Entropy Analysis in Gait Research: Methodological Considerations and Recommendations

Altered gait stability and regularity in lower limb amputees observed across different body segments

The lack of sensory feedback coupled with mechanical constraints due to the prosthetic leg increases walking instability and the risk of falling in lower limb amputees. We investigated kinematic regularity and stability of different body segments in lower limb amputees during walking to identify possible altered dynamics leading to compensatory movements. We measured the three-dimensional acceleration and angular velocity of 15 body segments during two minutes of treadmill walking at three different velocities. The maximal Lyapunov exponents and fuzzy entropy were calculated from these data to assess local dynamic stability and regularity. Probabilistic principal component analysis (PPCA) was used to select the body segments that showed the highest variability between amputees and able-bodied individuals. Amputees exhibited increased instability in acceleration patterns, particularly at low walking velocity (1 km/h), regardless of body segment and direction. Angular velocity patterns were more unstable in amputees, especially on the amputated side. Altered regularity adaptation was observed with higher velocity in amputees, with the intact side showing less adaptive patterns than controls. These results further suggest that amputees have a holistically disrupted gait and balance system. Our analysis of non-linear gait dynamics provides new insights into the complex challenges faced by amputees during walking, particularly in adapting to different gait velocities.

Changes in torque complexity with fatigue are related to motor unit behaviour

Physiological complexity is believed to reflect a system's adaptability to environmental challenges having been proposed as an indirect indicator of the functional capacity of the neuromuscular system. This study aimed to investigate the association between torque complexity's changes with neuromuscular fatigue and motor unit parameters. Twenty-one healthy and young adults visited the laboratory on one occasion. Knee extension maximum voluntary isometric contractions and isometric contractions at 30% of maximum were collected at baseline and immediately after a fatiguing knee extension protocol, which consisted of a series of concentric and eccentric knee extensions at 90°/s until exhaustion. Torque signals were sampled continuously, and torque complexity was assessed through an entropy measure. Motor unit-related parameters were extracted from the submaximal trials and further analysed. Our findings demonstrate that torque complexity's alteration pre-to-post neuromuscular fatigue is highly correlated with vastus lateralis and medialis average firing rate (r = - 0.618 and r = - 0.659, respectively) and peak motor unit action potential amplitude (rs = - 0.801 and rs = - 0.703, respectively) pre-fatigue. Moreover, alterations in torque complexity were observed, indicating a loss of adaptability within the neuromuscular system with neuromuscular fatigue. Overall, our findings supported our hypothesis by demonstrating alterations in torque complexity with neuromuscular fatigue, rendering the system less adaptable. Moreover, our results added to the current knowledge by highlighting the association between torque complexity's changes with neuromuscular fatigue and motor unit parameters.

Reliability of running gait variability measures calculated from inertial measurement units

Changes to the variability within biomechanical signals may reflect a change in the health of the human system. However, for running gait variability measures calculated from wearable device data, it is unknown whether a between-day difference reflects a shift in system dynamics reflective of a change in human health or is a result of poor between-day reliability of the measurement device or the biomechanical signal. This study investigated the reliability of stride time and sacral acceleration variability measures calculated from inertial measurement units (IMUs). Nineteen runners completed six treadmill running trials on two occasions seven days apart. Stride time and sacral acceleration signals were obtained using IMUs. Stride time variability and complexity were calculated using the coefficient of variation (CV) and detrended fluctuation analysis (DFA), respectively. Sacral acceleration regularity was quantified using sample entropy with a range of input parameters m (vector length) and r (similarity threshold). Between-day reliability was assessed using the intraclass correlation coefficient (ICC), standard error of measurement (SEM) and minimum detectable change. Stride time CV displayed moderate relative reliability (ICC = 0.672), but with a large absolute minimum detectable change = 0.525 %, whilst stride time DFA-α displayed poor relative reliability (ICC = 0.457) and yielded large minimum detectable changes (≥ 0.208). Sample entropy displayed good relative reliability in mediolateral and resultant sacral acceleration signals for certain combinations of the parameters m and r, although again with large minimum detectable changes. Researchers should be cognisant of these reliability metrics when interpreting changes in running gait variability measures in clinical contexts.

NONAN GaitPrint: An IMU gait database of healthy older adults

The continued effort to study gait kinematics and the increased interest in identifying individuals based on their gait patterns could be strengthened by the inclusion of data from older groups. To address this need and complement our previous database on healthy young adults, we present an addition to the Nonlinear Analysis Core (NONAN) GaitPrint database. We offer full-body inertial measurement data during self-paced overground walking on a 200 m indoor track of 41 older adults (56 + years old; 20 men and 21 women; age: 64.7 ± 7.5 years; height: 1.7 ± 0.1 m; body mass: 81.1 ± 17.8 kg) across 18 four-minute trials conducted over two days. The multiple recordings are supported by a range of pre-calculated spatiotemporal variables, a list of each subject's anthropometrics, notes for each walking trial, and template scripts for easier application of our data to classroom assignments or laboratory research. In addition, a preliminary Bayesian analysis found a range of evidence supporting age-related gait changes between this database and our database on young adults.

Cortical changes associated with an anterior cruciate ligament injury may retrograde skilled kicking in football: preliminary EEG findings

Anterior cruciate ligament injuries (ACLi) impact football players substantially leading to performance declines and premature career endings. Emerging evidence suggests that ACLi should be viewed not merely as peripheral injuries but as complex conditions with neurophysiological aspects. The objective of the present study was to compare kicking performance and associated cortical activity between injured and healthy players. Ten reconstructed and 15 healthy players performed a kicking task. Kicking biomechanics were recorded using wearable inertial measurement unit sensors. Cortical activity was captured with a 64-electrode mobile electroencephalography. Multiscale entropy (MSE) analysis of biomechanics revealed increased variability in foot external rotation among injured players. Source-derived event-related spectral perturbations indicated significant differences in posterior alpha and frontal theta oscillations between the two groups. Furthermore, kick-related complexity of these regions as indexed by MSE was reduced in injured players at medium and coarse scales. Our findings suggest sensorimotor changes during kicking in injured players, which may necessitate compensatory strategies involving augmented attention at the cost of processing visuospatial information. This conflict may hinder the integration of task-relevant information across distributed networks. Our study provides preliminary insights into the neurophysiological implications of ACLi within football context and underscores the potential for prospective research.

