Interest of a Hospital-Based Geriatric Living Lab among Inpatients with Neurocognitive Disorders: The ALLEGRIA Cross-Sectional Study.

INTRODUCTION: The objectives of this study were to determine the participation rates, levels of engagement, and abilities to answer User eXperience (UX) questionnaires according to the presence and severity of major neurocognitive disorders (MNCD) among participants involved in gerontechnological experimentations within a hospital-based geriatric clinical living lab. METHODS: Cross-sectional analysis examining all consecutive geriatric patients involved in the Allegro living lab experimentations, separated according to the presence and severity of MNCD. Participation rates were assessed using the "Task-Based Experiment"-type User eXperience (TBE-UX). Participation was considered successful if patients fully completed the TBE-UX experimental procedure. Engagement level was characterized using a five-point scale: interactive, constructive, active, passive, and disengaged. The abilities to answer UX questionnaires were characterized using a five-point scale from "no completion" to "completion in autonomy." RESULTS: 313 patients were included. All patients without MNCD and with mild MNCD fully completed the TBE-UX procedures. Their engagement behaviors were rather active and constructive. All patients without MNCD and 88% of those with mild MNCD were able to fully complete the UX questionnaires. 96.2% of the patients with moderate MNCD fully followed the TBE-UX procedures. Their engagement behaviors were mainly active or passive. 64.2% were able to fully complete the UX questionnaires. 76.5% of the patients with severe MNCD fully followed the TBE-UX procedures. Their engagement behaviors were mainly passive or disengaged. 35.3% were able to fully complete the UX questionnaires. CONCLUSION: Living lab experimentations appear feasible with older adults, even with those with MNCD. Task support can be offered to those with severe MNCD.

Gait kinematics based on inertial measurement units with the sensor-to-segment calibration and multibody optimization adapted to the patient's motor capacities, a pilot study.

INTRODUCTION: Inertial Measurement Units (IMUs) offer a promising alternative to optoelectronic systems to obtain joint lower-limb kinematics during gait. However, the associated methodologies, such as sensor-to-segment (S2S) calibration and multibody optimization, have been developed mainly for, and tested on, asymptomatic subjects. RESEARCH QUESTION: This study proposes to evaluate two personalizations of the methodology used to obtain lower-body kinematics from IMUs with pathological subjects: S2S calibration and multibody optimization. METHODS: Based on previous studies, two decision trees were developed to select the best (in terms of accuracy and repeatability) S2S methods to be performed by the patient given his/her abilities. The multibody optimization was personalized by limiting the kinematic chain range of motion to the results of the subject's clinical examination. These two propositions were tested on 12 patients with various gait deficits. The patients were equipped with IMUs and reflective markers tracked by an optoelectronic system. They had to perform the postures and movements selected by the decision trees then walk back and forth along a walkway. Gait kinematics obtained from the IMUs directly (referred to as Direct kinematics), and after multibody optimization performed via the OpenSim software using the generic range of motion (referred to as Generic Optimized kinematics), and using the personalized range of motion (referred to as Personalized Optimized kinematics) were compared to those obtained with the Conventional Gait Model through Root Mean Square Errors (RMSE), Correlation Coefficients (CC) and Range of Motion differences (ΔROM). RESULTS: The RMSEs were smaller than 8.1° in the sagittal plane but greater than 7.4° in the transverse plane. The CCs, between 0.71 and 0.99 in the sagittal plane, deteriorate sharply in the frontal and transverse planes where they only measured between 0.15 and 0.68. The ΔROMs were mostly below 8.3°. Optimized kinematics did not improve compared to Direct kinematics. SIGNIFICANCE: The personalization of the proposed S2S calibration method showed encouraging results, whereas multibody optimization did not impact the resulting joint kinematics.

Sensor-to-Bone Calibration with the Fusion of IMU and Bi-Plane X-rays.

