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Load carriage experiments are typically performed from a linear perspective that assumes that movement variability is equivalent to error or noise in the neuromuscular system. A complimentary, nonlinear perspective that treats variability as the object of study has generated important results in movement science outside load carriage settings. To date, no systematic review has yet been conducted to understand how load carriage dynamics change from a nonlinear perspective. The goal of this systematic review is to fill that need. Relevant literature was extracted and reviewed for general trends involving nonlinear perspectives on load carriage. Nonlinear analyses that were used in the reviewed studies included sample, multiscale, and approximate entropy; the Lyapunov exponent; fractal analysis; and relative phase. In general, nonlinear tools successfully distinguish between unloaded and loaded conditions in standing and walking, although not in a consistent manner. The Lyapunov exponent and entropy were the most used nonlinear methods. Two noteworthy findings are that entropy in quiet standing studies tends to decrease, whereas the Lyapunov exponent in walking studies tends to increase, both due to added load. Thus, nonlinear analyses reveal altered load carriage dynamics, demonstrating promise in applying a nonlinear perspective to load carriage while also underscoring the need for more research.

The temporal structure of the variability of the stride-to-stride time intervals during paced walking is affected by the underlying autocorrelation function (ACF) of the pacing signal. This effect could be accounted for by differences in the underlying probability distribution function (PDF) of the pacing signal. We investigated the isolated and combined effect of the ACF and PDF of the pacing signals on the temporal structure of the stride-to-stride time intervals during visually guided paced overground walking. Ten young, healthy participants completed four walking trials while synchronizing their footstep to a visual pacing signal with a temporal pattern of either pink or white noise (different ACF) and either a Gaussian or normal probability distribution (different PDF). The scaling exponent from the Detrended Fluctuation Analysis was used to quantify the temporal structure of the stride-to-stride time intervals. The ACF and PDF of the pacing signals had independent effects on the scaling exponent of the stride-to-stride time intervals. The scaling exponent was higher during the pink noise pacing trials compared to the white noise pacing trials and higher during the trials with the Gaussian probability distribution compared to the uniform distribution. The results suggest that the sensorimotor system in healthy young individuals has an affinity towards external cues with a pink noise pattern and a Gaussian probability distribution during paced walking.

Social interactions are pervasive in human life with varying forms of interpersonal coordination emerging and spanning different modalities (e.g. behaviors, speech/language, and neurophysiology). However, during social interactions, as in any dynamical system, patterns of coordination form and dissipate at different scales. Historically, researchers have used aggregate measures to capture coordination over time. While those measures (e.g. mean relative phase, cross-correlation, coherence) have provided a wealth of information about coordination in social settings, some evidence suggests that multiscale coordination may change over the time course of a typical empirical observation. To address this gap, we demonstrate an underutilized method, windowed multiscale synchrony, that moves beyond quantifying aggregate measures of coordination by focusing on how the relative strength of coordination changes over time and the scales that comprise social interaction. This method involves using a wavelet transform to decompose time series into component frequencies (i.e. scales), preserving temporal information and then quantifying phase synchronization at each of these scales. We apply this method to both simulated and empirical interpersonal physiological and neuromechanical data. We anticipate that demonstrating this method will stimulate new insights on the mechanisms and functions of synchrony in interpersonal contexts using neurophysiological and behavioral measures.

Free-recall tasks suggest human memory foraging may follow a heavy-tailed distribution, such as a Lévy flight, patch foraging, or area-restricted search - walk procedures that are common in other activities of cognitive agents, such as food foraging in both animals and humans. To date, research merely equates memory foraging with hunting in the physical world based on similarities in statistical structure. The current work supports that memory foraging follows a heavy-tailed distribution by using categories with quantitative distances between each item: countries, which have physical distances, and animals, from which cognitive distances can be derived using a multidimensional scaling (MDS) procedure. Likewise, inter-item lag times follow a heavy-tailed distribution. The current work also demonstrates that inter-item distances and times are positively correlated, suggesting the organization of items in memory may be akin to the organization of a physical landscape. Finally, both studies show that participants' original, heavy-tailed lists of countries and animal names produce shorter overall distances traveled than random selection. Human memory foraging follows the same pattern as foraging in the natural world - perhaps because exposure to ecological settings informs our inner cognitive experience - leading to a processing and retrieval time benefit.

