Gait Tasks Research Articles

Ankle-hip joint trade-off in normal gait: Exploring the kinematic influence of the medial longitudinal arch of the foot

BackgroundIn human gait, leg progression into the swing phase involves two primary strategies: ankle plantar flexion and hip flexion. These strategies are believed to exhibit a trade-off relationship; however, it is unclear whether this relationship holds for normal gait and the role of the medial longitudinal arch (MLA) in shaping these strategies. Research questionsDoes a trade-off relationship exist between ankle plantar flexion and hip flexion strategies during normal gait in young healthy adults? Do the kinematics of MLA during gait influence the strategies during leg progression into the swing phase? MethodsData from 36 young healthy adults were analyzed. Gait speed and peak moment, angular impulse, peak power and joint work at ankle plantar flexion and hip flexion were assessed within the context of the normal gait task. The parameters were also assessed using ankle-to-hip joint ratios (ankle/hip indices). Kinematics of MLA, including peak MLA angle, amount of descent, and amount of elevation during gait, were also measured. To exclude the effect of gait speed, partial correlation coefficients were employed to explore the relationship between ankle and hip variables as well as the ratio of ankle/hip indices and MLA kinematics. ResultsA significant negative correlation between ankle plantar flexion work and hip flexion work was detected. Moreover, a positive correlation between the ankle plantar flexion work to hip flexion work ratio and MLA elevation was detected. SignificanceA trade-off relationship between ankle plantar flexion and hip flexion strategies during normal gait in young healthy adults was confirmed, suggesting that these parameters are fundamental to normal gait. Additionally, the MLA elevation during late stance may influence the establishment of ankle plantar flexion and hip flexion strategies. These findings enhance our understanding of gait mechanisms and highlight the role of MLA kinematics in shaping gait strategies.

Gait abnormalities and longitudinal fall risk in older patients with end-stage kidney disease and sarcopenia

BackgroundSarcopenia, gait disturbance, and intradialytic hypotension are among the various factors that contribute to fall risk. This study aimed to investigate the relationship between risk of sarcopenia, hemodialysis (HD) session, and long-term fall risk in older end-stage kidney disease (ESKD) patients by analyzing their spatiotemporal gait characteristics.MethodsWe recruited 22 non-demented patients aged ≥ 65 years who were undergoing maintenance HD. Participants were divided into two groups based on their SARC-F score (< 4 and ≥ 4) to identify those with higher and lower risk of sarcopenia. Demographics, comorbidities, and renal parameters were compared between groups. Inertial measurement unit-based technology equipped with triaxial accelerometry and gyroscope was used to evaluate gait characteristics. The gait task was assessed both before and after dialysis using the Timed-Up and Go (TUG) test and a 10-meter walking test at a regular pace. Essential gait parameters were thoroughly analyzed, including gait speed, stride time, stride length, double-support phase, stability, and symmetry. We investigated the interaction between the dialysis procedure and gait components. Outcome of interest was any occurrence of injurious fall during follow-up period. Logistic regression models were employed to examine the relationship between baseline gait markers and long-term fall risk.ResultsThe SARC-F ≥ 4 group showed various gait abnormalities, including longer TUG time, slower gait speed, longer stride time, shorter stride length, and longer double support time compared to counterpart (SARC-F < 4). After HD sessions, the SARC-F ≥ 4 group showed a 2.0-second decrease in TUG task time, an 8.0 cm/s increase in gait speed, an 11.6% lower stride time, and a 2.4% increase in gait symmetry with significant group-time interactions. Shorter stride length and longer double support time were associated with injurious falls during the two-year follow-up.ConclusionOur study demonstrated the utility of triaxial accelerometers in extracting gait characteristics in older HD patients. High-risk sarcopenia (SARC-F ≥ 4) was associated with various gait abnormalities, some of which partially improved after HD sessions. These gait abnormalities were predictive of future falls, highlighting their prognostic significance.

Validation of a 3D Markerless Motion Capture Tool Using Multiple Pose and Depth Estimations for Quantitative Gait Analysis.

