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The present review aims at providing researchers and practitioners with a holistic overview of technology-based methods for the assessment of fine and gross motor skill in children. We conducted a search of electronic databases using Web of Science, PubMed and Google Scholar, including studies published up to March 2020, that assessed fine and/or gross motor skills, and utilized technological assessment of varying study design. A total of 739 papers were initially retrieved, and after title/abstract screening, removal of duplicates, and full-text screening, 47 were included. Results suggest that motor skills can be quantitatively estimated using objective methods based on a wearable- and/or laboratory-based technology, for typically developing (TD) and non-TD children. Fine motor skill assessment solutions were; force transducers, instrumented tablets and pens, surface electromyography, and optoelectronic systems. Gross motor skill assessment solutions were; inertial measurements units, optoelectronic systems, baropodometric mats, and force platforms. This review provides a guide in identifying and evaluating the plethora of available technological solutions to motor skill assessment. Although promising, there is still a need for large-scale studies to validate these approaches in terms of accuracy, repeatability, and usability, where interdisciplinary collaborations between researchers and practitioners and transparent reporting practices should be advocated.

Background Physical inactivity is worldwide considered one of the biggest public health problems of the 21st century. WHO recommended in children, at least 60 minute of Moderate Vigorous Physical activity (MVPA) per day, but low percentages comply with guidelines. Considering that children spend many hours at school, classroom is the ideal setting to increase their PA. Active Breaks (AB) are a 5-15-minute bouts of PA led by the teachers during academic lessons. The aim of the Imola AB study is to implement a 1-year intervention based on AB (10min/3per-day) in primary school as a new strategy to reduce inactivity. We present the baseline results. Methods Quasi-experimental pre-post study in 6-10aged primary school children, in Imola(Italy).We evaluated PA level with Actigraph accelerometers: time (in minutes) spent in MVPA Weekly and Daily (W-MVPA; D-MVPA) and Weekly Sedentary behaviours (W-SB). Results We recruited 152 children: N = 110 in Active Breaks experimental group (AB) and N = 42 in control group (CG). Actigraph's analysis showed that 42,5% of children in the ABG vs 31.0% in the CG reach the WHO recommendation (p=ns). We investigated baseline differences between groups using ANOVA dividing children by grade. In 3-4 grades: W-MVPA (AB = 318.3±15.5 vs CG = 310.4±98.0 p = 0.78); D-MVPA (AB = 53.0±20.3 vs CG = 51.8±16.3 p = 0.79);W-SB (AB = 6,687.5±375.3 vs CG = 6,754.7±281.0 p = 0.45). In 1grade: W-MVPA (AB = 376.1±127.9 vs CG = 300.3±120.0 p = 0.02); D-MVPA (AB = 62.7±21.3 vs CG = 50.0±20.0 p = 0.02); W-SB (AB = 6,436.0±496.0 vs CG = 6,373.3 ±1,532.0 p = 0.7). Conclusions Only the 39.2% of the total sample met the 60-minute/day of MVPA recommended. We found no significant baseline differences in PA level measured by Actigraph between CG and AB, excepted in 1 grade. The intervention implemented in the Imola AB study could be a good strategy to reduce sedentary in children and reach the WHO recommendation, thus contributing to the aims of the new Global Action Plan on PA 2018-2030. Key messages Less than 50% reach the WHO recommendations of PA. AB implemented in the Imola Study could be a public health school-based strategy to reduce sedentary and increase healthy behavior in children. Active breaks (AB) are emerging as a good strategy to increase the PA level, reducing the time in sedentary habits.

Background Walking on compliant surfaces, on sand in particular, is now recommended for training in both elderlies and injured subjects/individuals, allowing to perform high intensity exercises (i.e. augmented energy expenditure) in safe conditions (i.e. minimizing the impact on the joints and the risk of fall). Nevertheless, despite the assessment of energetics of walking on sand, the quantitative biomechanical characterization of walking on sand in ecological conditions is largely lacking. Research question Which is the effect of sand surface on gait speed, gait temporal segmentation and their variability as related to surface compliance in ecological condition? Methods Eighteen healthy adults were assessed while walking on solid ground, dry-, and wet sand in ecological conditions by means of wearable inertial sensors (Miniwave, Cometa s.r.l., Italy). The best performing algorithm for the segmentation of walking on sand was selected among 17 algorithms designed for solid ground. Gait timing (i.e. speed, temporal segmentation, variability) was analysed, for the first time, with respect to sand compliance, and compared to walking on solid ground. Results Self-selected speed on a 60 m distance increased when walking on sand with respect to solid ground (Median 1.02 m/s), with the highest speed on wet sand (Median 1.15 m/s). A stabilizing strategy on the uneven surface provided by sand was highlighted by i) increased stance and double support durations with respect to speed on wet sand, and ii) increased short-term variability of stride, corresponding to continual adjustments of the lower limbs due to shifting surface provided by sand. Significance This study represents the first step in the objective characterization of walking on compliant surfaces as sand, necessary for the definition of training and rehabilitative programs.