Variability is commonly observed in complex behavior, such as the maintenance of upright posture. The current study examines the value added by using nonlinear measures of variability to identify dynamic stability instead of linear measures that reflect average fluctuations about a mean state. The largest Lyapunov exponent (λ1) and SD were calculated on mediolateral movement as participants performed a sit-to-stand task on a stable and unstable platform. Both measures identified changes in movement across postures, but results diverged when participants stood on the unstable platform. Large SD indicated an increase in movement variability, but small λ1 identified those movements as stable and controlled. The results suggest that a combination of linear and nonlinear analyses is useful in identifying the proportion of observed variability that may be attributed to structured, controlled sources. Nonlinear measures of variability, like λ1, can further be used to make predictions about transitions between stable postures and to identify a system’s resistance to disruption from external perturbations. Those features make nonlinear analyses highly applicable to both human movement research and clinical practice.

Stochastic resonance has been successfully used to improve human movement when using subthreshold vibration. Recent work has shown promise in improving mobility in individuals with unilateral lower limb amputations. Furthering this work, we present an investigation of two different signal structures in the use of stochastic resonance to improve mobility in individuals with unilateral lower limb amputations. Cutaneous somatosensation and standing balance measures using spatial and temporal analysis were assessed. There were no differences in the somatosensation measures, but differences in the temporal characteristics of the standing measures were seen with the various vibration structures when compared to no vibration, one of which suggesting mass may play an important role in determining who may or may not benefit from this intervention. Stochastic resonance employed with subthreshold vibration influences mobility in individuals with unilateral amputations, but the full direction and extent of influence is yet to be understood.

In the past, team coordination dynamics have been explored using nonlinear dynamical systems (NDS) methods, but the relationship between team coordination dynamics and team performance for all-human teams was assumed to be linear. The current study examines team coordination dynamics with an extended version of the NDS methods and assumes that its relationship with team performance for human-autonomy teams (HAT) is nonlinear. In this study, three team conditions are compared with the goals of better understanding how team coordination dynamics differ between all-human teams and HAT and how these dynamics relate to team performance and team situation awareness. Each condition was determined based on manipulation of the pilot role: in the first condition (synthetic) the pilot role was played by a synthetic agent, in the second condition (control) it was a randomly assigned participant, and in the third condition (experimenter) it was an expert who used a role specific coordination script. NDS indices revealed that synthetic teams were rigid, followed by experimenter teams, who were metastable, and control teams, who were unstable. Experimenter teams demonstrated better team effectiveness (i.e., better team performance and team situation awareness) than control and synthetic teams. Team coordination stability is related to team performance and team situation awareness in a nonlinear manner with optimal performance and situation awareness associated with metastability coupled with flexibility. This result means that future development of synthetic teams should address these coordination dynamics, specifically, rigidity in coordination.

The assessment of argumentative writing generally includes analyses of the specific linguistic and rhetorical features contained in the individual essays produced by students. However, researchers have recently proposed that an individual’s ability to flexibly adapt the linguistic properties of their writing may more accurately capture their proficiency. However, the features of the task, learner, and educational context that influence this flexibility remain largely unknown. The current study extends this research by examining relations between linguistic flexibility, reading comprehension ability, and feedback in the context of an automated writing evaluation system. Students (n = 131) wrote and revised six argumentative essays in an automated writing evaluation system and were provided both summative and formative feedback on their writing. Additionally, half of the students had access to a spelling and grammar checker that provided lower-level feedback during the writing period. The results provide evidence for the supposition that skilled writers demonstrate linguistic flexibility across the argumentative essays that they produce. However, analyses also indicate that lower-level feedback (i.e., spelling and grammar feedback) have little to no impact on the properties of students’ essays nor on their variability across prompts or drafts. Overall, the current study provides important insights into the role of flexibility in argumentative writing skill and develops a strong foundation on which to conduct future research and educational interventions.