Comparison of Mean Values and Entropy in Accelerometry Time Series from Two Microtechnology Sensors Recorded at 100 vs. 1000 Hz During Cumulative Tackles in Young Elite Rugby League Players

Several microtechnology devices quantify the external load of team sports using Global Positioning Systems sampling at 5, 10, or 15 Hz. However, for short, explosive actions, such as collisions, these sample rates may be limiting. It is known that very high-frequency sampling is capable of capturing changes in actions over a short period of time. Therefore, the aim of this study was to compare the mean acceleration and entropy values obtained from 100 Hz and 1000 Hz tri-axial accelerometers in tackling actions performed by rugby players. A total of 11 elite adolescent male rugby league players (mean ± SD; age: 18.5 ± 0.5 years; height: 179.5 ± 5.0 cm; body mass: 88.3 ± 13.0 kg) participate in this study. Participants performed tackles (n = 200), which were recorded using two triaxial accelerometers sampling at 100 Hz and 1000 Hz, respectively. The devices were placed together inside the Lycra vests on the players' backs. The mean acceleration, sample entropy (SampEn), and approximate entropy (ApEn) were analyzed. In mean acceleration, the 1000 Hz accelerometer obtained greater values (p < 0.05). However, SampEn and ApEn were greater with the 100 Hz accelerometer (p < 0.05). A large relationship was observed between the two devices in all the parameters analyzed (R2 > 0.5; p < 0.0001). Sampling frequency can affect the quality of the data collected, and a higher sampling frequency potentially allows for the collection of more accurate motion data. A frequency of 1000 Hz may be suitable for recording short and explosive actions.

Learning to Cycle: Why Is the Balance Bike More Efficient than the Bicycle with Training Wheels? The Lyapunov's Answer

BACKGROUND/OBJECTIVES

Riding a bicycle is a foundational movement skill that can be acquired at an early age. The most common training bicycle has lateral training wheels (BTW). However, the balance bike (BB) has consistently been regarded as more efficient, as children require less time on this bike to successfully transition to a traditional bike (TB). The reasons for this greater efficiency remain unclear, but it is hypothesized that it is due to the immediate balancing requirements for learners. This study aimed to investigate the reasons why the BB is more efficient than the BTW for learning to cycle on a TB.

METHODS

We compared the variability of the child-bicycle system throughout the learning process with these two types of training bicycles and after transitioning to the TB. Data were collected during the Learning to Cycle Program, with 23 children (6.00 ± 1.2 years old) included. Participants were divided into two experimental training groups, BB (N = 12) and BTW (N = 11). The angular velocity data of the child-bicycle system were collected by four inertial measurement sensors (IMUs), located on the child's vertex and T2 and the bicycle frame and handlebar, in three time phases: (i) before practice sessions, (ii) immediately after practice sessions, and (iii), two months after practice sessions with the TB. The largest Lyapunov exponents were calculated to assess movement variability.

CONCLUSIONS

Results supported the hypothesis that the BB affords greater functional variability during practice sessions compared to the BTW, affording more functionally adaptive responses in the learning transition to using a TB.

Monitoring Age-Related Changes in Gait Complexity in the Wild with a Smartphone Accelerometer System

Stride-to-stride fluctuations during walking reflect age-related changes in gait adaptability and are estimated with nonlinear measures that confine data collection to controlled settings. Smartphones, with their embedded accelerometers, may provide accessible gait analysis throughout the day. This study investigated age-related differences in linear and nonlinear gait measures estimated from a smartphone accelerometer (SPAcc) in an unconstrained, free-living environment. Thirteen young adults (YA) and 11 older adults (OA) walked within a shopping mall with a SPAcc placed in their front right pants pocket. The inter-stride interval, calculated as the time difference between ipsilateral heel contacts, was used for dependent measures calculations. One-way repeated-measures analysis of variance revealed significant (p < 0.05) age-related differences (mean: YA, OA) for stride-time standard deviation (0.04 s, 0.05 s) and coefficient of variation (3.47%, 4.16%), sample entropy (SaEn) scale 1 (1.70, 1.86) and scale 3 (2.12, 1.80), and statistical persistence decay (31 strides, 23 strides). The fractal scaling index was not different between groups (0.93, 0.95), but exceeded those typically found in controlled settings, suggesting an upregulation in adaptive behaviour likely to accommodate the increased challenge of free-living walking. These findings support the SPAcc as a viable telehealth instrument for remote monitoring of gait dynamics, with implications for unsupervised fall-risk assessment.

Longitudinal detection of gait alterations associated with hypertension-induced cerebral microhemorrhages in mice: predictive role of stride length and stride time asymmetry and increased gait entropy

Cerebral microhemorrhages (CMHs) are of paramount importance as they not only signify underlying vascular pathology but also have profound implications for cognitive function and neurological health, serving as a critical indicator for the early detection and management of vascular cognitive impairment (VCI). This study aimed to investigate the effects of hypertension-induced CMHs on gait dynamics in a mouse model, focusing on the utility of advanced gait metrics as sensitive indicators of subclinical neurological alterations associated with CMHs. To induce CMHs, we employed a hypertensive mouse model, using a combination of Angiotensin II and L-NAME to elevate blood pressure, further supplemented with phenylephrine to mimic transient blood pressure fluctuations. Gait dynamics were analyzed using the CatWalk system, with emphasis on symmetry indices for Stride Length (SL), Stride Time (ST), and paw print area, as well as measures of gait entropy and regularity. The study spanned a 30-day experimental period, capturing day-to-day variations in gait parameters to assess the impact of CMHs. Temporary surges in gait asymmetry, detected as deviations from median gait metrics, suggested the occurrence of subclinical neurological signs associated with approximately 50% of all histologically verified CMHs. Our findings also demonstrated that increases in gait entropy correlated with periods of increased gait asymmetry, providing insights into the complexity of gait dynamics in response to CMHs. Significant correlations were found between SL and ST symmetry indices and between these indices and the paw print area symmetry index post-hypertension induction, indicating the interdependence of spatial and temporal aspects of gait affected by CMHs. Collectively, advanced gait metrics revealed sensitive, dynamic alterations in gait regulation associated with CMHs, resembling the temporal characteristics of transient ischemic attacks (TIAs). This underscores their potential as non-invasive indicators of subclinical neurological impacts. This study supports the use of detailed gait analysis as a valuable tool for detecting subtle neurological changes, with implications for the early diagnosis and monitoring of cerebral small vessel disease (CSVD) in clinical settings.

Force Fluctuations During Role-Differentiated Bimanual Movements Reflect Cognitive Impairments in Older Adults: A Cohort Sequential Study

During role-differentiated bimanual movements (RDBM), an object is typically stabilized with 1 hand and manipulated with the other. RDBM require coupling both hands for coordinated action (achieved through interhemispheric connections), but also inhibition of crosstalk to avoid involuntary movements in the stabilizing hand. We investigated how healthy cognitive aging and mild cognitive impairments (MCI) affect force stabilization during an RDBM in a cohort sequential study design with up to 4 measurement points over 32 months. In total, 132 older adults (>80 years) participated in this study, 77 were cognitively healthy individuals (CHI) and 55 presented with MCI. Participants performed a visuomotor bimanual force-tracking task. They either produced a constant force with both hands (bimanual constant) or a constant force with 1 and an alternating force with the other hand (role-differentiated). We investigated force fluctuations of constant force production using the coefficient of variation (CV), detrended fluctuation analysis (DFA), and sample entropy (SEn). Results showed higher CV and less complex variability structure (higher DFA and lower SEn) during the role-differentiated compared to the bimanual constant task. Furthermore, CHI displayed a more complex variability structure during the bimanual constant, but a less complex structure during the role-differentiated task than MCI. Interestingly, this complexity reduction was more pronounced in CHI than MCI individuals, suggesting different changes in the control mechanisms. Although understanding these changes requires further research, potential causes might be structural deteriorations leading to less efficient (intra- and interhemispheric) networks because of MCI, or an inability to appropriately divert the focus of attention.