Background: Children and adolescents should perform, according to the World Health Organization guidelines, at least 60 min of moderate-to-vigorous physical activity per-day in order to avoid the risk of metabolic and cardiovascular diseases. The school represents a fundamental setting to conduct interventions to promote physical activity (PA) and contrast sedentary behaviors. Active breaks (ABs), bouts of 10 min of PA conducted inside the classroom, seem to be a good strategy to promote PA and improve classroom behavior. The aim of this study protocol is to describe the design and the assessment of the Imola Active Breaks I-MOVE study. Methods: The I-MOVE study is a school-based intervention trial, with a quasi-experimental design, performed in a primary school. It involves one experimental-group performing the intervention, focused on ABs, and one control-group. Nine main outcomes are evaluated: PA and sedentary behaviors; health related fitness; motor control development; dietary patterns; anthropometric evaluation; sociodemographic determinants; cognitive function; time-on-task behavior and quality of life. Conclusions: Results from the I-MOVE study will help to clarify the effects of incorporating ABs in the Italian school curriculum as a new public health strategy and an innovative school model oriented to the well-being of children and teachers for the best quality of school life.

Background The quantification of gait temporal parameters (i.e. step time, stance time) is crucial in human motion analysis and requires the accurate identification of gait events (i.e. heel strike, toe off). With the widespread use of inertial wearable sensors, many algorithms were proposed and applied for the purpose. Nevertheless, only few studies addressed the assessment of the actual performance of these algorithms, rather considering each proposed algorithm as a whole. Research question How different implementation characteristics influence the assessment of gait events and temporal parameters from inertial sensor measures in terms of accuracy and repeatability? Methods Seventeen different algorithms were identified from a systematic review and classified based on: 1) sensor position, 2) target variable, 3) computational approach. The influence of these characteristics was analysed on walking data of 35 healthy volunteers mounting 5 tri-axial inertial sensors. Foot contact events identified by 2 force platforms were assumed as gold standard. Temporal parameters were calculated from gait events. Algorithm performance was analysed in terms of accuracy (error median value) and repeatability (error 25th and 75th percentile values). Results Shank- and foot-based algorithms performed better (in terms of accuracy and repeatability) in gait events detection and stance time estimation than lower trunk-based ones, while sensor position did not affect step estimate, given the error bias characteristics. Angular velocity-based algorithms performed significantly better than acceleration-based ones for toe off detection in terms of repeatability (68 ms and 102 ms, 25th–75th percentile error range, respectively) and, for heel strike detection, showed better repeatability (40 ms and 111 ms) and comparable accuracy (65 ms and 60 ms median error, respectively) than acceleration-based ones. The performance of different computational approaches varied depending on sensor positioning. Significance Present results support the selection of the proper algorithm for the estimation of gait events and temporal parameters in relation to the specific application.

The availability of wearable sensors allows shifting gait analysis from the traditional laboratory settings, to daily life conditions. However, limited knowledge is available about whether alterations associated to different testing environment (e.g. indoor or outdoor) and walking protocols (e.g. free or controlled), result from actual differences in the motor behaviour of the tested subjects or from the sensitivity to these changes of the indexes adopted for the assessment. In this context, it was hypothesized that testing environment and walking protocols would not modify motor control stability in the gait of young healthy adults, who have a mature and structured gait pattern, but rather the variability of their motor pattern.\ud \ud To test this hypothesis, data from trunk and shank inertial sensors were collected from 19 young healthy participants during four walking tasks in different environments (indoor and outdoor) and in both controlled (i.e. following a predefined straight path) and free conditions. Results confirmed what hypothesized: variability indexes (Standard deviation, Coefficient of variation and Poincaré plots) were significantly influenced by both environment and walking conditions. Stability indexes (Harmonic ratio, Short term Lyapunov exponents, Recurrence quantification analysis and Sample entropy), on the contrary, did not highlight any change in the motor control.\ud \ud In conclusion, this study highlighted an influence of environment and testing condition on the assessment of specific characteristics of gait (i.e. variability and stability). In particular, for young healthy adults, both environment and testing conditions affect gait variability indexes, whereas neither affect gait stability indexes.