Older adults and people suffering from neurodegenerative disease often experience difficulty controlling gait during locomotion, ultimately increasing their risk of falling. To combat these effects, researchers and clinicians have used metronomes as assistive devices to improve movement timing in hopes of reducing their risk of falling. Historically, researchers in this area have relied on metronomes with isochronous interbeat intervals, which may be problematic because normal healthy gait varies considerably from one step to the next. More recently, researchers have advocated the use of irregular metronomes embedded with statistical properties found in healthy populations. In this paper, we explore the effect of both regular and irregular metronomes on many statistical properties of interstride intervals. Furthermore, we investigate how these properties react to mechanical perturbation in the form of a halted treadmill belt while walking. Our results demonstrate that metronomes that are either isochronous or random metronome break down the inherent structure of healthy gait. Metronomes with statistical properties similar to healthy gait seem to preserve those properties, despite a strong mechanical perturbation. We discuss the future development of this work in the context of networked augmented reality metronome devices., This paper has been accepted for publication by the 18th IEEE Annual Consumer Communications & Networking Conference (CCNC). The copyright is with the IEEE

Biomechanics is a scientific discipline that studies the forces acting on a body and the effects they produce. In this paper, we bring together biomechanists and networking researchers to shed light into how research efforts in biomechanics, primarily related to the study of the human body, can be facilitated through networking and computing technologies, such as edge and cloud computing, Software Defined Networking, and Information-Centric Networking. We first present challenges related to networking and computing that biomechanists face today and we then describe how networking and computing technologies can address them. Finally, we identify directions for future networking research with a focus on biomechanics to facilitate and encourage interdisciplinary collaborations between biomechanists and networking researchers., Comment: Accepted for publication by the IEEE Communications Magazine

Research suggests that promoting metacognitive awareness can increase performance in, and learning from, intelligent tutoring systems (ITSs). The current work examines the effects of two metacognitive prompts within iSTART, a reading comprehension strategy ITS in which students practice writing quality self-explanations. In addition to comparing iSTART practice to a no-training control, those in the iSTART condition (n = 116) were randomly assigned to a 2 (performance threshold: off, on) × 2(self-assessment: off, on) design. The performance threshold notified students when their average self-explanation score was below an experimenter-set threshold and the self-assessment prompted students to estimate their self-explanation score on the current trial. Students who practiced with iSTART had higher posttest self-explanation scores and inference comprehension scores on a transfer test than students in the no training control, replicating previous benefits for iSTART. However, there were no effects of either metacognitive prompt on these learning outcomes. In-system self-explanation scores indicated that the metacognitive prompts were detrimental to performance relative to standard iSTART practice. This study did not find benefits of metacognitive prompts in enhancing performance during practice or after the completion of training. Such findings support the idea that improving reading comprehension strategies comes from deliberate practice with actionable feedback rather than explicit metacognitive supports.

The structure of the stride-to-stride time intervals during paced walking can be altered by the temporal pattern of the pacing cues, however, it is unknown if an altered probability distribution of these cues could also affect stride-to-stride time intervals. We investigated the effect of the temporal pattern and probability distribution of visual pacing cues on the temporal structure of the variability of the stride-to-stride time intervals during walking. Participants completed self-paced walking (SPW) and walking paced by visual cueing that had a temporal pattern of either pink noise presented with a normal distribution (PNND), shuffled pink noise presented with a normal distribution (SPNND), white noise presented with a normal distribution (WNND), and white noise presented with a uniform distribution (WNUD). The temporal structure of the stride-to-stride time intervals was quantified using the scaling exponent calculated from Detrended Fluctuation Analysis. The scaling exponent was higher during the SPW and PNND trials than during the SPNND, WNND and WNUD trials and it was lower during the WNUD trial compared to the SPNND trial. The results revealed that both the temporal pattern and the probability distribution of the visual pacing cues can affect the scaling exponent of the variability of the stride-to-stride time intervals. This information is fundamental in understanding how visual input is involved in the control of gait.