Gait analysis is essential for evaluating walking patterns and identifying functional limitations. Traditional marker-based motion capture tools are costly, time-consuming, and require skilled operators. This study evaluated a 3D Marker-less Motion Capture (3D MMC) system using pose and depth estimations with the gold-standard Motion Capture (MOCAP) system for measuring hip and knee joint angles during gait at three speeds (0.7, 1.0, 1.3 m/s). Fifteen healthy participants performed gait tasks which were captured by both systems. The 3D MMC system demonstrated good accuracy (LCC > 0.96) and excellent inter-session reliability (RMSE < 3°). However, moderate-to-high accuracy with constant biases was observed during specific gait events, due to differences in sample rates and kinematic methods. Limitations include the use of only healthy participants and limited key points in the pose estimation model. The 3D MMC system shows potential as a reliable tool for gait analysis, offering enhanced usability for clinical and research applications.

Gait Speed and Task-Specificity in Predicting Lower-Limb Kinematics: A Deep Learning Approach Using Inertial Sensors

ObjectiveTo develop a deep-learning framework to predict lower-limb joint kinematics from IMU data across multiple gait tasks (walking, jogging, and running) and evaluate the impact of dynamic time warping (DTW) on reducing prediction errors. Patients and MethodsData were collected from 18 participants fitted with IMUs and an optical motion capture (OMC) system between May 25, 2023, to May 30, 2023. A long-short-term memory (LSTM) autoencoder supervised regression model was developed. The model consisted of multiple LSTM and convolution layers. Acceleration and gyroscope data from the IMUs in three axes and their magnitude for the proximal and distal sensors of each joint (hip, knee, ankle) were inputs to the model. OMC kinematics were considered ground truth and used as an output to train the prediction model. ResultsThe deep-learning models achieved a root mean square error (RMSE) of less than 6° for hip, knee, and ankle joint sagittal plane angles, with the ankle showing the lowest error (5.1°). Task-specific models demonstrated enhanced performance during certain gait phases, such as knee flexion during running. The application of DTW significantly reduced RMSE across all tasks by at least 3-4°. External validation of independent data confirmed the model’s generalizability. ConclusionOur findings underscore the potential of IMU-based deep-learning models for joint kinematic predictions, offering a practical solution for remote and continuous biomechanical assessments in healthcare and sports science.

Do sensorimotor insoles improve gait safety in patients with Parkinson’s disease on a short scale?

IntroductionParkinson’s disease (PD) often leads to gait abnormalities, increasing the risk of falls and affecting daily life. Sensorimotor insoles aim to enhance foot sensitivity, potentially improving gait stability. MethodsThis study examined whether there are short-term effects of sensorimotor insoles on neural activation (measured by EEG), kinematic gait parameters (speed, cadence, step length, and step-length variability), and subjective gait stability in PD patients. Sixteen individuals suffering from PD completed a gait task while wearing sensorimotor and placebo insoles, respectively. ResultsThe results showed no significant changes in kinematic parameters with the sensorimotor insoles. Subjective ratings of gait stability and attentional control of gait improved on average with the sensorimotor insoles, but again did not reach statistical significance. There was no significant reduction in alpha-band activity, indicating no improvement in sensorimotor processing. ConclusionThe immediate impact of sensorimotor insoles on sensorimotor processing and gait characteristics in PD patients remains inconclusive. The small sample size limited the statistical power, highlighting the need for larger studies to comprehensively assess efficacy. Further research should investigate the long-term effects and potential benefits on disability measures in PD patients.