Quantitative gait analysis can provide a description of joint kinematics and dynamics, and it is recognized as a clinically useful tool for functional assessment, diagnosis and intervention planning. Clinically interpretable parameters are estimated from quantitative measures (i.e. ground reaction forces, skin marker trajectories, etc.) through biomechanical modelling. In particular, the estimation of joint moments during motion is grounded on several modelling assumptions: (1) body segmental and joint kinematics is derived from the trajectories of markers and by modelling the human body as a kinematic chain; (2) joint resultant (net) loads are, usually, derived from force plate measurements through a model of segmental dynamics. Therefore, both measurement errors and modelling assumptions can affect the results, to an extent that also depends on the characteristics of the motor task analysed (i.e. gait speed). Errors affecting the trajectories of joint centres, the orientation of joint functional axes, the joint angular velocities, the accuracy of inertial parameters and force measurements (concurring to the definition of the dynamic model), can weigh differently in the estimation of clinically interpretable joint moments. Numerous studies addressed all these methodological aspects separately, but a critical analysis of how these aspects may affect the clinical interpretation of joint dynamics is still missing. This article aims at filling this gap through a systematic review of the literature, conducted on Web of Science, Scopus and PubMed. The final objective is hence to provide clear take-home messages to guide laboratories in the estimation of joint moments for the clinical practice. Electronic supplementary material The online version of this article (doi:10.1186/s12938-017-0396-x) contains supplementary material, which is available to authorized users.

Movement competence (MC) is defined as the development of sufficient skill to assure successful performance in different physical activities. Monitoring children MC during maturation is fundamental to detect early minor delays and define effective intervention. To this purpose, several MC assessment batteries are available. When evaluating movement strategies, with the aim of identifying specific skill components that may need improving, widespread MC assessment is limited by high time consumption for scoring and the need for trained operators to ensure reliability. This work aims to facilitate and support the assessment by designing, implementing and validating an instrumented version of the TGMD-2 locomotor subtest based on Inertial Measurement Units (IMUs) to quantify MC in children rapidly and objectively. 45 typically developing children, aged 6–10, performed the TGMD-2 locomotor subtest (six skills). During the tests, children wore five IMUs mounted on lower back, on ankles and on wrists. Sensor and video recordings of the tests were collected. Three expert evaluators performed the standard assessment of TGMD-2. Using theoretical and modelling approaches, algorithms were implemented to automatically score children tests based on IMUs’ data. The automatic assessment, compared to the standard one, showed an agreement higher than 87% on average on the entire group for each skill and a reduction of time for scoring from 15 to 2 min per participant. Results support the use of IMUs for MC assessment: this approach will allow improving the usability of MC assessment, supporting objectively evaluator decisions and reducing time requirement for the evaluation of large groups.

In synergy with the musculoskeletal system, motor control is responsible of motor performance, determining joint kinematics and kinetics as related to task and environmental constraints. Multiple metrics have been proposed to quantify motor control from kinematic measures of motion, each index quantifying a different specific aspect, but the characterization of motor control as related to a specific subject or population during the execution of a specific task is still missing. In the present work, the performance of a novel approach for quantitative parametrization of motor control is tested over 86 primary school children: 36 I grade, 50 II grade; 40 females, 46 males. Children were assessed performing natural and tandem gait using 3 inertial measurement units, and gait variability, regularity, and complexity indexes were calculated from gait temporal parameters and trunk acceleration. Standard Test of Motor Competence and Developmental Coordination Disorder Questionnaire were used to assess reference motor competence. The proposed set of parameters allowed to discriminate the level of motor competence as related to age and standardised scales, while differences related to sex resulted negligible. The proposed method can effectively integrate musculoskeletal dynamic models, allowing the parametric characterization of motor control of specific subjects and/or populations.

