Specifically, specialized athletes exhibited more regular movement patterns during the soccer header than the nonspecialized athletes. However, no significant between-group differences were observed when comparing participants' center of gravity time series data from the drop vertical jump assessment. This pattern of altered movement strategy indicates that realistic, sport-specific virtual reality assessments may be uniquely beneficial in exposing overly rigid movement patterns of individuals who engage in repeated sport specialized practice.

Sprinting performance of individuals with unilateral transfemoral amputation: compensation strategies for lower limb coordination.

Understanding the sprinting patterns of individuals with unilateral transfemoral amputation (uTFA) is important for designing improved running-specific prostheses and for prosthetic gait rehabilitation. Continuous relative phase (CRP) analysis acquires clues from movement kinematics and obtains insights into the sprinting coordination of individuals with uTFA. Seven individuals with uTFA sprinted on a 40 m runway. The spatio-temporal parameters, joint and segment angles of the lower limbs were obtained, and CRP analysis was performed on thigh-shank and shank-foot couplings. Subsequently, the asymmetry ratios of the parameters were calculated. Statistical analyses were performed between the lower limbs. Significant differences in the stance time, stance phase percentage, ankle joint angles and CRP of the shank-foot coupling (p < 0.05) were observed between the lower limbs. The primary contributor to these differences could be the structural differences between the lower limbs. Despite the presence of different coordination features in the stance and swing phases between the lower limbs, no significant difference in the coordination patterns of the thigh-shank coupling was observed. This may be a compensation strategy for achieving coordination patterns with improved symmetry between the lower limbs. The results of this study provide novel insights into the sprinting movement patterns of individuals with uTFA.

Depth Partitioning and Diel Movement of Two Large Carcharhinid Sharks in Extremely Shallow Waters

Two species of carcharhinid sharks aggregate every winter at the warm water effluent of a coastal power plant on the Israeli Mediterranean coast. The two species (Carcharhinus obscurus and Carcharhinus plumbeus) cooccur in a highly confined area for several months every year and are highly associated with the area in and around the hot water effluent. Niche partitioning has recently been suggested as a mechanism that enables the coexistence of similar shark species by resource partitioning, spatial partitioning, and temporal partitioning. In this study, we used acoustic telemetry to study the individual diel movement and activity patterns within this enclosed area and examined the differences between the two species sharing it. Although this location only reaches a maximum depth of 7.5 m, we found both species perform a diel vertical movement, rising closer to the surface at night and moving deeper during daytime. Furthermore, the two shark species swam at different depths both day and night, with C. obscurus swimming in the upper column, about 2 m shallower than C. plumbeus. The very small scale of movement, which nearly equals the sharks’ body length, suggests movement patterns might be conserved at the species level. Moreover, spatiotemporal differences between the two species may reflect a mean of interspecific partitioning that occurs even in a highly confined and shallow habitat.

Editor's Choice: February 2023

Beetles on the move: not-just-a-technical review of beetles' radio-tracking – J. Růžičková & Z. Elek (https://doi.org/10.1111/eea.13260) Figure A.1 (a) Elicited uncertainty of pest infestation per 10,000 plants (histogram in blue–vertical blue line indicates the elicited percentile in the following order: 1%, 25%, 50%, 75%, 99%) and distributional fit (red line); (b) uncertainty of the proportion of pest-free plants per 10,000 (i.e. =1 – pest infestation proportion expressed as percentage); (c) descending uncertainty distribution function of pest infestation per 10,000 plants Movement and migration are hallmarks of animals. In the past years we have witnessed a technical revolution in animal tracking methods. The miniaturization of transmitters and sophistication of analytical software now make it possible to monitor movement patterns of individual insects. Růžičková & Elek review the current state-of-the-art of radio-tracking of beetles. Most reported studies still restrict to describing movement trajectories of individuals. However, processing movement patterns of multiple individuals can also be applied at a broader level, such as for the study of habitat use and population dynamics. Further technological innovations and automatization in insect tracking are expected to find their application in future studies of insect populations.

Between-day reliability of trunk orientation measured with smartphone sensors during sit-to-stand in asymptomatic individuals

BackgroundTrunk kinematics during sit-to-stand is often impaired in individuals with musculoskeletal disorders. Trunk kinematics is commonly assessed in laboratories using motion capture; however, this equipment is often not available outside research centers. Smartphones are widely available and may be a suitable alternative to assess trunk orientation during sit-to-stand remotely. ObjectivesWe investigated whether trunk orientation in the sagittal plane during sit-to-stand can be measured reliably between days when collected remotely using smartphones. DesignCross-sectional study. MethodForty-three asymptomatic participants performed 15 sit-to-stand movements in two separate sessions remotely over videoconferencing. Trunk orientation was measured using each participant's smartphone. Absolute peak trunk orientation in the sagittal plane was extracted during standing, sitting, stand up and sit down. Relative trunk orientation was calculated as the difference between sitting and stand up, or sitting and sit down. Reliability was assessed using Intraclass Correlation Coefficient (ICC2,k), Standard Error of Measurement (SEM) and Minimal Detectable change (MDC). Between day bias and between-gender differences were assessed using T tests. ResultsAll measures showed good reliability (ICC2,k > 0.80; SEM < 5.6°; MDC < 13.6°) and no between-day bias (p > 0.31). Relative measures were more consistent (ICC2,k > 0.88; SEM < 3.6°; MDC < 9.9°). No between-gender differences were observed for relative orientation (p > 0.75). ConclusionsSagittal trunk orientation during sitting, standing, and sit-to-stand can be measured reliably when asymptomatic individuals use their own smartphones supervised over videoconferencing. These findings support the use of smartphone sensors for assessing how trunk orientation changes over time, which may assist physiotherapists assess movement patterns of individuals with musculoskeletal disorders remotely.