Evaluation of a finite state machine algorithm to measure stepping with ankle accelerometry: Performance across a range of gait speeds, tasks, and individual walking ability

Wearable sensors, including accelerometers, are a widely accepted tool to assess gait in clinical and free-living environments. Methods to identify phases and subphases of the gait cycle are necessary for comprehensive assessment of pathological gait. The current study evaluated the accuracy of a finite state machine (FSM) algorithm to detect strides by identifying gait cycle subphases from ankle-worn accelerometry. Algorithm performance was challenged across a range of speeds (0.4-2.6 m/s), task conditions (e.g., single- and dual-task walking), and individual characteristics. Specifically, the study included a range of treadmill speeds in young adults and overground walking conditions in older adults with neurological disease. Manually counted and algorithm-derived stride detection from acceleration data were evaluated using error analysis and Bland-Altman plots for visualization. Overall, the algorithm successfully detected strides (>96 % accuracy) across gait speed ranges and tasks, for young and older adults. The accuracy of an FSM algorithm combined with ankle-worn accelerometers, provides an analytical approach with affordable and portable tools that permits comprehensive assessment of gait unbounded by setting and proves to perform well in in walking tasks characterized by variable walking. These algorithm capabilities and advancements are critical for identifying phase dependent gait impairments in clinical and free-living assessment.

Dual-task performance during the Timed Up and Go test in Parkinson's disease - the impact of freezing and cognition

BackgroundDual-task interference (DTI) on gait is well documented in Parkinson’s disease (PD), but how dual-tasks affect functional mobility is less known. Understanding how cognition and freezing of gait (FOG) further impact dual-task ability is important for risk assessment and subsequent delivery of targeted rehabilitation. Research questionWhat is the DTI on completion time of the Timed Up and Go, and DTI on response rate of a serial subtraction task when performed simultaneously, and is DTI impacted by FOG or cognition? MethodsA cross-sectional study design was used. Demographic and clinical characteristics of participants were collected, including global cognition and self-reported FOG. The TUG test was performed with and without a serial subtraction task. Completion times on TUG and response rates on the serial subtraction task was compared between single and dual-task performance using paired samples t-test or Wilcoxon signed rank test as appropriate. Prioritization between tasks was compared with one-sample Wilcoxon signed rank test. The impact of FOG and cognition was investigated with multiple linear regression, controlling for age, sex, and disease severity. ResultsA total of 77 people with mild to moderate PD were included. Significant DTI was observed for both the gait (TUG) and cognitive (response rate) tasks. No statistically significant pattern of prioritization was observed between motor and cognitive tasks. Global cognition was significantly related to both completion time and response rate in single and dual-tasking, whereas FOG was not found to be associated to the outcomes in either condition. SignificanceCognition appears to significantly relate to performance of functional mobility in single and dual-task conditions, which should be considered during routine mobility assessments in people with PD.

The Ramp protocol: Uncovering individual differences in walking to an auditory beat using TeensyStep

Intentionally walking to the beat of an auditory stimulus seems effortless for most humans. However, studies have revealed significant individual differences in the spontaneous tendency to synchronize. Some individuals tend to adapt their walking pace to the beat, while others show little or no adjustment. To fill this gap we introduce the Ramp protocol, which measures spontaneous adaptation to a change in an auditory rhythmic stimulus in a gait task. First, participants walk at their preferred cadence without stimulation. After several steps, a metronome is presented, timed to match the participant’s heel-strike. Then, the metronome tempo progressively departs from the participant’s cadence by either accelerating or decelerating. The implementation of the Ramp protocol required real-time detection of heel-strike and auditory stimuli aligned with participants’ preferred cadence. To achieve this, we developed the TeensyStep device, which we validated compared to a gold standard for step detection. We also demonstrated the sensitivity of the Ramp protocol to individual differences in the spontaneous response to a tempo-changing rhythmic stimulus by introducing a new measure: the Response Score. This new method and quantification of spontaneous response to rhythmic stimuli holds promise for highlighting and distinguishing different profiles of adaptation in a gait task.

Associations between dual-task walking and cognitive impairment in people attending a cognitive diagnostic clinic.