Background and objectives Walking in water is used for rehabilitation in different pathological conditions. For the characterization of gait alterations related to pathology, gait timing assessment is of primary importance. With the widespread use of inertial sensors, several algorithms have been proposed for gait timing estimation (i.e. gait events and temporal parameters) out of the water, while an assessment of their performance for walking in water is still missing. The purpose of the present study was to assess the performance in the temporal segmentation for gait in water of 17 algorithms proposed in the literature. Methods Ten healthy volunteers mounting 5 tri-axial inertial sensors (trunk, shanks and feet) walked on dry land and in water. Seventeen different algorithms were implemented and classified based on: 1) sensor position, 2) target variable, and 3) computational approach. Gait events identified from synchronized video recordings were assumed as reference. Temporal parameters were calculated from gait events. Algorithm performance was analysed in terms of sensitivity, positive predictive value, accuracy, and repeatability. Results For walking in water, all Trunk-based algorithms provided a sensitivity lower than 81% and a positive predictive value lower than 94%, as well as acceleration-based algorithms, independently from sensor location, with the exception of two Shank-based ones. Drop in algorithm sensitivity and positive predictive value was associated to significant differences in the stride pattern of the specific analysed variables during walking in water as compared to walking on dry land, as shown by the intraclass correlation coefficient. When using Shank- or Foot-based algorithms, gait events resulted delayed, but the delay was compensated in the estimate of Stride and Step time; a general underestimation of Stance- and overestimation of Swing-time was observed, with minor exceptions. Conclusion Sensor position, target variable and computational approach determined different error distributions for different gait events and temporal parameters for walking in water. This work supports an evidence-based selection of the most appropriate algorithm for gait timing estimation for walking in water as related to the specific application, and provides relevant information for the design of new algorithms for the specific motor task.

Background When aiming at studying and monitoring locomotor development in childhood, innovative indexes for the characterization of motor control performance and wearable technologies have highlighted the potential of significant advances. In particular, quantitative assessment of motor performance during natural walking (NW) and tandem walking (TW) has been proposed to highlight manifestations of motor automaticity and complexity, respectively. Research question This work aims at providing a quantitative overview of metrics characterizing locomotor maturation in a typically developing population, by analysing NW and TW. The final goal is to propose a novel graphical representation of motor development from childhood to adulthood, providing metrics for quantitative assessment with reference bands and data-set, supporting data interpretation and longitudinal assessment. Methods 112 typically developing participants (age groups: 6-, 7-, 8-, 9-, 10-, 15-, and 25 years) walked in NW and in TW at self-selected speed. 3D acceleration and angular velocity of lower trunk and shanks were collected. Temporal parameters, their variability, and nonlinear metrics characterizing human movement (harmonic ratio, short-term Lyapunov exponents, multiscale entropy, and recurrence quantification analysis) were calculated. Effect of age was analysed on the different parameters and a graphical polar plot was defined to represent parameters that showed age effect in at least one of the two tasks. Results Age effect was shown on temporal parameters, their variability, multiscale entropy and recurrence quantification analysis. These parameters were selected for monitoring locomotor development and presented on an ad-hoc designed polar plot showing age-group reference bands. Significance Graphic results outline locomotor differences with maturation at first glance. The patterns in NW and TW allow to characterize specific aspects of locomotor maturation, to evaluate in which area changes occur and towards which direction, depending on the task. The novel database containing participants’ raw collected data is made available as additional result of the present study.

Movement complexity can be defined as the capability of using different strategies to accomplish a specific task and is expected to increase with maturation, reaching its highest level in adulthood.Multiscale Entropy (MSE) has been proposed to estimate complexity on different kinematic signals, at different time scales. When applied on trunk acceleration data during natural walking (NW) at different ages, MSE decreased from childhood to adulthood, apparently contradicting the premises. On the contrary, authors hypothesised that this decrease was dependent on the specific task analysed and resulted from the concurrent increase in gait automaticity.This work aims to test this hypothesis, applying MSE on a non-paradigmatic task (tandem walking, TW), in order to exclude aspects related to automaticity.MSE was estimated on trunk acceleration data, collected on children, adolescents, and young adults during TW and NW. As hypothesized, MSE increased significantly with age in TW and decreased in NW on the sagittal plane. Assuming the development of complexity in TW as reference, MSE in NW showed a reduction to half of the complexity of TW with maturation on the sagittal plane. These results indicate MSE as sensitive to differences in performance due to maturation and to expected changes in complexity related to the specific performed task.