The common practice of standardizing foot placement in postural research and in clinical practice may serve to increase postural sway. The focus of this study was to investigate foot placement strategies in the tandem (anteroposterior, AP) and side-to-side (mediolateral, ML) stance in healthy adults. Foot placement was either experimenter-controlled or selected by the participant. Greater sway was observed for the AP stance than the ML stance, where sway was minimal. When foot placement was self-selected, participants recruited additional degrees of freedom by rotating both feet outward to expand the base of support; they narrowed their stance width in the AP stance only. Self-selection served to decrease AP sway for the AP stance and increase ML sway for both the AP and ML stances. A dynamical measure, the largest Lyapunov exponent, supported the finding that self-selection of foot placement serves to stabilize posture. The implication is that improvements in postural control were due primarily to self-selection of foot placement and not to adjustments in stance width. Experimental and perhaps clinical procedures should be revised to allow participants to self-select foot placement during postural tasks.

Researchers generally agree that perceived heaviness is based on the actions associated with unsupported holding. Psychophysical research has supported this idea, as has psychophysiological research connecting muscle activity to the perceptions of heaviness and effort. However, the role of muscle activity in the context of the resulting motions has not been investigated. In the present study, perceptions of heaviness were recorded along with the electromyogram (EMG) of the lifting muscle and peak acceleration of the lift. Consistent with predictions derived from Newton's Second Law of motion (Force=Mass × Acceleration), normal and illusory perceptions of heaviness were a function of the ratio of muscle activity to lifting acceleration. These results identify a psychophysiological mechanism for heaviness perception based on the forces and motions associated with unsupported holding.

Game-based environments frequently afford students the opportunity to exert agency over their learning paths by making various choices within the environment. The combination of log data from these systems and dynamic methodologies may serve as a stealth means to assess how students behave (i.e., deterministic or random) within these learning environments. The current work captures variations in students’ behavior patterns by employing two dynamic analyses to classify students’ sequences of choices within an adaptive learning environment. Random Walk analyses and Hurst exponents were used to classify students’ interaction patterns as random or deterministic. Forty high school students interacted with the game-based system, iSTART-ME, for 11-sessions (pretest, 8 training sessions, posttest, and a delayed retention test). Analyses revealed that students who interacted in a more deterministic manner also generated higher quality self-explanations during training sessions. The results point toward the potential for dynamic analyses such as random walk analyses and Hurst exponents to provide stealth assessments of students’ learning behaviors while engaged within a game-based environment.

Self-explanations are commonly used to assess on-line reading comprehension processes. However, traditional methods of analysis ignore important temporal variations in these explanations. This study investigated how dynamical systems theory could be used to reveal linguistic patterns that are predictive of self-explanation quality. High school students (n = 232) generated self-explanations while they read a science text. Recurrence Plots were generated to show qualitative differences in students' linguistic sequences that were later quantified by indices derived by Recurrence Quantification Analysis (RQA). To predict self-explanation quality, RQA indices, along with summative measures (i.e., number of words, mean word length, and type-token ration) and general reading ability, served as predictors in a series of regression models. Regression analyses indicated that recurrence in students' self-explanations significantly predicted human rated self-explanation quality, even after controlling for summative measures of self-explanations, individual differences, and the text that was read (R2 = 0.68). These results demonstrate the utility of RQA in exposing and quantifying temporal structure in student's self-explanations. Further, they imply that dynamical systems methodology can be used to uncover important processes that occur during comprehension.

Objective: We investigated cross-level effects, which are concurrent changes across neural and cognitive-behavioral levels of analysis as teams interact, between neurophysiology and team communication variables under variations in team training. Background: When people work together as a team, they develop neural, cognitive, and behavioral patterns that they would not develop individually. It is currently unknown whether these patterns are associated with each other in the form of cross-level effects. Method: Team-level neurophysiology and latent semantic analysis communication data were collected from submarine teams in a training simulation. We analyzed whether (a) both neural and communication variables change together in response to changes in training segments (briefing, scenario, or debriefing), (b) neural and communication variables mutually discriminate teams of different experience levels, and (c) peak cross-correlations between neural and communication variables identify how the levels are linked. Results: Changes in training segment led to changes in both neural and communication variables, neural and communication variables mutually discriminated between teams of different experience levels, and peak cross-correlations indicated that changes in communication precede changes in neural patterns in more experienced teams. Conclusion: Cross-level effects suggest that teamwork is not reducible to a fundamental level of analysis and that training effects are spread out across neural and cognitive-behavioral levels of analysis. Cross-level effects are important to consider for theories of team performance and practical aspects of team training. Application: Cross-level effects suggest that measurements could be taken at one level (e.g., neural) to assess team experience (or skill) on another level (e.g., cognitive-behavioral).