Dual-task walking performance is an early marker of dementia. However, there is uncertainty about which measure of the dual-task test is a better marker. The objective of this study was to determine which dual-task measure best differentiates between normal cognition, mild cognitive impairment (MCI) and dementia. Participants (n = 116) were aged ≥60 years attending a cognitive clinic in Melbourne, Australia. Single- and dual-task gait speed were obtained using a 16 metre distance and stopwatch. The cognitive task involved reciting alternate letters of the alphabet sitting and walking. Dual-task interference in gait and cognition was calculated as: single-task-dual-task/single task × 100 and summed to obtain total interference. Multiple linear regression was used to determine differences in single and dual-task measures between those with no cognitive impairment (n = 11), MCI (n = 54) and dementia (n = 51). The mean age of the sample was 76.9 (SD 6.4) years and 48.3% (n = 56) were female. Compared to those with dementia: (a) those with MCI had a higher dual-task letter rate and lower cognitive and total interference (all indicate better performance) (p < .05) and (b) those with no cognitive impairment had a higher single- and dual-task letter rate (both indicate better performance) (p < .05). There were no differences between those with no cognitive impairment and those with MCI (all p > .05). In a cognitive clinic, measurement during dual-task walking differentiated those with dementia from those with MCI or no cognitive impairment. However, differences appear to be driven by performance on the cognitive, rather than the gait task.

Effect of Blood Flow Restriction on Gait and Mobility in Older Adults: A Systematic Review and Meta-Analysis.

Older adults demonstrate gait impairments that increase their risk for falls. These age-related mobility impairments are in part due to declines in muscle mass and strength. High-intensity exercise can improve muscle strength and mobility but may not be tolerable for older adults due to musculoskeletal injury and pain. Blood flow restriction (BFR) with lower-intensity exercise offers a strategy that may be more tolerable for older adults, but whether BFR improves gait and mobility in older adults is unclear. The purpose of this systematic review and meta-analysis was to determine the effect of BFR on gait and mobility in healthy older adults. PubMed, Embase, Cochrane Library, and CINAHL were systematically searched for articles utilizing BFR in older adults. Articles were included if adults were over 60 years, did not have chronic health conditions, had undergone randomized controlled trials, and presented objectively measured gait outcomes. The search identified 1501 studies, of which 9 were included in the systematic review and 8 studies in the meta-analysis. Outcome measures included the Timed Up and Go (TUG), 6-Minute Walk Test (6MWT), 400 m walk test, Short Physical Performance Battery (SPPB), and 10 m walk test. Meta-analyses found improvements in the TUG (mean difference (MD) = -0.71; 95% CI = -1.05, -0.37; p < 0.001) and SPPB (MD = -0.94; 95% CI = -1.48, -0.39; p < 0.001) in BFR compared to no BFR. There were no differences in gait speed (MD = 0.59; 95% CI = -0.22, 1.41; p = 0.16). BFR may be effective for gait and mobility tasks over shorter distances. Clinicians may consider incorporating BFR to improve mobility and gait function in older adults.

Spatiotemporal Gait Characteristics and Neuropsychological Performance in Midlife

Abstract Background Midlife risk factors such as Type 2 Diabetes Mellitus (T2DM) confer a significantly increased risk of cognitive impairment in later life, with executive function, memory and attention domains often affected first. Spatiotemporal gait characteristics are increasingly recognised as biomarkers of neurocognitive function and later dementia risk. Methods Using an automated walkway, 24 spatiotemporal gait parameters were examined across 5 domains of gait previously linked to cognitive function on usual-pace, maximal-pace, and cognitive dual-task gait conditions. Neurocognitive function was measured using a neuropsychological assessment battery. Linear regression was used assess the relationship between each gait parameter across the three walks and cognitive function. Results 102 middle-aged adults underwent assessment, 65 with uncomplicated T2DM (57.5 ± 8.0 years; 40% female) and 37 healthy controls (57.0 ± 8.3 years; 62.1% female). T2DM was associated with significant changes in gait phases and rhythm domains at usual-pace, and greater gait variability observed during maximal-pace and dual-task. In the overall cohort, both gait pace and rhythm domains were associated with memory and executive function during usual pace walking. At maximal-pace, gait pace parameters were associated with reaction time and delayed memory. During the cognitive dual-task, associations between gait variability and delayed memory and executive function were observed. Associations persisted following covariate adjustment and did not differ by T2DM status. Conclusion This supports the use of spatiotemporal gait as an integrative biomarker of neurocognitive function in otherwise healthy middle-aged individuals. Discrete associations were seen between both differing gait tasks and gait domains with domain-specific neuropsychological performance. Employing both maximal-pace and dual-task paradigms, in addition to single-task usual-pace gait, may be important in cognitively unimpaired populations with risk factors for later cognitive decline - with the aim of identifying individuals who may benefit most from potential preventative interventions.