Associating neuromotor outcomes at 12 months with wearable sensor measures collected during early infancy in rural Guatemala

BACKGROUND

Sensitive measures to predict neuromotor outcomes from data collected early in infancy are lacking. Measures derived from the recordings of infant movement using wearable sensors may be a useful new technique.

METHODS

We collected full-day leg movement of 41 infants in rural Guatemala across 3 visits between birth and 6 months of age using wearable sensors. Average leg movement rate and fuzzy entropy, a measure to describe the complexity of signals, of the leg movements' peak acceleration time series and the time series itself were derived. We tested the three measures for the predictability of infants' developmental outcome, Bayley Scales of Infant and Toddler Development III motor, language, or cognitive composite score assessed at 12 months of age. We performed quantile regressions with clustered standard errors, accounting for the multiple visits for each infant.

RESULTS

Fuzzy entropy was associated with the motor composite score at the 0.5 quantiles; this association was not found for the other two measures. Also, no leg movement characteristic was associated with language or cognitive composite scores.

CONCLUSION

We propose that the entropy of leg movement associated peak accelerations calculated from the wearable sensor data collected for a full-day can be considered as one predictor for infants' motor developmental outcome assessed with Bayley Scales of Infant and Toddler Development III at 12 months of age.

Movement Diversity and Complexity Increase as Arm Impairment Decreases After Stroke: Quality of Movement Experience as a Possible Target for Wearable Feedback

Upper extremity (UE) impairment is common after stroke resulting in reduced arm use in daily life. A few studies have examined the use of wearable feedback of the quantity of arm movement to promote recovery, but with limited success. We posit that it may be more effective to encourage an increase in beneficial patterns of movement practice - i.e. the overall quality of the movement experience - rather than simply the overall amount of movement. As a first step toward testing this idea, here we sought to identify statistical features of the distributions of daily arm movements that become more prominent as arm impairment decreases, based on data obtained from a wrist IMU worn by 22 chronic stroke participants during their day. We identified several measures that increased as UE Fugl-Meyer (UEFM) score increased: the fraction of movements achieved at a higher speed, forearm postural diversity (quantified by kurtosis of the tilt-angle), and forearm postural complexity (quantified by sample entropy of tilt angle). Dividing participants into severe, moderate, and mild impairment groups, we found that forearm postural diversity and complexity were best able to distinguish the groups (Cohen's D =1.1, and 0.99, respectively) and were also the best subset of predictors for UEFM score. Based on these findings coupled with theories of motor learning that emphasize the importance of variety and challenge in practice, we suggest that using these measures of diversity and complexity in wearable rehabilitation could provide a basis to test whether the quality of the daily movement experience is therapeutic.

Gait characterization in rare bone diseases in a real-world environment - A comparative controlled study

BACKGROUND

Rare bone diseases (RBD) cause physical and sensory disability that affects quality of life. Mobility challenges are common for people with RBDs, and travelling to gait analysis labs can be very complex. Smartphone sensors could provide remote monitoring.

RESEARCH QUESTION

This study aimed to search for and identify variables that can be used to discriminate between people with RBD and healthy people by using built-in smartphone sensors in a real-world setting.

METHODS

In total, 18 participants (healthy: n=9; RBD: n=9), controlled by age and sex, were included in this cross-sectional study. A freely available App (Phyphox) was used to gather data from built-in smartphone sensors (accelerometer & gyroscope) at 60 Hz during a 15-min walk on a level surface without turns or stops. Temporal gait parameters like cadence, mean stride time and, coefficient variance (CoVSt) and nonlinear analyses, as the largest Lyapunov exponent (LLE) & sample entropy (SE) in the three accelerometer axes were used to distinguish between the groups and describe gait patterns.

RESULTS

The LLE (p=0.04) and the SE of the z-axis (p=0.01), which are correlated with balance control during walking and regularity of the gait, are sufficiently sensitive to distinguish between RBD and controls.

SIGNIFICANCE

The use of smartphone sensors to monitor gait in people with RBD allows for the identification of subtle changes in gait patterns, which can be used to inform assessment and management strategies in larger cohorts.

Gait variability, fractal dynamics, and statistical regularity of treadmill and overground walking recorded with a smartphone

BACKGROUND

The nonlinear variability present during steady-state gait may provide a signature of health and showcase one's walking adaptability. Although treadmills can capture vast amounts of walking data required for estimating variability within a small space, gait patterns may be misrepresented compared to an overground setting. Smartphones may provide a low-cost and user-friendly estimate of gait patterns among a variety of walking settings. However, no study has investigated differences in gait patterns derived from a smartphone between treadmill walking (TW) and overground walking (OW).

RESEARCH QUESTION

This study implemented a smartphone accelerometer to compare differences in temporal gait variability and gait dynamics between TW and OW.

METHODS

Sixteen healthy adults (8F; 24.7 ± 3.8 years) visited the laboratory on three separate days and completed three 8-minute OW and three TW trials, at their preferred speed, during each visit. The inter-stride interval was calculated as the time difference between right heel contact events located within the vertical accelerometery signals recorded from a smartphone while placed in participants front right pant pocket during walking trials. The inter-stride interval series was used to calculate stride time standard deviation (SD) and coefficient of variation (COV), statistical persistence (fractal scaling index), and statistical regularity (sample entropy). Two-way analysis of variance compared walking condition and laboratory visits for each measure.

RESULTS

Compared to TW, OW displayed significantly (p < 0.01) greater stride time SD (0.014 s, 0.020 s), COV (1.26 %, 1.82 %), fractal scaling index (0.70, 0.79) and sample entropy (1.43, 1.63). No differences were found between visits for all measures.

SIGNIFICANCE

Smartphone-based assessment of gait provides the ability to distinguish between OW and TW conditions, similar to previously established methodologies. Furthermore, smartphones may be a low-cost and user-friendly tool to estimate gait patterns outside the laboratory to improve ecological validity, with implications for free-living monitoring of gait among various populations.

