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In this work, a flexible and extensive digital platform for Smart Homes is presented, exploiting the most advanced technologies of the Internet of Things, such as Radio Frequency Identification, wearable electronics, Wireless Sensor Networks, and Artificial Intelligence. Thus, the main novelty of the paper is the system-level description of the platform flexibility allowing the interoperability of different smart devices. This research was developed within the framework of the operative project HABITAT (Home Assistance Based on the Internet of Things for the Autonomy of Everybody), aiming at developing smart devices to support elderly people both in their own houses and in retirement homes, and embedding them in everyday life objects, thus reducing the expenses for healthcare due to the lower need for personal assistance, and providing a better life quality to the elderly users.

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.

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.

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.

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: 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.

The assessment of walking function alterations is a key issue to design effective rehabilitative interventions in sub-acute stroke patients. Nevertheless, the objective quantification of these alterations remains a challenge. Clinical rating scales are commonly used in clinical practice, but have been proven prone to errors associated to the evaluator subjective perception. On the other hand, instrumental measurement of trunk acceleration can be exploited for an objective quantitative characterization of gait function, but it is not applied in routine clinical practice, because the resulting quantitative indexes have not been related to the clinically information, conventionally provided by the rating scales. To overcome this limitation, the relationship between the indexes, in specific clinical conditions, and rating scale must be better investigated, to support their exploitability in the clinical practice as a fast and reliable screening tool. Thirty-one sub-acute stroke patients (17 with and 14 without cane) participated in the study. All were assessed with 6 rating scales (MI, TCT, MRI, FAC, WHS, CIRS) and 2 functional tests (2MWT and TUG). Sample Entropy (SEN) and Recurrence Quantification Analysis (RQA) in AP, ML and V directions were calculated over 2MWT and walking section of TUG. The influence of assessment task and cane was analysed, as well as correlation of SEN and RQA indexes with clinical rating scales. SEN and RQA on the medio-lateral plane resulted influenced by the use of the cane, while the correlations between indexes and clinical scales showed that SEN and RQA for antero-posterior direction correlate positively with WHS.

Main topics: Analysis of gait and motor disorders; Movement deviation indexes Introduction and aim: Subjects who suffered a stroke often experience alterations in the normal pattern of walking and a higher fall risk [1]. Clinical rating scales represent the standard approach used by clinicians for motor function assessment of post-stroke patients; this approach is however highly dependent on the clinician's subjective judgement [2]. Instrumental measurements of trunk accelerations during gait resulted promising in the assessment of gait stability and fall risk in healthy elderly subjects [3]. A more reliable and objective quantification of motor function could be obtained from the integration of stability measures and clinical rating scales. In order to evaluate the potential clinical benefits derivable from this approach, the association between stability measures and clinical scales has to be assessed. The aim of the present study is the assessment of the relationship between instrumental gait stability measures of trunk accelerations and some of the most used clinical rating scales in a sample of post-acute stroke patients. Patients/materials and methods: Thirty-three subjects post-acute stroke patients with hemiparesis (56 ± 14 years, 71 ± 14 kg) participated in the study. Seventeen subjects were not able to walk without a cane. Data were collected at Sol et Salus Hospital (Rimini, Italy). Motricity Index (MI), Trunk Control Test (TCT), Functional Ambulation Category (FAC), Walking Handicap Scale (WHS), Rivermead Mobility Index (RMI), Cumulative Illness Rating Scale (SI and CI), Timed-Up and Go Test (TUG) and Two Minute Walk Test (2MWT) were administered to subjects by the same operators. The 2MWT was administered with the addition of an IMU located on the trunk, at the height of the fifth lumbar vertebra. Four gait stability measures, namely Harmonic Ratio (HR), Index of Harmonicity (IH), Multiscale Entropy (MSE), and Recurrence Quantification Analysis (RQA), were calculated on trunk acceleration signal during gait obtained from 2MWT. Each measure was calculated for anterior-posterior (AP), mediolateral (ML) and vertical (V) acceleration directions. Log transformed measures were then used as inputs for linear regression models. Results: Subjects who used a cane showed a high correlation between MSE, RQA and TCT, RMI. More sparse but significant correlation has been found between MSE and WHS, CIRS. IH showed no correlation with clinical parameters. Subjects who were able to walk without a cane showed high correlation values between MSE, RQA and TUG, 2MWT and WHS. TUG, 2MWT and SI correlated in a lesser extent with HR. IH showed high correlation values with TUG and RMI; RMI correlated with MSE and RQA also. Discussion and conclusions: In subjects who walked with a cane, correlations between TCT and MSE were particularly consistent, highlighting an affinity between the instrumental measure of complexity of trunk acceleration and the clinical assessment of trunk control. For subjects who were able to walk without a cane TUG, 2MWT showed high correlations with stability measures, in particular with MSE and RQA (mainly in the ML direction), highlighting the importance of the medio-lateral control of the trunk during gait. In conclusion, gait stability measures based on trunk accelerations (in particular MSE and RQA) showed promising correlation with clinical scales in stroke patients, and could complement the standard clinical scores in the assessment of locomotor performance of subjects with stroke, helping clinicians and physical therapists in the patient's rehabilitation process. Moreover, the use of instrumental measurements could lead, in the future, to a more reliable quantification of locomotor features, allowing avoiding inter-operator differences.