Which Gait Tasks Produce Reliable Outcome Measures of Freezing of Gait in Parkinson's Disease?

Measurement of freezing of gait (FOG) relies on the sensitivity and reliability of tasks to provoke FOG. It is currently unclear which tasks provide the best outcomes and how medication state plays into this. To establish the sensitivity and test-retest reliability of various FOG-provoking tasks for presence and severity of FOG, with (ON) and without (OFF) dopaminergic medication. FOG-presence and percentage time frozen (% TF) were derived from video annotations of a home-based FOG-provoking protocol performed in OFF and ON. This included: the four meter walk (4MW), Timed Up and Go (TUG) single (ST) and dual task (DT), 360° turns in ST and DT, a doorway condition, and a personalized condition. Sensitivity was tested at baseline in 63 definite freezers. Test-retest reliability was evaluated over 5 weeks in 26 freezers. Sensitivity and test-retest reliability were highest for 360° turns and higher in OFF than ON. Test-retest intra-class correlation coefficients of % TF varied between 0.63-0.90 in OFF and 0.18-0.87 in ON, and minimal detectable changes (MDCs) were high. The optimal protocol included TUG ST, 360° turns ST, 360° turns DT and a doorway condition, provoking FOG in all freezers in OFF and 91.9% in ON and this could be done reliably in 95.8% (OFF) and 84.0% (ON) of the sample. Combining OFF and ON further improved outcomes. The highest sensitivity and reliability was achieved with a multi-trigger protocol performed in OFF + ON. However, the high MDCs for % TF underscore the need for further optimization of FOG measurement.

Implicit learning provides advantage over explicit learning for gait-cognitive dual-task interference

Dual-task performance holds significant relevance in real-world scenarios. Implicit learning is a possible approach for improving dual-task performance. Analogy learning, utilizing a single metaphor to convey essential information about motor skills, has emerged as a practical method for fostering implicit learning. However, evidence supporting the effect of implicit learning on gait-cognitive dual-task performance is insufficient. This exploratory study aimed to examine the effects of implicit and explicit learning on dual-task performance in both gait and cognitive tasks. Tandem gait was employed on a treadmill to assess motor function, whereas serial seven subtraction tasks were used to gauge cognitive performance. Thirty healthy community-dwelling older individuals were randomly assigned to implicit or explicit learning groups. Each group learned the tandem gait task according to their individual learning styles. The implicit learning group showed a significant improvement in gait performance under the dual-task condition compared with the explicit learning group. Furthermore, the implicit learning group exhibited improved dual-task interference for both tasks. Our findings suggest that implicit learning may offer greater advantages than explicit learning in acquiring autonomous motor skills. Future research is needed to uncover the mechanisms underlying implicit learning and to harness its potential for gait-cognitive dual-task performance in clinical settings.

Improving Task-Agnostic Energy Shaping Control of Powered Exoskeletons with Task/Gait Classification.

Emerging task-agnostic control methods offer a promising avenue for versatile assistance in powered exoskeletons without explicit task detection, but typically come with a performance trade-off for specific tasks and/or users. One such approach employs data-driven optimization of an energy shaping controller to provide naturalistic assistance across essential daily tasks with passivity/stability guarantees. This study introduces a novel control method that merges energy shaping with a machine learning-based classifier to deliver optimal support accommodating diverse individual tasks and users. The classifier detects transitions between multiple tasks and gait patterns in order to employ a more optimal, task-agnostic controller based on the weighted sum of multiple optimized energy-shaping controllers. To demonstrate the efficacy of this integrated control strategy, an in-silico assessment is conducted over a range of gait patterns and tasks, including incline walking, stairs ascent/descent, and stand-to-sit transitions. The proposed method surpasses benchmark approaches in 5-fold cross-validation ( ), yielding 93.17 ± 7.39% cosine similarity and 77.92 ± 19.76% variance-accounted-for across tasks and users. These findings highlight the control approach's adaptability in aligning with human joint moments across various tasks.