Biomechanical Assessment Methods Used in Chronic Stroke: A Scoping Review of Non-Linear Approaches

Non-linear and dynamic systems analysis of human movement has recently become increasingly widespread with the intention of better reflecting how complexity affects the adaptability of motor systems, especially after a stroke. The main objective of this scoping review was to summarize the non-linear measures used in the analysis of kinetic, kinematic, and EMG data of human movement after stroke. PRISMA-ScR guidelines were followed, establishing the eligibility criteria, the population, the concept, and the contextual framework. The examined studies were published between 1 January 2013 and 12 April 2023, in English or Portuguese, and were indexed in the databases selected for this research: PubMed®, Web of Science®, Institute of Electrical and Electronics Engineers®, Science Direct® and Google Scholar®. In total, 14 of the 763 articles met the inclusion criteria. The non-linear measures identified included entropy (n = 11), fractal analysis (n = 1), the short-term local divergence exponent (n = 1), the maximum Floquet multiplier (n = 1), and the Lyapunov exponent (n = 1). These studies focused on different motor tasks: reaching to grasp (n = 2), reaching to point (n = 1), arm tracking (n = 2), elbow flexion (n = 5), elbow extension (n = 1), wrist and finger extension upward (lifting) (n = 1), knee extension (n = 1), and walking (n = 4). When studying the complexity of human movement in chronic post-stroke adults, entropy measures, particularly sample entropy, were preferred. Kinematic assessment was mainly performed using motion capture systems, with a focus on joint angles of the upper limbs.

Laboratory-assessed gait cycle entropy for classifying walking limitations among community-dwelling older adults

Among older people, walking difficulty results from actual and perceived declines in physical capacities and environmental requirements for walking. We investigated whether the physiological complexity of the gait cycle covaries with experience of walking difficulty. Walking difficulty, gait speed, and gait cycle complexity were evaluated among 702 community-dwelling older people aged 75, 80, and 85 years who took part in the six-minute walking test in the research laboratory. Walking difficulty for 500 m was self-reported. Complexity was quantified as trunk acceleration multiscale entropy during the gait cycle. Complexity was then compared between those with no reported walking difficulty, walking with modifications but no difficulty, and those reporting walking difficulty. Higher entropy differentiated those reporting no difficulty walking from those reporting walking difficulties, while those reporting having modified their walking, but no difficulty formed an intermediate group that could not be clearly distinguished from the other categories. The higher complexity of the gait cycle is associated with slower gait speed and the presence of self-reported walking difficulty. Among older people, gait cycle complexity which primarily reflects the biomechanical dimensions of gait quality, could be a clinically meaningful measure reflecting specific features of the progression of walking decline. This encourages further investigation of the sensitivity of gait cycle complexity to detect early signs of gait deterioration and to support targeted interventions among older people.

Predictability and Complexity of Fine and Gross Motor Skills in Fibromyalgia Patients: A Pilot Study

BACKGROUND

Fine and gross motor tasks are usually used to evaluate behavioral dysfunctions and can be applied to diseases of the central nervous system, such as fibromyalgia (FM). Non-linear measures have allowed for deeper motor control analysis, focusing on the process and on the quality of movement. Therefore, to assess uncertainty, irregularity, and structural richness of a time series, different algorithms of entropy can be computed. The aim of this study was to (i) verify the single-scale and multiscale entropy values in fine and gross motor movements and (ii) to verify whether fine and gross motor tasks are sensitive to characterizing FM patients.

METHODS

The sample consisted of 20 females (46.2 ± 12.8 years) divided in two groups, an experimental group with 10 FM subjects and a control group with 10 subjects without FM. Inertial sensors were used to collect the finger tapping test (FTT), walking, and sit-and-stand task data.

RESULTS

Regarding fine motor skills, patients with FM showed a loss of structural richness (complexity), but they had information processing with greater control in the FTT, probably to simplify task execution and for correction of the movement. On the other hand, people without FM seemed to have more automatic control of the movement when performed with the preferred hand and exhibited similar difficulties to the FM group when performed with the non-preferred hand. Gross motor tasks showed similar entropy values for both groups.

CONCLUSIONS

The results show that FM patients have movement controls primarily at the level of the motor cortex, whereas people without FM perform movement at the medullary level, especially in fine motor tasks, indicating that the FTT is sensitive to the presence of FM, especially when performed with the preferred hand.

Sample Entropy Improves Assessment of Postural Control in Early-Stage Multiple Sclerosis

Postural impairment in people with multiple sclerosis (pwMS) is an early indicator of disease progression. Common measures of disease assessment are not sensitive to early-stage MS. Sample entropy (SE) may better identify early impairments. We compared the sensitivity and specificity of SE with linear measurements, differentiating pwMS (EDSS 0-4) from healthy controls (HC). 58 pwMS (EDSS ≤ 4) and 23 HC performed quiet standing tasks, combining a hard or foam surface with eyes open or eyes closed as a condition. Sway was recorded at the sternum and lumbar spine. Linear measures, mediolateral acceleration range with eyes open, mediolateral jerk with eyes closed, and SE in the anteroposterior and mediolateral directions were calculated. A multivariate ANOVA and AUC-ROC were used to determine between-groups differences and discriminative ability, respectively. Mild MS (EDSS ≤ 2.0) discriminability was secondarily assessed. Significantly lower SE was observed under most conditions in pwMS compared to HC, except for lumbar and sternum SE when on a hard surface with eyes closed and in the anteroposterior direction, which also offered the strongest discriminability (AUC = 0.747), even for mild MS. Overall, between-groups differences were task-dependent, and SE (anteroposterior, hard surface, eyes closed) was the best pwMS classifier. SE may prove a useful tool to detect subtle MS progression and intervention effectiveness.

Motivation-related influences on fNIRS signals during walking exercise: a permutation entropy approach

Cortical activity is typically indexed by analyzing functional near-infrared spectroscopy (fNIRS) signals in terms of the mean (e.g., mean oxygenated hemoglobin; HbO). Entropy approaches have been proposed as useful complementary methods for analyzing fNIRS signals. Entropy methods consider the regularity of a time series, and in doing so, may provide additional insights into the underlying dynamics of brain activity. Recent research using fNIRS found that non-disabled adults exhibit widespread increases in cortical activity and walk faster when under "extra motivation" conditions (e.g., verbal encouragement, lap timer) compared to trials without such motivators ("standard motivation"). This ancillary analysis of that study aimed to assess the extent to which fNIRS permutation entropy (PE) was affected by motivational conditions and explained variance in self-reported motivation. No regional PE differences were found between different motivational conditions. However, a greater difference in PE between motivational conditions (higher in standard, lower in extra motivation) in the anterior prefrontal cortex (aPFC) was associated with greater self-determined motivation. PE was also higher (less regular) in the primary sensorimotor cortex lower limb area compared to all other cortical areas analyzed, except the dorsal premotor cortex, regardless of motivational condition. This study provides early evidence to suggest that while different motivational environments during walking activity influence the magnitude of fNIRS signals, they may not influence the regularity of cortical signals. However, the magnitude of PE difference between motivational conditions was related to self-determined motivation in the aPFC, and this is an area warranting further investigation.