Introduction: Instrumented gait assessment is traditionally carried out asking subjects to merely walk (ST). Such condition does not represent an everyday walking situation; indeed, in the daily life, locomotion requires to meet individual goals, to adapt to the environmental constrains and commonly involves cognitive tasks. Dual-task (DT) paradigms have been used to assess a shift in gait control strategy in real life situations [1]. In particular, variability and stability indexes used to motor control assessment, could be useful to evaluate cognitive motor interference during walking. The aim of the present study is to evaluate how the DT condition changes the stability and variability indexes. Methods: 16 young adults (25YA) participated to the study. Measures of trunk acceleration (L5 level) were collected using one tri-axial wireless inertial sensor. The participants were asked to walk for 250 m: at self-selected speed (ST) and counting backward aloud by 7 from a random starting number (DT). For all the participants and each condition 5 variability indexes – Standard Deviation (SD), Coefficient of Variation (CV), Non-stationary Index (NI), Inconsistency of Variance (IV) and Poincaré Plots (PSD1/PSD2) – and 6 stability indexes – short/long-term Lyapunov Exponents (sLE/lLE), Harmonic Ratio (HR), Index of Harmonicity (IH), Multiscale Entropy (MSE) and Recurrence Quantification Analysis (RQA) – were calculated on non-overlapping windows of 20 strides and on the whole signal. Kruskal–Wallis tests (p-value at 5%) were performed to evaluate DT effects. Results: Analyses performed on the 6 portions of 20 strides showed, in general, three different behaviours: none/all the portions were statistically significant or only the first portions were significantly different. In particular, for HR, was found that the first two portions showed statistical differences. Kruskal–Wallis test performed between indexes calculated on the entire signal did not show statistical differences (Fig. 1). Discussion: Analyses on the six portions of 20 strides suggest that indexes were influenced by DT condition; furthermore, indicate the existence of an adaptation, by the subjects, to the DT conditions. The statistical results about the indexes calculated on the entire signal were not in agreement with those in literature [2,3]. A non-sufficient analyzed strides number, taken into account in the previous studies, to guarantee that the indexes reached steady values [4] could explain these discrepancies. In conclusion the obtained results highlight the importance of a standardized methodology to compute indexes and suggest that DT condition during trial seems to fit with the walking pattern of the ST. Further researches are needed to understand the physiological and motor control meaning of the adaptation phases.

Gait analysis of subjects with short and non-uniform gait is difficult using the common commercial force platforms. The present work consists in the design, based on finite element method (FEM) analysis, of a force platform of small dimensions (0.40x0.40 m) considering static and dynamic simulation of its behavior. The aim of this project is to improve, with a simple and low cost structure, the instrumentation available for the gait analysis of children and neurologic patients. The applicability of gait analysis to children and neurologic patients, improved the flexibility of force platforms without loosing the performance provided by traditional force platforms (e.g. for postural analysis)