When aiming at assessing motor control development, natural walking (NW), and tandem walking (TW) are two locomotor tasks that allow analyzing different characteristics of motor control performance. NW is the reference locomotor task, expected to become more and more automatic with age. TW is a nonparadigmatic task used in clinics to highlight eventual impairments and to evaluate how a child deals with a new challenging motor experience. This work aims at investigating motor development in school-aged children, by assessing quantitatively their performance during TW and NW. Eighty children (6–10 years) participated in the study. Trunk acceleration data and nonlinear measures (recurrence quantification analysis (RQA), and multiscale entropy (MSE)) were used to characterize trunk postural control and motor complexity. The results were analyzed with respect to age and standard clinical assessment of TW (number of correct consecutive steps), by means of Spearman correlation coefficients. RQA and MSE allowed highlighting age-related changes in both postural control of the trunk and motor complexity, while classic standard assessment of TW resulted uniformly distributed in the different age groups. The present results suggest this quantitative approach as relevant when assessing the motor development in schoolchildren and complementary to standard clinical tests.

Soft tissue artefact (STA) represents one of the main obstacles for obtaining accurate and reliable skeletal kinematics from motion capture. Many studies have addressed this issue, yet there is no consensus on the best available bone pose estimator and the expected errors associated with relevant results. Furthermore, results obtained by different authors are difficult to compare due to the high variability and specificity of the phenomenon and the different metrics used to represent these data. Therefore, the aim of this study was twofold: firstly, to propose standards for description of STA; and secondly, to provide illustrative STA data samples for body segments in the upper and lower extremities and for a range of motor tasks specifically, level walking, stair ascent, sit-to-stand, hip- and knee-joint functional movements, cutting motion, running, hopping, arm elevation and functional upper-limb movements. The STA dataset includes motion of the skin markers measured in vivo and ex vivo using stereophotogrammetry as well as motion of the underlying bones measured using invasive or bio-imaging techniques (i.e., X-ray fluoroscopy or MRI). The data are accompanied by a detailed description of the methods used for their acquisition, with information given about their quality as well as characterization of the STA using the proposed standards. The availability of open-access and standard-format STA data will be useful for the evaluation and development of bone pose estimators thus contributing to the advancement of three-dimensional human movement analysis and its translation into the clinical practice and other applications.

Introduction: In a recent work the complexity of gait, assessed through Sample Entropy (SE), was suggested as an innovative and relevant parameter for characterizing the maturation of gait during growth [1]. A possible physiological interpretation of this index is that it describes the amount of cognitive input during walking: in the work by Lamoth et al. [2], SE showed larger values in elderly individuals during dual task (DT), indicating that changes in cognitive functions contribute to changes in gait stability and automaticity. On the other hand, in another study on adolescents’ gait, gait complexity was found to be slightly reduced during DT gait when compared to single task (ST) gait [3]: it was suggested that, probably, adolescents use a different strategy when walking in DT conditions when compared to elderlies. The aim of this work was to further investigate how gait automaticity, assessed through SE, changes through maturation when comparing ST and DT conditions. To this purpose, SE was applied on trunk acceleration data collected during gait of subjects at different ages, from scholar children to young adults. Methods: Forty healthy subjects participated in the study: ten 7-year-old children (7YC), ten 9-year-old children (9YC), ten 15-year-old adolescents (15YC) and ten 25-year-old adults (25YA). Measures of acceleration of the trunk (at L5 level) were collected using one tri-axial wireless inertial sensor. The participants were asked to walk at self-selected speed in ST and cognitive DT conditions: the cognitive DT consisted in counting backward aloud by n from a random starting number (n was fixed at 3 for children, 8 for adolescents and 7 for young adults). For each participant 20 strides were analysed. SE (m = 2, r = 0.2 and τ = 6) was calculated on raw unfiltered data of L5 acceleration along the anteroposterior (AP), vertical (V) and mediolateral (ML) axis, for both conditions (SEap, SEv and SEml). The difference between SE in DT and ST was calculated for each participant (ΔSE). ΔSE was expressed in percentage of SE in ST. Median (and 25th and 75th percentiles) were obtained for each group. Results: Children and adolescents showed a decrease in complexity from ST to DT condition on all the three axes. Young adults showed an opposite trend on AP and ML directions (Fig. 1). ΔSE (%) results for the three axes (median, 25th and 75th percentiles) Download high-res image (94KB)Download full-size image Fig. 1. ΔSE (%) results for the three axes (median, 25th and 75th percentiles). Discussion: The results of this study suggest that the strategy used while walking during DT is different in childhood and adulthood. Adults’ results are in agreement with those shown by elderlies [2], where gait complexity in AP increased with DT, suggesting a decrease in automaticity. Children’ and adolescents’ results showed an opposite behaviour: it could be argued that they involve a lower amount of cognitive input in walking, when focusing on a cognitive task. These results highlight the relevance of studying movement performance during growth in order to improve our understanding on motor control and its development: future research will have to focus on the interpretation of these results, with particular attention on how physical and cognitive changes affect motor development.