Trunk Instability in the Pitch, Yaw, and Roll Planes during Clinical Balance Tests: Axis Differences and Correlations to vHIT Asymmetries Following Acute Unilateral Vestibular Loss.

Clinical dynamic posturography concentrates on the pitch and roll but not on the yaw plane instability measures. This emphasis may not represent the axis instability observed in clinical stance and gait tasks for patients with balance deficits in comparison to healthy control (HC) subjects, nor the expected instability based on correlations with vestibulo-ocular reflex (VOR) deficits. To examine the axis stability changes with vestibular loss, we measured trunk sway in all three directions (pitch, roll, and yaw) during the stance and gait tasks of patients with acute unilateral vestibular neuritis (aUVN) and compared the results with those of HC. Concurrent changes in VORs were also examined and correlated with trunk balance deficits. The results of 11 patients (mean age of 61 years) recorded within 6 days of aUVN onset were compared within those of 8 age-matched healthy controls (HCs). All subjects performed a two-legged stance task-standing with eyes closed on foam (s2ecf), a semi-gait task-walking eight tandem steps (tan8), and four gait tasks-walking 3 m with head rotating laterally, pitching, or eyes closed (w3hr, w3hp, w3ec), and walking over four barriers 24 cm high, spaced 1 m apart (barr). The tasks' peak-to-peak yaw, pitch and roll angles, and angular velocities were measured with a gyroscope system (SwayStarTM) mounted at L1-3 and combined into three, axis-specific, balance control indexes (BCI), using angles (a) for the tandem gait and barriers task, and angular velocities (v) for all other tasks, as follows: axis BCI = (2 × 2ecf)v + 1.5 × (w3hr + w3hp + w3ec)v + (tan8 + 12 × barr)a. Yaw and pitch BCIs were significantly (p ≤ 0.004) greater (88 and 30%, respectively) than roll BCIs for aUVN patients. For HCs, only yaw but not pitch BCIs were greater (p = 0.002) than those of roll (72%). The order of BCI aUVN vs. HC differences was pitch, yaw, and roll at 55, 44, and 31%, respectively (p ≤ 0.002). This difference with respect to roll corresponded to the known greater yaw plane than roll plane asymmetry (40 vs. 22%) following aUVN based on VOR responses. However, the lower pitch plane asymmetry (3.5%) in VOR responses did not correspond with the pitch plane instability observed in the balance control tests. The increases in pitch plane instability in UVL subjects were, however, highly correlated with those of roll and yaw. These results indicate that greater yaw than pitch and roll trunk motion during clinical balance tasks is common for aUVN patients and HCs. However, aUVN leads to a larger increase in pitch than yaw plane instability and a smaller increase in roll plane instability. This difference with respect to roll corresponds to the known greater yaw plane than roll plane asymmetry (40 vs. 22%) following aUVN observed in VOR responses. However, the lower pitch plane asymmetry (3.5%) in VOR responses does not correspond with the enhanced movements in the pitch plane, observed in balance control tasks. Whether asymmetries in vestibular-evoked myogenic potentials (Vemps) are better correlated with the deficits in pitch plane balance control remains to be investigated. The current results provide a strong rationale for the clinical testing of directional specific balance responses, especially yaw and pitch, and the linking of balance results for yaw and roll to VOR asymmetries.

Enhancing fall risk assessment: instrumenting vision with deep learning during walks