Change in sensory integration and regularity of postural sway with the suspensory strategy during static standing balance

Background and aim

The suspensory strategy, a method for controlling postural balance in the vertical direction of the center of mass (COM), is considered by the elderly as a means of balance control. The vertical COM control might alter the sensory integration and regularity of postural sway, which in turn impacts balance. However, to date, this was not confirmed. Thus, this study aimed at investigating the influence of the suspensory strategy achieved through knee flexion on the static standing balance.

Methods

Nineteen participants were monitored at knee flexion angles of 0°, 15°, and 65°. Time-frequency analysis and sample entropy were employed to analyze the COM data. Time-frequency analysis was utilized to assess the energy content across various frequency bands and corresponding percentage of energy within each frequency band. The outcomes of time-frequency are hypothesized to reflect the balance-related sensory input and sensory weights. Sample entropy was applied to evaluate the regularity of the COM displacement patterns.

Results

Knee flexion led to a decreased COM height. The highest energy content was observed at 65° knee flexion, in contrast with the lowest energy observed at 0° in both the anterior-posterior (AP) and medial-lateral (ML) directions. Additionally, the ultra-low-frequency band was more pronounced at 65° than that at 0° or 15° in the ML direction. Furthermore, the COM amplitudes were notably higher at 65° than those at 0° and 15° in the AP and ML directions, respectively. The sample entropy values were lower at 65° and 15° than those at 0° in the ML direction, with the lowest value observed at 65° in the vertical direction.

Conclusion

The suspensory strategy could enhance the sensory input and cause sensory reweighting, culminating in a more regular balance control. Such suspensory strategy-induced postural control modifications may potentially provide balance benefits for people with declining balance-related sensory, central processing, and musculoskeletal system functions.

Distinct clusters of movement entropy in children's exploration of a virtual reality balance beam

Although assessing motor competence is vital to advancing current understandings of motor development and its significance in various fields, no consensus exists on how the construct should be operationalised and measured. Existing approaches to assessing motor competence in children typically involve applying qualitative and/or quantitative scoring procedures in which children's performance is evaluated according to certain levels of assessment-specific task performance dependent upon predefined sets of instructions and procedures. Building upon ecological dynamics as a framework, different levels of motor competence can be identified in children's attempts to coordinate their degrees of freedom while trying to complete the interactive task and environmental constraints. Given the dynamic, nonlinear features of that coordinating process, assessments need to consider the inherit structure of inter- and intra-individual variability in patterns of movement. Against that background, we investigated 7-10-year-old children's (n = 58) whole-body joint kinematics as they freely explored a balance beam in a virtual reality playground. Specifically, we used exploratory cluster analysis to examine the discriminatory capability of utilising joint-specific sample entropy as a window into individual differences in movement coordination that emerged from children's exploration of the constraints embedded in the virtual task. Among the results, three clusters of children with distinct profiles of movement variability emerged, all of which showed heterogeneous levels of repeatability in joint movements in combination with the level of spatiotemporal exploration on the balance beam that could not be explained by between-cluster differences in age and gender distributions. Those findings suggest that entropy from whole-body movements can be used to cluster children into distinct groups with different profiles regarding the structure of movement variability, which can inform new understandings and the development of gross motor competence assessments for children.

Visual feedback influences the consistency of the locomotor pattern in Asian elephants (Elephas maximus)

Elephants are atypical of most quadrupeds in that they maintain the same lateral sequence footfall pattern across all locomotor speeds. It has been speculated that the preservation of the footfall patterns is necessary to maintain a statically stable support polygon. This should be a particularly important constraint in large, relatively slow animals. This suggests that elephants must rely on available sensory feedback mechanisms to actively control their massive pillar-like limbs for proper foot placement and sequencing. How the nervous system of elephants integrates the available sensory information for a stable gait is unknown. Here we explored the role that visual feedback plays in the control of the locomotor pattern in Asian elephants. Four Asian elephants (Elephas maximus) walked with and without a blindfold as we measured their stride time intervals. Coefficient of variation was used to assess changes in the overall variability of the stride time intervals, while approximate entropy was used to measure the stride-to-stride consistency of the time intervals. We show that visual feedback plays a role in the stride-to-stride consistency of the locomotor pattern in Asian elephants. These results suggest that elephants use visual feedback to correct and maintain proper sequencing of the limbs during locomotion.

Studying Dynamical Characteristics of Oxygen Saturation Variability Signals Using Haar Wavelet

An aim of the analysis of biomedical signals such as heart rate variability signals, brain signals, oxygen saturation variability (OSV) signals, etc., is for the design and development of tools to extract information about the underlying complexity of physiological systems, to detect physiological states, monitor health conditions over time, or predict pathological conditions. Entropy-based complexity measures are commonly used to quantify the complexity of biomedical signals; however novel complexity measures need to be explored in the context of biomedical signal classification. In this work, we present a novel technique that used Haar wavelets to analyze the complexity of OSV signals of subjects during COVID-19 infection and after recovery. The data used to evaluate the performance of the proposed algorithms comprised recordings of OSV signals from 44 COVID-19 patients during illness and after recovery. The performance of the proposed technique was compared with four, scale-based entropy measures: multiscale entropy (MSE); multiscale permutation entropy (MPE); multiscale fuzzy entropy (MFE); multiscale amplitude-aware permutation entropy (MAMPE). Preliminary results of the pilot study revealed that the proposed algorithm outperformed MSE, MPE, MFE, and MMAPE in terms of better accuracy and time efficiency for separating during and after recovery the OSV signals of COVID-19 subjects. Further studies are needed to evaluate the potential of the proposed algorithm for large datasets and in the context of other biomedical signal classifications.

Isometric force complexity may not fully originate from the nervous system

In humans and animals, spatial and temporal information from the nervous system are translated into muscle force enabling movements of body segments. To gain deeper understanding of this translation of information into movements, we investigated the motor control dynamics of isometric contractions in children, adolescents, young adults and older adults. Twelve children, thirteen adolescents, fourteen young adults, and fifteen older adults completed two minutes of submaximal isometric plantar- and dorsiflexion. Simultaneously, sensorimotor cortex EEG, tibialis anterior and soleus EMG and plantar- and dorsiflexion force was recorded. Surrogate analysis suggested that all signals were from a deterministic origin. Multiscale entropy analysis revealed an inverted U-shape relationship between age and complexity for the force but not for the EEG and EMG signals. This suggests that temporal information in from the nervous system is modulated by the musculoskeletal system during the transmission into force. The entropic half-life analyses indicated that this modulation increases the time scale of the temporal dependency in the force signal compared to the neural signals. Together this indicates that the information embedded in produced force does not exclusively reflect the information embedded in the underlying neural signal.