Research question: Are gait variability and stability indexes representative of specific diseases? And can they explain the physiological deficit of motor control in these pathologies? Introduction: The importance of stability and variability indexes in the assessment of motor functionality is known [1–4]; however much effort is still required to identify which indexes are representative of specific diseases and consequently which physiological aspects each index analyzes. To improve these aspects the ability of the indexes to discriminate (a) young healthy subjects from pathological ones and (b) different pathologies was assessed. Materials and methods: The study was conducted on 10 healthy young people (Y), 10 elderly subjects (E), 10 stroke patients (S) and 10 subjects with choreic movement disorder (C). The participants performed an instrumented over ground gait task wearing three inertial measurement units (IMUs): one located on the trunk at the height of the fifth lumbar vertebra to acquire trunk acceleration, and two attached above the ankles, allowing the strides detection according to [5]. 5 stability and 7 variability indexes were calculated on stride time and trunk acceleration data during gait, for antero-posterior, medio-lateral and vertical directions. Statistical analyses were performed (a) to verify if the indexes were able to discriminate young healthy subjects from pathological ones and (b) to evaluate the ability of the indexes to describe different pathologies. Results: Two variability indexes (Standard Deviation and Coefficient of Variation) and one stability index (Multiscale Sample Entropy) were able to discriminate pathological people from healthy young ones. None of the evaluated indexes was able to discriminate all the different pathologies (S C E); conversely, clusters of indexes representative of elderly and stroke subjects were found. Discussion: The obtained results shown that the variability of the stride time and the complexity of acceleration signals are able to discriminate healthy young people from pathological ones; this not surprising since gait pattern of healthy and pathological subjects are very different. Indeed these features are the first to be influenced by the ability of the subject to implement a right motor-control. The indexes that are able to discriminate S from C and E are about the smoothness of the signal. This could be explained with the nature of the pathologies; indeed stroke subjects have important impairments only in one side of the body, instead old age and chorea are degenerative diseases that affect the whole body. The indexes that are able to discriminate E from C and S are about the recurrences of the signal. This could suggest that the variability of gait pattern is lower in elderly than in chorea and stroke subjects.

The understanding of locomotor stability is a critical issue in the assessment of subjects with high level of fall risk either pathological (e.g. stroke subjects) or elderly. Clinical assessment of fall risk is typically based on clinical rating scales; however, this approach heavily relies on the clinician’s subjective judgment. Instrumental stability and variability indexes of gait can represent a promising solution for the objective quantification of locomotor function and fall risk. Furthermore clusters of stability and variability indexes give important information about the clinical deficits of subjects that could be the causes of the fall risk. An important step for the improvement of the assessment of fall risk is to analyze the subject’s walk not only in the laboratory but also in his daily life. This is possible with the implementation of the stability and variability indexes in a portable device. Mobile phone is the ideal device for this goal. Indeed it is user friendly, cheap and although the IMUs mounted on standard smart phones have nothing to envy to other commercially available devices, but sampling frequency at 100 or 200 Hz is not compatible with the computational characteristics. The influence of reduced sampling frequency on the assessment of variability and stability indexes used for the monitoring must be assessed, and this is the aim of the present work. The preliminary obtained results show that the influence of the sampling frequencies in the computation of the stability and variability indexes is not an obstacle to move the assessment and monitoring of fall risk from the laboratory to a portable device.