BackgroundFalls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual’s gait during scripted walking protocols within a lab to identify deficits that potentially increase fall risk, but subtle deficits may not be (readily) observable. Therefore, objective approaches (e.g., inertial measurement units, IMUs) are useful for quantifying high resolution gait characteristics, enabling more informed fall risk assessment by capturing subtle deficits. However, IMU-based gait instrumentation alone is limited, failing to consider participant behaviour and details within the environment (e.g., obstacles). Video-based eye-tracking glasses may provide additional insight to fall risk, clarifying how people traverse environments based on head and eye movements. Recording head and eye movements can provide insights into how the allocation of visual attention to environmental stimuli influences successful navigation around obstacles. Yet, manual review of video data to evaluate head and eye movements is time-consuming and subjective. An automated approach is needed but none currently exists. This paper proposes a deep learning-based object detection algorithm (VARFA) to instrument vision and video data during walks, complementing instrumented gait.MethodThe approach automatically labels video data captured in a gait lab to assess visual attention and details of the environment. The proposed algorithm uses a YoloV8 model trained on with a novel lab-based dataset.ResultsVARFA achieved excellent evaluation metrics (0.93 mAP50), identifying, and localizing static objects (e.g., obstacles in the walking path) with an average accuracy of 93%. Similarly, a U-NET based track/path segmentation model achieved good metrics (IoU 0.82), suggesting that the predicted tracks (i.e., walking paths) align closely with the actual track, with an overlap of 82%. Notably, both models achieved these metrics while processing at real-time speeds, demonstrating efficiency and effectiveness for pragmatic applications.ConclusionThe instrumented approach improves the efficiency and accuracy of fall risk assessment by evaluating the visual allocation of attention (i.e., information about when and where a person is attending) during navigation, improving the breadth of instrumentation in this area. Use of VARFA to instrument vision could be used to better inform fall risk assessment by providing behaviour and context data to complement instrumented e.g., IMU data during gait tasks. That may have notable (e.g., personalized) rehabilitation implications across a wide range of clinical cohorts where poor gait and increased fall risk are common.

The use of nonlinear analysis in understanding postural control: A scoping review

Nonlinear analyses have emerged as an approach to unraveling the intricate dynamics and underlying mechanisms of postural control, offering insights into the complex interplay of physiological and biomechanical factors. However, achieving a comprehensive understanding of the application of nonlinear analysis in postural control studies remains a challenge due to the various nonlinear measurement methods currently available. Thus, this scoping review aimed to identify existing nonlinear analyses used to study postural control in both dynamic and quiet tasks, and to summarize and disseminate the available literature on the use of nonlinear analysis in postural control. For this purpose, a scoping review was conducted and reported following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) Checklist and Explanation. Searches were conducted up to July 2023 on PubMed/Medline, Embase, CINAHL, Web of Science, and Google Scholar databases, resulting in the inclusion of 397 unique studies. The main classes employed among the studies were entropy-based, fractal-based, quantification of recurrence plots, and quantification of stability, with a total of 91 different algorithms distributed among these classes. The most common condition used to study postural control was quiet standing, followed by dynamic standing and gait tasks. Although various algorithms were utilized for this purpose, sample entropy was employed in 43% of studies to explore mechanisms related to postural control. Among them, 28% were in quiet standing, 3.27% were in dynamic standing, and 4.78% to study postural control during the gait. The results also provide insights into nonlinear analysis for future studies, concerning the complexity and interactions within the postural control system across various task demands.

Discrete Relationships between Spatiotemporal Gait Characteristics and Domain-Specific Neuropsychological Performance in Midlife.

Midlife risk factors such as type 2 diabetes mellitus (T2DM) confer a significantly increased risk of cognitive impairment in later life with executive function, memory, and attention domains often affected first. Spatiotemporal gait characteristics are emerging as important integrative biomarkers of neurocognitive function and of later dementia risk. We examined 24 spatiotemporal gait parameters across five domains of gait previously linked to cognitive function on usual-pace, maximal-pace, and cognitive dual-task gait conditions in 102 middle-aged adults with (57.5 ± 8.0 years; 40% female) and without (57.0 ± 8.3 years; 62.1% female) T2DM. Neurocognitive function was measured using a neuropsychological assessment battery. T2DM was associated with significant changes in gait phases and rhythm domains at usual pace, and greater gait variability observed during maximal pace and dual tasks. In the overall cohort, both the gait pace and rhythm domains were associated with memory and executive function during usual pace. At maximal pace, gait pace parameters were associated with reaction time and delayed memory. During the cognitive dual task, associations between gait variability and both delayed memory/executive function were observed. Associations persisted following covariate adjustment and did not differ by T2DM status. Principal components analysis identified a consistent association of slower gait pace (step/stride length) and increased gait variability during maximal-pace walking with poorer memory and executive function performance. These data support the use of spatiotemporal gait as an integrative biomarker of neurocognitive function in otherwise healthy middle-aged individuals and reveal discrete associations between both differing gait tasks and gait domains with domain-specific neuropsychological performance. Employing both maximal-pace and dual-task paradigms may be important in cognitively unimpaired populations with risk factors for later cognitive decline-with the aim of identifying individuals who may benefit from potential preventative interventions.