The list of psychological processes thought to exhibit fractal behavior is growing. Although some might argue that the seeming ubiquity of fractal patterns illustrates their significance, unchecked growth of that list jeopardizes their relevance. It is important to identify when a single behavior is and is not fractal in order to make meaningful conclusions about the processes underlying those patterns. The hypothesis tested in the present experiment is that fractal patterns reflect the enactment of control. Participants performed two steering tasks: steering on a straight track and steering on a circular track. Although each task could be accomplished by holding the steering wheel at a constant angle, steering around a curve may require more constant control, at least from a psychological standpoint. Results showed that evidence for fractal behavior was strongest for the circular track; straight tracks showed evidence of two scaling regions. We argue from those results that, going forward, the goal of the fractal literature should be to bring scaling behavior under experimental control.

Rhythmic coordination with stimuli and other people’s movements containing variable or unpredictable fluctuations might involve distinct processes: detecting the fluctuation structure and tuning to or matching the structure’s temporal complexity. This framework predicts that global tuning and local parameter adjustments (e.g., position, velocity or phase) can operate independently during coordination (Marmelat & Delignieres, 2012). Alternatively, we propose that complexity matching is a result of local phase adjustments during coordination (Delignieres & Marmelat, 2014; Torre, Varlet, & Marmelat, 2013). The current study examined this relationship in a rhythmic interpersonal coordination task. Dyads coordinated swinging pendulums that differed in their uncoupled frequencies (detuning). We predicted that frequency detuning would require increased local corrections to maintain the intended phase pattern (in phase). This was expected to yield a relative phase shift accompanied by a change in period complexity and matching. Experimental data and numerical modeling of the pendulum dynamics confirmed our predictions. Increased relative phase shifts occurred simultaneously with increased dissociation between individuals’ movement period complexity. This provided evidence that global complexity matching is intricately linked to local movement adjustments and is not a distinct coordination mechanism. These findings are considered with respect to dynamical and computational approaches to interpersonal coordination.

In this study, we investigated the degree to which the cognitive processes in which students engage during reading comprehension could be examined through dynamical analyses of their natural language responses to texts. High school students (n = 142) generated typed self-explanations while reading a science text. They then completed a comprehension test that measured their comprehension at both surface and deep levels. The recurrent patterns of the words in students' self-explanations were first visualized in recurrence plots. These visualizations allowed us to qualitatively analyze the different self-explanation processes of skilled and less skilled readers. These recurrence plots then allowed us to calculate recurrence indices, which represented the properties of these temporal word patterns. Results of correlation and regression analyses revealed that these recurrence indices were significantly related to the students' comprehension scores at both surface- and deep levels. Additionally, when combined with summative metrics of word use, these indices were able to account for 32% of the variance in students' overall text comprehension scores. Overall, our results suggest that recurrence quantification analysis can be utilized to guide both qualitative and quantitative assessments of students' comprehension.

Teamwork is a complex dynamic process that emerges from team member interaction. The dynamics provide a characterization of the team over time. The stability, flexibility, and resilience of team dynamics over various windows of time can change with experience, training, environmental perturbations, and technological intervention. Once patterns of team dynamics have been established for a particular team, anomalous dynamics can signify impending teamwork problems. Dynamical systems modeling has been applied to many physical and natural systems and has only recently been applied to teamwork. The panel that we have assembled has applied dynamical modeling to this problem from different perspectives and at different scales. Each panelist will overview his or her approach to this problem. We will then discuss pros and cons of each approach and possibilities for using them in a complementary fashion.

Metacognitive awareness has been shown to be a critical skill for academic success. However, students often struggle to regulate this ability during learning tasks. The current study investigates how features designed to promote metacognitive awareness can be built into the game-based intelligent tutoring system (ITS) iSTART-2. College students (n=28) interacted with iSTART-2 for one hour, completing lesson videos and practice activities. If students’ performance fell below a minimum threshold during game-based practice, they received a pop-up that alerted them of their poor performance and were subsequently transitioned to a remedial activity. Results revealed that students’ scores in the system improved after they were transitioned (even when they did not complete the remedial activity). This suggests that the pop-up feature in iSTART-2 may indirectly promote metacognitive awareness, thus leading to increased performance. These results provide insight into the potential benefits of real-time feedback designed to promote metacognitive awareness within a game-based learning environment.