Main topics: Experimental studies in human movement science; Movement deviation indexes Introduction and aim: Falls in the elderly represent a major community and public health problem, with large clinical and economic consequences [1]. The understanding of locomotor stability is a critical issue in clinical assessment procedures. Clinicians typically use clinical rating scales of motor function tests for fall risk assessment purposes. However, this approach highly relies on the clinician's subjective judgement [2]. Variability and stability measurements of stride time and trunk accelerations during gait resulted promising in the assessment of gait stability and fall risk in healthy elderly subjects [3] and could lead to a more reliable and objective quantification of motor function, potentially representing a valid and objective complement to clinical rating scales. For an effective exploitation in clinical practice, the association between stability measures and clinical scales has to be assessed. The aim of the present study is the assessment of the relationship between instrumental variability and stability measures based on trunk accelerations during gait and some widely used clinical rating scales. Patients/materials and methods: Seventy community dwelling old adults (35 males and 35 females, 76 ± 7 years, 76 ± 13 kg, 168 ± 9 cm) participated in the study. Barthel Index (BI), Cumulative Illness Rating Scale (CIRS) and Mini-BESTest (MBT) were administered to subjects by the same operators. Due to time/location constraints, MBT was only administered to 39 subjects (19 males and 20 females, 76 ± 6 years, 77 ± 12 kg, 168 ± 8 cm). Subjects also performed an instrumented over-ground gait task (on a 100 m long road) wearing an IMU located on the trunk, at the height of the fifth lumbar vertebra. Eleven gait variability/stability measures were calculated on stride time and trunk acceleration data during gait, namely Standard Deviation (SD), Coefficient of Variation (CV), Nonstationary Index (NI), Inconsistency of Variance (IV), Poincaré Plots (PSD1/PSD2), Maximum Floquet Multipliers (maxFM), short/long-term Lyapunov exponents (sLE/lLE), Harmonic Ratio (HR), Index of Harmonicity (IH), Multiscale Entropy (MSE) and Recurrence Quantification Analysis (RQA). Each measure was calculated for anterior–posterior (AP), medio-lateral (ML) and vertical (V) acceleration directions. In order to assess the correlation between clinical parameters and variability/stability measures, log transformed measures were used as inputs for linear regression models. Results: SD, CV, PSD1 and PSD2 showed negative correlation with BI and MBT. The only stability measure that correlated (positively) with MBT and BI was IH in the ML direction. CIRS correlated with MSE (ML and V directions), maxFM and lLE. Discussion and conclusions: BI and MBT negatively correlated with stride time variability measures, meaning that a relationship exists between the deterioration of the overall motor functionality and the increase in stride time variability. BI and MBT were also found to be linked to the harmonicity of acceleration signal in the ML direction, confirming the importance of ML trunk oscillations during gait for functionality assessment. CIRS correlated with stability measures, in particular with MSE in ML and V directions, suggesting a link between cumulative illness and gait stability in elderly subjects. Moreover, MSE was previously found to be linked to fall history in elderly subjects, and should hence to be taken into consideration for gait stability assessment. In conclusion, gait variability and stability measures showed promising correlation with clinical rating scales in the elderly population, and could be considered for complementing the standard clinical scores in the assessment of fall risk. A more reliable quantification of locomotor features could be obtained from instrumental measurements, allowing to avoid inter-operator differences.

Clinical assessment of walking deficits in post-stroke patients is typically based on clinical rating scales. This approach is however highly dependent on the clinician’s subjective judgement. Objective tools for the quantification of locomotor function are needed, and instrumental measures of gait stability could represent a promising solution. The integration of the two approaches could lead to a more reliable quantification of locomotor deficits in post-stroke patients, and improving the understanding of the physiological correlate of gait stability measures. The aim of the present study was to assess the association between instrumental stability measures based on trunk accelerations during gait and clinical rating scales in a sample of post-acute stroke subjects.

Introduction: The use of inertial sensors, placed at approximately CoM level (L5 level), is today a common practice in gait analysis [1]: CoM acceleration data allow indeed evaluating spatio-temporal gait parameters [2] and characterizing different populations [3]. Frequency domain analysis of the CoM acceleration signal has been already proposed in literature, in order to assess the range of frequency spectrum and its dependency on the motor task [4–6] or in order to evaluate characteristics of the signal in relation to task event (e.g. impact-related shock, Parkinson's freezing) [7,8]. The aim of this study was to investigate the use of the frequency domain analysis of CoM acceleration in characterizing gait maturation from childhood to adulthood, evidencing deterioration of gait performance during ageing. Methods: The study was conducted on: 7 toddlers at two weeks of walking experience (T2wks, 13 ± 2 mo, 10 ± 2 kg, 78 ± 4 cm), 7 toddlers at 6 months of walking experience (T6mo, 18 ± 2 mo, 11 ± 2 kg, 82 ± 2 cm), 7 4-year old children (4YC, 4 y, 16 ± 2 kg, 101 ± 3 cm), 7 6-year old children (6YC, 6 y, 23 ± 1 kg, 121 ± 2 cm), 7 adolescents (15YA, 15 y, 60 ± 13 kg, 162 ± 6 cm), 7 young adults (25YA, 25 ± 1 y, 171 ± 9 cm, 67 ± 14 kg) and 7 elderlies (E, 75 ± 7 y, 77 ± 11 kg, 167 ± 6 cm). The participants performed an instrumented over ground gait task wearing a tri-axial wireless inertial sensors (OPALS, Apdm, USA) (fs 128 Hz) located on L5. Ten consecutive strides, for all the participants, were analyzed [9]. The FFT of the acceleration signals was used to determine the frequency corresponding to the maximum of the monolateral signal spectrum (fMAX). The signal power (PW) was calculated integrating the potential spectrum density (psd), obtained with the Matlab built-in function pwelch. Then PW was normalized with the maximum value of it, obtaining the normalized signal power (PW%). The frequencies corresponding to the 50% (f50%) and 98% (f98%) of the PW%. were calculated. fMAX, f50% and f98% were calculated along the three axes (AP, ML V). The estimated parameters were tested with gaussianity test in such way was possible performed the right statistical analysis: Kruskal–Wallis test with a p-value of 5%. When age effect was found, a multiple comparison test was performed. Results: Kruskal–Wallis results showed effect of age on all the features in V direction and on f98% and f50% in AP direction. No significant results were found in ML direction. In Fig. 1a and b are showed 25° 50° and 75° percentiles of fMAX_AP and fMAX_V respectively. Colours indicate differences found by the multiple comparison test for T2wks group (blue): red indicates statistical differences and grey no statistical differences. Fig. 1 Download high-res image (67KB)Download full-size image Fig. 1. Discussion: The results of the present work indicate that f50%, f98% and fMAX can be relevant and descriptive parameters of gait development. In particular, fMAX_AP, changes from high to low values with the increasing of the age and could describe improvement and deterioration of the motor development; moreover fMAX_V and f98%_V discern between immature and mature gait during gait development and could be used as an index of deterioration of gait performance during ageing.