The effect of visual sensory interference during multitask obstacle crossing in younger and older adults.

When older adults step over obstacles during multitasking, their performance is impaired; the impairment results from central and/or sensory interference. The purpose was to determine if sensory interference alters performance under low levels of cognitive, temporal, and gait demand, and if the change in performance is different for younger versus older adults. Participants included 17 younger adults (20.9±1.9 years) and 14 older adults (69.7±5.4 years). The concurrent task was a single, simple reaction time (RT) task: depress button in response to light cue. The gait task was stepping over an obstacle (8 m walkway) in three conditions: (1) no sensory interference (no RT task), (2) low sensory interference (light cue on obstacle, allowed concurrent foveation of cue and obstacle), or (3) high sensory interference (light cue away from obstacle, prevented concurrent foveation of cue and obstacle). When standing, the light cue location was not relevant (no sensory interference). An interaction (sensory interference by task, p<0.01) indicated that RT was longer for high sensory interference during walking, but RT was not altered for standing, confirming that sensory interference increased RT during obstacle approach. An interaction (sensory interference by age, p<0.01) was observed for foot placement before the obstacle: With high sensory interference, younger adults placed the trail foot closer to the obstacle while older adults placed it farther back from the obstacle. The change increases the likelihood of tripping with the trail foot for younger adults, but with the lead limb for older adults. Recovery from a lead limb trip is more difficult due to shorter time for corrective actions. Overall, visual sensory interference impaired both RT and gait behavior with low levels of multitask demand. Changes in foot placement increased trip risk for both ages, but for different limbs, reducing the likelihood of balance recovery in older adults.

Two-minute standing endurance test for axial postural abnormalities in patients with Parkinson’s disease

BackgroundPhoto-based measurement methods are used to assess axial postural abnormalities (PA) in Parkinson’s disease (PD). However, they capture only moments in time. We developed the 2-minute standing endurance test (2 M-SET), which specifically captures temporal changes in posture, as a novel dynamic method for measuring axial PA in patients with PD. Research questionThis study aimed to verify the effectiveness and validity of the 2 M-SET for capturing temporal changes in axial PA in patients with PD. MethodsTwenty-eight patients with PD participated. The participants attempted to maintain an upright posture for 2 minutes during three tasks: standing, stepping in place, and walking. The rate of change in postural angle was recorded at 10-second intervals. Based on the results, the 2 M-SET was developed. Therapists evaluated the 2 M-SET using the NeuroPostureApp© to measure anterior trunk flexion (ATF) angles and lateral trunk flexion (LTF) angles at 0, 10, 30, 60, and 120 seconds. To assess reliability, the congruence between the measurements obtained by the therapists and those obtained using a three-dimensional motion-analysis system was examined. For validity, we assessed whether the ATF and LTF angles measured by the therapists could accurately capture postural changes at regular intervals over time. ResultsThe average postural changes over 2 minutes for the standing, stepping in place, and gait tasks were 59.2±83.5%, 37.6±30.7%, and 45.4±50.6%, respectively. The intraclass correlation coefficients showed high reliability, with values of 0.985 and 0.970 for the ATF and LTF angles, respectively. SignificanceThe results of our proposed 2 M-SET method, which uses temporal photo-based measurements to assess the patient’s ability to maintain an upright standing position for 2 minutes, demonstrate the potential to capture temporal changes in axial PA. Data Availability StatementThe data supporting the findings of this study are available upon reasonable request and approval from the local ethics committee.