Research question: Is CoM kinematics a descriptive parameter of gait motor development? Could it be a leading factor during gait maturation? Introduction: Independent gait starts generally around age 1, when toddlers show a wide range of walking strategies [1]. As children grow, their gait pattern begins to approximate that of an adult: by age 3, most of the adult kinematic patterns are present, but gait maturation continues until age 6 [2]. Literature shows that variability of gait kinematic is higher in children than in adults [3]: thus, segmental kinematics has not been proved to be representative of gait development. The hypothesis of the present work is that the trajectory of the centre of mass (CoM) is a leading factor during gait maturation, allowing 4- and 6-year old children (4YC and 6YC) to reach steady state points in gait development, despite the shown variability: if this is true, the variability of CoM kinematic should be lower than that of other kinematic variables. Materials and methods: 7 4YC [4 ± 0 years, 101 ± 3 cm, 17 ± 2 kg], 7 6YC [6 ± 0 years, 121 ± 2 cm, 22 ± 1 kg] and 7 young adults [23 ± 1years, 157 ± 8 cm, 61 ± 7 kg] participated in the study. Coordination exercises were used for ensuring children's level of development. Each participant performed 3 times a 5-walk-test. 3D kinematic (SmartD, Bts, Italy) was collected using Plug-in-Gait protocol. One triaxial inertial sensor (Opal, Apdm, US) was positioned at CoM level. For each walking test, joint angles, CoM trajectory and CoM acceleration were obtained. Intra-test and inter-test coefficient of variation (std%) was calculated for each variable (respectively among the 5 walks of each test and among the repetitions of the 5-walk- test). Results: Joint angles results showed higher variability in children than in adults for both the intra-test and the inter-test conditions: e.g. children hip intra/extra rotation and ankle flexion/extension std% were 4 times greater than adults’ for 4YC and twice for 6YC. CoM trajectory in the inter-test condition showed similar std% for the 3 groups, while, in the intra-test, mediolateral (ML) std% was higher in both 4YC and 6YC (5 times for the ML axis and twice for vertical (V) and anteroposterior (AP) axes). In both intra-test and inter-test conditions, children CoM acceleration showed std% similar to adults’ for the AP and the V axis, while higher on the ML one. Discussion: Obtained results support the hypothesis that CoM trajectory is a leading factor during gait maturation and could be used as descriptive parameter: both 4YC and 6YC showed %std of CoM kinematics along the sagittal plane close to the adults’ one, while %std of joint angles was always higher. Moreover, present results suggest that control of gait is focused on the progression of the CoM and not on its lateral stabilization: children variability on the ML axis was always higher than adults’ one.