Main topics: Analysis of gait and motor disorders; Technical developments in movement science Introduction and aim: Gait analysis of subjects with short and non-uniform gait, typical children, children with cerebral palsy, elderly and stroke patients, can result critical in terms of ground reaction force (GRF) quantification with traditional force platforms. The standard de facto of commercial force platforms dimension (0.60 m × 0.40 m) can determine problems resulting from the double contact of the foot on the same platform. The aim of this work is the design of a small modular, six components, force platform (0.40 m × 0.40 m) to solve the problem of double contact, maintaining the performance of commercial larger ones. The simplicity of the design and materials used allows the use of multiple force platforms at low cost. Electronics dedicated to the acquisition of the output signal is not required because a commercial evaluation board can be exploited, that is able to independently manage the output of the strain gauges. This solution simplifies the realization of instrumented corridors. Patients/materials and methods: The design of the proposed small modular force platform [1] was performed to obtain a performance comparable to that of commercial force platforms. The total dimension of the force platform is: 0.40 m × 0.40 m × 0.105 m. The minimum number of mono-axial strain gauges are used for deformation sensing: six for each post, longitudinally arranged. The output of each strain gauge is directly provided as input to a commercial evaluation board. This removes the need for ad-hoc electronics for signal acquisition. Static analysis was performed to estimate the platform calibration matrix. 576 simulations were implemented considering applied forces varying between −200 N and 200 N for Fx and Fy and between −2000 N and -200 N for Fz, in 9 different points of application. Which were used in order to cover most of the surface of the platform. Eighty-four additional simulations were performed to test the calibration matrix and quantify the error that the system commits in the estimation of applied loads and moments, which were not exploited in the estimation of the calibration matrix. Results: The median error made in the determination of the forces is between −0.0378% and 0.0041%. The maximum error made in the determination of the forces ranges from a minimum of 0.0325% to a maximum of 0.8075%. The median error made in the determination of the moments is between 0.0028% and 0.0372%. The maximum error made in the determination of the moments is in Mx 0.1112% at −45 Nm, in My 0.2401% at 15 Nm and in Mz 3.435% at 10 Nm. The median and the maximum error in the determination of the forces and moments, based on the calculated calibration matrix, resulting from the 84 additional simulations are illustrated in Tables 1 and 2.

The gait analysis of subjects with short and non-uniform gait is difficult using the common commercial force platforms. The present work consists in the design, based on finite element method (FEM) analysis, of a force platform of two different dimensions (0.40 × 0.40 m and 0.80 × 0.40 m) considering static and dynamic simulation of their behavior. The aim of this project is to improve, with a simple, low cost and flexible structure, the instrumentation available for the gait analysis of children, neurologic patients and in general the most common clinical cases. The applicability of gait analysis to children, neurologic patients ECC can be improved by the flexibility of force platforms without losing the performance provided by traditional force platforms (e.g., for postural analysis).