Calculating sample entropy from isometric torque signals: methodological considerations and recommendations

We investigated the effect of different sampling frequencies, input parameters and observation times for sample entropy (SaEn) calculated on torque data recorded from a submaximal isometric contraction. Forty-six participants performed sustained isometric knee flexion at 20% of their maximal contraction level and torque data was sampled at 1,000 Hz for 180 s. Power spectral analysis was used to determine the appropriate sampling frequency. The time series were downsampled to 750, 500, 250, 100, 50, and 25 Hz to investigate the effect of different sampling frequency. Relative parameter consistency was investigated using combinations of vector lengths of two and three and tolerance limits of 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, and 0.4, and data lengths between 500 and 18,000 data points. The effect of different observations times was evaluated using Bland-Altman plot for observations times between 5 and 90 s. SaEn increased at sampling frequencies below 100 Hz and was unaltered above 250 Hz. In agreement with the power spectral analysis, this advocates for a sampling frequency between 100 and 250 Hz. Relative consistency was observed across the tested parameters and at least 30 s of observation time was required for a valid calculation of SaEn from torque data.

Multiscale Entropy Algorithms to Analyze Complexity and Variability of Trunk Accelerations Time Series in Subjects with Parkinson's Disease

The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson's disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (τ) 1-6. Differences between swPD and HS were calculated at each τ, and the area under the receiver operating characteristics, optimal cutoff points, post-test probabilities, and diagnostic odds ratios were calculated. MSE, RCMSE, and CIs showed to differentiate swPD from HS. MSE in the anteroposterior direction at τ4 and τ5, and MSE in the ML direction at τ4 showed to characterize the gait disorders of swPD with the best trade-off between positive and negative posttest probabilities and correlated with the motor disability, pelvic kinematics, and stance phase. Using a time series of 2000 data points, a scale factor of 4 or 5 in the MSE procedure can yield the best trade-off in terms of post-test probabilities when compared to other scale factors for detecting gait variability and complexity in swPD.

The Application of non-linear methods to quantify changes to movement dynamics during running: A scoping review

The aim of this scoping review was to evaluate research approaches that quantify changes to non-linear movement dynamics during running in response to fatigue, different speeds, and fitness levels. PubMed and Scopus were used to identify appropriate research articles. After the selection of eligible studies, study details and participant characteristics were extracted and tabulated to identify methodologies and findings. Twenty-seven articles were included in the final analysis. To evaluate non-linearities in the time series, a range of approaches were identified including motion capture, accelerometery, and foot switches. Common methods of analysis included measures of fractal scaling, entropy, and local dynamic stability. Conflicting findings were evident when studies examined non-linear features in fatigued states when compared to non-fatigued. More pronounced alterations to movement dynamics are evident when running speed is changed markedly. Greater fitness levels resulted in more stable and predictable running patterns. The mechanisms by which these changes are underpinned require further examination. These could include the physiological demand of running, biomechanical constraints of the runner, and the attentional demands of the task. Moreover, the practical implications are yet to be elucidated. This review has identified gaps in the literature which should be addressed for further understanding of the field.

Considerations for Applying Entropy Methods to Temporally Correlated Stochastic Datasets

The goal of this paper is to highlight considerations and provide recommendations for analytical issues that arise when applying entropy methods, specifically Sample Entropy (SampEn), to temporally correlated stochastic datasets, which are representative of a broad range of biomechanical and physiological variables. To simulate a variety of processes encountered in biomechanical applications, autoregressive fractionally integrated moving averaged (ARFIMA) models were used to produce temporally correlated data spanning the fractional Gaussian noise/fractional Brownian motion model. We then applied ARFIMA modeling and SampEn to the datasets to quantify the temporal correlations and regularity of the simulated datasets. We demonstrate the use of ARFIMA modeling for estimating temporal correlation properties and classifying stochastic datasets as stationary or nonstationary. We then leverage ARFIMA modeling to improve the effectiveness of data cleaning procedures and mitigate the influence of outliers on SampEn estimates. We also emphasize the limitations of SampEn to distinguish among stochastic datasets and suggest the use of complementary measures to better characterize the dynamics of biomechanical variables. Finally, we demonstrate that parameter normalization is not an effective procedure for increasing the interoperability of SampEn estimates, at least not for entirely stochastic datasets.

Methodological Considerations in the Kinematic and Kinetic Analysis of Human Movement among Healthy Adolescents: A Scoping Review of Nonlinear Measures in Data Processing

Nonlinear measures have increasingly revealed the quality of human movement and its behaviour over time. Further analyses of human movement in real contexts are crucial for understanding its complex dynamics. The main objective was to identify and summarize the nonlinear measures used in data processing during out-of-laboratory assessments of human movement among healthy adolescents. Summarizing the methodological considerations was the secondary objective. The inclusion criteria were as follows: According to the Population, Concept, and Context (PCC) framework, healthy teenagers between 10 and 19 years old that reported kinetic and/or kinematic nonlinear data-processing measurements related to human movement in non-laboratory settings were included. PRISMA-ScR was used to conduct this review. PubMed, Science Direct, the Web of Science, and Google Scholar were searched. Studies published between the inception of the database and March 2022 were included. In total, 10 of the 2572 articles met the criteria. The nonlinear measures identified included entropy (n = 8), fractal analysis (n = 3), recurrence quantification (n = 2), and the Lyapunov exponent (n = 2). In addition to walking (n = 4) and swimming (n = 2), each of the remaining studies focused on different motor tasks. Entropy measures are preferred when studying the complexity of human movement, especially multiscale entropy, with authors also carefully combining different measures, namely entropy and fractal analysis.

The influence of walking speed and effects of signal processing methods on the level of human gait regularity during treadmill walking

BACKGROUND

In recent years the use of sample entropy (SampEn) to evaluate the complexity of the locomotor system in human gait data has gained in popularity. However, it has been suggested that SampEn is sensitive to various input parameters and signal preprocessing methods. This study quantified the effects of different temporal and spatial normalization approaches and various lengths of the template vector (m) on SampEn calculations. The discriminatory ability of SampEn was studied by comparing two walking conditions.

METHODS

Twenty-three participants (seven males, 55.7 ± 8.5 years, 165.7 ± 7.9 cm, 80.5 ± 16.7 kg) walked on a treadmill with preferred (Vpref) and maximum (Vmax) speed. Data were segmented and resampled (SEGM), resampled and spatially normalized (NORM), resampled and detrended (ZERO).