Research question: Are there significant differences in gait acceleration signal spectrum between young and elderly subjects? And could these improve the understanding of motor control? Introduction: From signals theory the knowledge of spectrum features is the starting point for the signal processing. In particular, know features of gait acceleration signal spectrum of young and elderly subjects could improve the understanding of the multiple factors that contribute to achieve the specific motor task. Studies about the range of gait acceleration frequency are presented in literature; these start from: kinematic data [1], acquired with stereo photogrammetry, and from ground reaction force data [2], acquired with force platform. The first method is affected by the well-known drifts problem; instead the second measures the acceleration of the center of pressure (COP) and not those of the center of mass that is a follower of the COP. The study aims to assess the features of gait acceleration signal spectrum, directly obtained from inertial measurement unit (IMU), in young and elderly subjects. Materials and methods: The study was conducted on 10 healthy young people and 10 elderly subjects. The participants performed an instrumented over ground gait task wearing an IMU located on the trunk at the height of fifth lumbar vertebra. The acceleration signals in antero-posterior, medio-lateral and vertical directions were acquired with a sample frequency of 128 Hz. The Fast Fourier Transform (FFT) of the signals was used to determine: the frequency corresponding to the maximum of the signal spectrum (fMAX) and the frequency corresponding to the median value of the signal spectrum (fMEDIAN). The potential spectrum density (psd) was obtained with the matlab built-in function pwelch. The signal power was calculated integrating the psd. The percentage power at 32, 16, 10, 8 Hz was calculated. Results: For the young population fMAX varies from 1.9 to 3 Hz and fMEDIAN from 28.9 to 32.4 Hz. Instead for the elderly population fMAX is between 1.0 and 2.6 Hz and fMEDIAN from 26.8 to 34.3 Hz. The power analysis showed for young subjects that the signal power is between 99.9% at 32 Hz and 72.9% at 8 Hz. For the elderly population, instead, it varies form 99.2% at 32 Hz to 44.9% al 8 Hz. Discussion: On the medio-lateral axis the frequency range of the elderly is lower than young subjects; this could be explained by the fact that medio-lateral frequencies are influenced by stride time. Instead, for antero-posterior and vertical directions frequency range of the elderly are shifted to the higher frequencies than those of young; this could be due to the muscularity stiffness present in elderly subjects. The percentage power, in all the directions, is lower in elderly than in young subjects; this could be due to the no smooth body control during gait that introduces components at the high frequencies.

Introduction: Gait motor control is a topic of well-known high relevance among the scientific community: its comprehension is indeed fundamental in order to understand what happens in pathologic and/or elderly subjects. The sudden increase in height that usually happens during adolescence can be an interesting environment for understanding how gait motor control works when, having reached a mature manifestation of gait [1], suddenly encounters peripheral constrictions (changes in segment lengths). It is indeed common to observe low gross motor coordination in this population: this could be due to sudden peripheral changes that adolescents have and that affect the output of the controller, which has been previously organized on different segment dimensions. Stability and variability indices [2] can be useful in detecting the manifestation of this lower coordination, i.e. indicating adolescents that undergo a sudden growth as less stable than their not grown peers. Moreover, these indices could give information about the direction/plane on which the motor control encounters more difficulties when sudden segment changes happen. The aim of the present study is to apply stability indices on trunk acceleration data collected during gait of a large group of adolescents. Data will be collected longitudinally in order to evaluate gait changes after height increases. Methods: 280 15-year-old adolescents were included in the study and will be followed longitudinally for one year. Present results are preliminary and regard 20 male subjects: 10 declared to have had a sudden increase in height during the previous three months (more than 3 cm) (Grown, 15 y, 72 ± 15 kg, 174 ± 6 cm) and other 10 not (NotGrown, 15 y, 70 ± 10 kg, 171 ± 6 cm). Measures of acceleration of the trunk (L5 level) were collected using one tri-axial wireless inertial sensor (OPALS, Apdm, USA) (sampling frequency, 128 Hz). The participants were asked to walk at self-selected speed back and forth four times in a 10 m long corridor in two conditions: free walking and walking performing a mental dual task (DT). For all the participants and each condition 30 strides were analyzed [3]: turns were excluded from the analysis. The following methods for quantifying gait stability were applied: stride time variability, Poincaré plots, harmonic ratio, short term Lyapunov exponents, maximum Floquet multipliers, recurrence quantification analysis and multiscale entropy [2]. An unpaired t-test (level of significance of 5%) was performed on the two groups for each method: t-test was right- or left-tailed hypothesizing higher stability in the NotGrown group. Results:t-Test results showed no differences between the two groups for stride time variability, Poincaré plots, harmonic ratio, short term Lyapunov exponents and maximum Floquet multipliers. Recurrence quantification analysis and multiscale entropy showed statistically significant results for the two groups in the DT condition when applied on the AP axis and indicated correctly the NotGrown as more stable than the Grown. Discussion: Preliminary results suggested that during normal walking no stability indices could discern between Grown and NotGrown adolescents. In DT condition, recurrence quantification analysis and multiscale entropy identified the Grown group as less stable than the NotGrown, suggesting that a focused attention to the task make the two groups not discernible, while, during DT, some manifestations of low coordination appeared. Moreover, the AP direction seemed to be the most sensitive to the differences between the two groups: further studies are needed in order to understand if this result is indicative of a focused direction of the motor control during gait. Present results are preliminary and are based on two different groups of adolescents, who declared whether they recently grew or not. More detailed and significant results will be obtained through the longitudinal study on the 280 adolescents included.