Project overview. The current study focuses on the nature of team coordination dynamics within all-human teams and Human-Autonomy Teams (HAT) in the context of the development of a fully-fledged synthetic agent that is a computational cognitive model for a three-agent Unmanned Aircraft System (UAS) ground crew. In this study, the relationship between team coordination dynamics and team performance within the HAT and all-human teams is considered. To serve as a teammate, the synthetic agent must be able to communicate and coordinate with its human teammates in a constructive and timely manner (Demir, McNeese, & Cooke, 2016). In this current research, there were three heterogeneous team members who communicated via a text-based communication system to photograph target waypoints. Each team member had a different role: (1) navigator – provides information regarding a flight plan with speed and altitude restrictions of each waypoint; (2) pilot – controls the UAS by adjusting its altitude and airspeed by negotiating with the photographer to take a good photo for the target waypoints; and (3) photographer – screens camera settings, and sends feedback to the other team members regarding the status of target’s photograph. At each target waypoint, this coordination sequence among the team members, called Information-Negotiation-Feedback (INF), is captured by a Kappa Score (Gorman, Amazeen, & Cooke, 2010) that describes the sequence and timing of the information coordination. Three conditions were created that manipulated the pilot role: (1) Synthetic – pilot was the synthetic agent, (2) Control – pilot was a randomly assigned participant, and (3) Experimenter – pilot was an experimenter who was highly experienced with the task and focused on pushing and pulling the information in a timely manner. Method. In this experiment, there were 30 teams (ten teams for each condition): control teams were composed of three participants randomly assigned to each role; synthetic and experimenter teams were composed of only two participants randomly assigned to the navigator and photographer roles. The experiment consisted of five missions (each 40 minutes) in which teams needed to take as many “good” photos as possible of ground targets while avoiding alarms and rule violations. Several measures were obtained from this research, including team performance scores (mission and target level), team process measures (situation awareness, process ratings, communication and coordination), and other measures (teamwork knowledge, workload, and demographics). The research reported here identifies how differences in team coordination, captured by Kappa, relate to performance of all human teams and HAT teams. In this paper, we focus on: (1) target level team performance scores calculated based on the time spent inside a target waypoint to get a good photo; and (2) two team coordination dynamics measures: stability and team communication determinism. Stability was inversely related to the largest Lyapunov Exponent which was estimated by Kappa, that is, the INF coordination sequence. Team communication determinism was estimated from communication data using Joint Recurrence Quantification Analysis (Marwan, Carmen, Thiel, & Kurths, 2007) and served as an index of flexible behavior. Results and discussion. In general, findings indicate that (1) synthetic teams were most stable, followed by experimenter teams, who were moderately stable, and control teams, who were least stable; and (2) extreme stability and instability corresponded to lower levels of performance; experimenter teams performed best, followed by control teams and, then synthetic teams. Thus, synthetic agents could be made more effective if interventions were developed to enhance the flexibility and adaptive nature of HATs (Demir, 2017).

The quality of a team depends on its ability to deliver information through a hierarchy of team members and negotiate processes spanning different time scales. That structure and the behavior that results from it pose problems for researchers because multiply-nested interactions are not easily separated. We explored the behavior of a six-person team engaged in a Submarine Piloting and Navigation (SPAN) task using the tools of dynamical systems. The data were a single entropy time series that showed the distribution of activity across six team members, as recorded by nine-channel electroencephalography (EEG). A single team's data were analyzed for the purposes of illustrating the utility of multifractal analysis and allowing for in-depth exploratory analysis of temporal characteristics. Could the meaningful events experienced by one of these teams be captured using multifractal analysis, a dynamical systems tool that is specifically designed to extract patterns across levels of analysis? Results indicate that nested patterns of team activity can be identified from neural data streams, including both routine and novel events. The novelty of this tool is the ability to identify social patterns from the brain activity of individuals in the social interaction. Implications for application and future directions of this research are discussed.