RESULTS

For vertical ground reaction force (vGRF) and center of pressure in anterio-posterior direction (COPap), in both walking conditions, SampEn was generally sensitive to the vector length and not to the data processing, except for COPap in ZERO, m = 2, 4. For the COPml SampEn behaved oppositely, it was sensitive to preprocessing method and not to the m length. The regularity of COPap and vGRF in all processed signals increased in Vmax condition. For the COPml only two signals, WHOLE and ZERO, revealed increased complexity caused by more demanding walking conditions.

CONCLUSIONS

SampEn was able to discriminate between different walking conditions in all analyzed variables, but not in all signals. Depending on evaluated variable, SampEn was susceptible in different way for the m level and processing method. Hence, these should be checked and selected for each variable independently. For future studies evaluating influence of walking velocity on COP and vGRF regularity during treadmill walking it is advised to use raw time series. Furthermore, to maintain template vector which represents biological relevance it is advised to detect highest frequencies present in analyzed signals and evaluate minimal time interval which can reflect change caused by response of a neuromuscular system. During evaluating treadmill walking measured with 100 Hz sampling frequency it is recommended to adopt m from 6 to 10, when average stride time is up to about 1 s.

Multimodal Agility-Based Exercise Training for Persons With Multiple Sclerosis: A New Framework

INTRODUCTION

Multimodal agility-based exercise training (MAT) has been described as a framework for fall prevention in the elderly but might also be a valuable concept for exercise training in persons with Multiple Sclerosis (pwMS).

THE PROBLEM

Current recommendations advise pwMS to perform a multitude of different exercise training activities, as each of these has its separate evidence. However, pwMS struggle even more than the general population to be physically active. Additionally, Multiple Sclerosis often leads to co-occurring mobility and cognitive dysfunctions, for which simultaneous, time-efficient, and engaging training approaches are still limited in clinical practice and healthcare.

THE SOLUTION

The MAT framework has been developed to integratively improve cardiovascular, neuromuscular, and cognitive function by combining aspects of perception and orientation, change of direction, as well as stop-and-go patterns (ie, agility), in a group-training format. For pwMS, the MAT framework is conceptualized to include 3 Components: standing balance, dynamic balance (including functional leg strength), and agility-based exercises. Within these Components sensory, cognitive, and cardiovascular challenges can be adapted to individual needs.

RECOMMENDATIONS

We recommend investigating multimodal exercise interventions that go beyond easily standardized, unimodal types of exercise (eg, aerobic or resistance exercise), which could allow for time-efficient training, targeting multiple frequent symptoms of persons with mild disability at once. MAT should be compared to unimodal approaches, regarding sensor-based gait outcomes, fatigue-related outcomes, cognition, as well as neuroprotective, and (supportive) disease-modifying effects.

Gait variability predicts cognitive impairment in older adults with subclinical cerebral small vessel disease

Introduction

Advanced methods of gait research, including approaches to quantify variability, and orderliness/regularity/predictability, are increasingly used to identify patients at risk for the development of cognitive impairment. Cerebral small vessel disease (CSVD) is highly prevalent in older adults and is known to contribute to the development of vascular cognitive impairment and dementia (VCID). Studies in preclinical models demonstrate that subclinical alterations precede CSVD-related cognitive impairment in gait coordination. In humans, CSVD also associates with gait abnormalities. The present study was designed to test the hypothesis that increased gait variability and gait asymmetry predict a decline in cognitive performance in older adults with CSVD.

Methods

To test this hypothesis, we compared cognitive performance and gait function in patients with CSVD (age: 69.8 ± 5.3 years; n = 11) and age- and sex-matched control participants (age: 70.7 ± 5.8 years; n = 11). Based on imaging findings, patients with CSVD were identified [presence of white matter hyperintensities plus silent brain infarcts and/or microhemorrhages on magnetic resonance imaging (MRI) assessment]. Cognitive performance was assessed using the Cambridge Neuropsychological Test Automated Battery (CANTAB). Gait parameters were measured during the single and dual tasks, during which participants, in addition to the motor task, completed a series of mental arithmetic calculations. Spatial and temporal parameters of gait variability, symmetry, and permutation entropy were determined using a pressure-sensitive gait mat during single and dual cognitive task conditions.

Results

Patients with CSVD exhibited lower performance in a visual learning test (p = 0.030) and in a sustained attention test (p = 0.007). CSVD also affected step time variability (p = 0.009) and step length variability (p = 0.017). Step lengths of CSVD participants were more asymmetric (p = 0.043) than that of controls, while the two groups were statistically similar regarding step time symmetry and entropy of step time and length. Gait variability was inversely associated with sustained attention, especially among CSVD patients, and this relationship was significantly different between the two groups. The association of sustained attention with gait symmetry was also significantly different between the two groups.

Discussion

Our findings provide additional evidence in support of the concept that increased gait variability and asymmetry may predict cognitive impairment in older adults with CSVD.

Nonlinear Analyses Distinguish Load Carriage Dynamics in Walking and Standing: A Systematic Review

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.

Effects of cognitive- and motor-dual tasks on postural control regularity following anterior cruciate ligament reconstruction

BACKGROUND

High injury rates following anterior cruciate ligament reconstruction (ACLR) motivate the need to better understand lingering movement deficiencies following return to sport. Athletic competition involves various types of sensory, motor, and cognitive challenges; however, postural control deficiencies during this spectrum of conditions are not well understood following ACLR.

RESEARCH QUESTION

To what extent is postural control altered following ACLR in the presence of sensory, motor, and cognitive challenges, and does postural control correlate with patient-reported symptoms?

METHODS

Fourteen individuals following ACLR (4 m/10 f, 21.2 ± 2.4 yr, 76.9 ± 19.1 kg, 1.70 ± 0.14 m) and fourteen matched healthy controls (4 m/10 f, 21.2 ± 1.4 yr, 75.4 ± 15.3 kg, 1.70 ± 0.15 m) participated in the study. Participants completed single-leg balance, ACLR limb or matched side for controls, under four conditions: 1) eyes open, 2) eyes closed, 3) visual-cognitive dual task (i.e., reverse digit span), and 4) motor dual task (i.e., catching a ball). Sample entropy (SEn) was calculated for each balance condition to characterize regularity of center of pressure control. Participants also completed patient-reported outcomes to characterize self-reported knee function, symptoms, and fear. A mixed effects model tested for differences in SEn between balance conditions, and Spearman correlations tested for relationships between SEn and patient-reported outcomes.

RESULTS

A significant Group-by-Condition interaction was detected (P = 0.043). While the motor dual task and eyes closed balance conditions were associated with the lowest SEn for both groups, only the visual-cognitive dual task condition demonstrated a significant difference between groups, with the ACLR group having lower SEn [95% confidence interval for ΔSEn: (0.03, 0.35)]. Lower KOOS-Sport scores were associated with decreased SEn for the ACLR group (ρ = 0.81, P < 0.001).

SIGNIFICANCE

These findings are consistent with ACLR individuals using a less automatic approach to postural control compared to controls, particularly when presented with a visual-cognitive challenge. Altered neuromuscular control persists well after ACLR surgery and can be related to patient-reported outcomes.

Electro-suit treatment of children with unilateral cerebral palsy alters nonlinear dynamics of walking

BACKGROUND

Cerebral palsy (CP) is characterized by spasticity and muscle contracture development and associated with mild to severe motor impairments including reduced gait function. Treatment with the Exopulse® suit has been shown to reduce spasticity of the affected muscles and constitutes a non-invasive alternative to pharmaceutical agents and surgical denervation. The present study investigated the effect of systematic treatment with the Exopulse® suit on the nonlinear dynamics and variability of trunk accelerations during walking in children with unilateral CP.

METHODS

Twelve patients (mean age: 12 years, range 7-17 years) with unilateral CP (GMFCS level 1 and 2) received 24 weeks Exopulse® suit treatment with patient-specific muscle stimulation. Before and after the treatment, the patients completed 4 min treadmill walking while trunk accelerometry was obtained. The nonlinear dynamics was quantified by the largest Lyapunov exponent and the complexity index from the multiscale entropy and movement variability was quantified by the root mean square ratio. Pre- vs post-treatment differences were evaluated by a paired Student's t-test.

FINDINGS

The largest Lyapunov exponent (p-value = 0.041) and the complexity index (p-value = 0.030) of the acceleration in the anterior-posterior direction was significantly lower post-treatment. No other between-trial differences were observed.

INTERPRETATION

The present study suggests that 24 weeks of Exopulse® suit treatment alters the nonlinear dynamics but not the variability of the trunk accelerations during walking in children with unilateral CP. The temporal structure of the trunk acceleration in the anterior-posterior direction was altered towards that of healthy individuals.

Nonlinear Dynamic Measures of Walking in Healthy Older Adults: A Systematic Scoping Review

BACKGROUND

Maintaining a healthy gait into old age is key to preserving the quality of life and reducing the risk of falling. Nonlinear dynamic analyses (NDAs) are a promising method of identifying characteristics of people who are at risk of falling based on their movement patterns. However, there is a range of NDA measures reported in the literature. The aim of this review was to summarise the variety, characteristics and range of the nonlinear dynamic measurements used to distinguish the gait kinematics of healthy older adults and older adults at risk of falling.

METHODS

Medline Ovid and Web of Science databases were searched. Forty-six papers were included for full-text review. Data extracted included participant and study design characteristics, fall risk assessment tools, analytical protocols and key results.

RESULTS

Among all nonlinear dynamic measures, Lyapunov Exponent (LyE) was most common, followed by entropy and then Fouquet Multipliers (FMs) measures. LyE and Multiscale Entropy (MSE) measures distinguished between older and younger adults and fall-prone versus non-fall-prone older adults. FMs were a less sensitive measure for studying changes in older adults' gait. Methodology and data analysis procedures for estimating nonlinear dynamic measures differed greatly between studies and are a potential source of variability in cross-study comparisons and in generating reference values.

CONCLUSION

Future studies should develop a standard procedure to apply and estimate LyE and entropy to quantify gait characteristics. This will enable the development of reference values in estimating the risk of falling.

Gait performance in toddlers born preterm: A sensor based quantitative characterization

BACKGROUND AND OBJECTIVES

Preterm children have an increased risk of motor difficulties. Gait analysis and wearable technologies allow the assessment of motor performance in toddlers, identifying early deviations from typical development. Using a sensor-based approach, gait performance of full-term and preterm toddlers at different risk of motor delay was analysed. The aim was to measure quantitative differences among groups.

METHODS

Twenty-nine two-year old children born preterm (≤36 gestational weeks) and 17 full-term controls, matched for age and walking experience, participated in the study. Preterm children were further divided based on risk of motor delay: preterm at high risk (n = 8, born at ≤28 gestational weeks or with ≤1000 g of body weight), and at moderate risk (n = 21). Children were asked to walk along a corridor while wearing 3 inertial sensors on the lower back and on the ankles. Gait temporal parameters, their variability, and nonlinear metrics of trunk kinematics (i.e. recurrence quantification analysis, multiscale entropy) were extracted from the collected data and compared among groups.

RESULTS

Children born preterm showed significantly longer stance and double support phases, higher variability of temporal parameters, and lower multiscale entropy values than peers born full-term. No difference was found for the other parameters when comparing preterm and full-term children. When comparing children grouped according to risk of delay, with increasing risk, children showed longer stride-, stance- and double-support-time, higher variability of temporal parameters, higher recurrence- and lower multiscale entropy values.

CONCLUSIONS

Sensor-based gait analysis allowed differentiating the gait performance of preterm from full-term toddlers, and of preterm toddlers at different risk of motor delay. When analysing the present results with respect to the expected trajectory of locomotor development, children born preterm, in particular those at higher risk of motor delay, exhibited a less mature motor control performance during gait: lower stability (i.e. longer support phases), and higher variability, although not structured towards the exploration of more complex movements (i.e. higher recurrence- and lower multiscale entropy values). These indexes can serve as biomarkers for monitoring locomotor development and early detecting risk to develop persistent motor impairments.

Quantitative Characterization of Motor Control during Gait in Dravet Syndrome Using Wearable Sensors: A Preliminary Study

Dravet syndrome (DS) is a rare and severe form of genetic epilepsy characterized by cognitive and behavioural impairments and progressive gait deterioration. The characterization of gait parameters in DS needs efficient, non-invasive quantification. The aim of the present study is to apply nonlinear indexes calculated from inertial measurements to describe the dynamics of DS gait. Twenty participants (7 M, age 9-33 years) diagnosed with DS were enrolled. Three wearable inertial measurement units (OPAL, Apdm, Portland, OR, USA; Miniwave, Cometa s.r.l., Italy) were attached to the lower back and ankles and 3D acceleration and angular velocity were acquired while participants walked back and forth along a straight path. Segmental kinematics were acquired by means of stereophotogrammetry (SMART, BTS). Community functioning data were collected using the functional independence measure (FIM). Mean velocity and step width were calculated from stereophotogrammetric data; fundamental frequency, harmonic ratio, recurrence quantification analysis, and multiscale entropy (τ = 1...6) indexes along anteroposterior (AP), mediolateral (ML), and vertical (V) axes were calculated from trunk acceleration. Results were compared to a reference age-matched control group (112 subjects, 6-25 years old). All nonlinear indexes show a disruption of the cyclic pattern of the centre of mass in the sagittal plane, quantitatively supporting the clinical observation of ataxic gait. Indexes in the ML direction were less altered, suggesting the efficacy of the compensatory strategy (widening the base of support). Nonlinear indexes correlated significantly with functional scores (i.e., FIM and speed), confirming their effectiveness in capturing clinically meaningful biomarkers of gait.