Inertial measurement units (IMUs) need sensor-to-segment calibration to measure human kinematics. Multiple methods exist, but, when assessing populations with locomotor function pathologies, multiple limitations arise, including holding postures (limited by joint pain and stiffness), performing specific tasks (limited by lack of selectivity) or hypothesis on limb alignment (limited by bone deformity and joint stiffness). We propose a sensor-to-bone calibration based on bi-plane X-rays and a specifically designed fusion box to measure IMU orientation with respect to underlying bones. Eight patients undergoing total hip arthroplasty with bi-plane X-rays in their clinical pathway participated in the study. Patients underwent bi-plane X-rays with fusion box and skin markers followed by a gait analysis with IMUs and a marker-based method. The validity of the pelvis, thigh and hip kinematics measured with a conventional sensor-to-segment calibration and with the sensor-to-bone calibration were compared. Results showed (1) the feasibility of the fusion of bi-plane X-rays and IMUs in measuring the orientation of anatomical axes, and (2) higher validity of the sensor-to-bone calibration for the pelvic tilt and similar validity for other degrees of freedom. The main strength of this novel calibration is to remove conventional hypotheses on joint and segment orientations that are frequently violated in pathological populations.

Consistency of muscle activation signatures across different walking speeds.

BACKGROUND: Using a machine learning algorithm, individuals can be accurately identified from their muscle activation patterns during gait, leading to the concept of individual muscle activation signatures. RESEARCH QUESTION: Are muscle activation signatures robust across different walking speeds? METHODS: We used an open dataset containing electromyographic (EMG) signals from 8 lower limb muscles in 50 asymptomatic adults walking at 5 speeds (extremely slow, very slow, slow, spontaneous, and fast). A machine learning approach classified the EMG profiles based on similar (intra-speed classification) or different (inter-speed classification) walking speeds as training and testing conditions. RESULTS: Intra-speed median classification rates of muscle activation profiles increased with walking speed, from 92 % for extremely slow, to 100 % for self-selected fast walking conditions. Inter-speed median classification rates increased when the speed of the training condition was closer to that of the testing condition. Higher median classification rates were found across slow, spontaneous, and fast walking speed conditions, from 56 % to 96 %, compared with classification rates involving extremely and very slow walking speed conditions, from 6 % to 62 %. SIGNIFICANCE: Our findings reveal that i) muscle activation signatures are detectable for a large range of walking speeds, even those involving different gait strategies (intra-speed median classification rates from 92 % to 100 %), and ii) muscle activation signatures observed during very low walking speeds are not consistent with those observed at higher speeds, suggesting a difference in motor control strategy. Caution should therefore be exercised when assessing gait deviations of a slow walking patient against a normative database obtained at higher speed. Identifying the robustness of individual muscle activation signatures across different movements could help in detecting changes in motor control, otherwise difficult to detect on classical time-varying EMG patterns.

A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates.

Human motion capture and analysis could be made easier through the use of wearable devices such as inertial sensors and/or pressure insoles. However, many steps are still needed to reach the performance of optoelectronic systems to compute kinematic parameters. The proposed dataset has been established on 10 asymptomatic adults. Participants were asked to walk at different speeds on a 10-meters walkway in a laboratory and to perform different movements such as squats or knee flexion/extension tasks. Three-dimensional trajectories of 69 reflective markers placed according to a conventional full body markerset, acceleration and angular velocity signals of 8 inertial sensors, pressure signals of 2 insoles, 3D ground reaction forces and moments obtained from 3 force plates were simultaneously recorded. Eight calculated virtual markers related to joint centers were also added to the dataset. This dataset contains a total of 337 trials including static and dynamic tasks for each participant. Its purpose is to enable comparisons between various motion capture systems and stimulate the development of new methods for gait analysis.

Three-Dimensional Lower-Limb Kinematics from Accelerometers and Gyroscopes with Simple and Minimal Functional Calibration Tasks: Validation on Asymptomatic Participants.

The use of inertial measurement units (IMUs) to compute gait outputs, such as the 3D lower-limb kinematics is of huge potential, but no consensus on the procedures and algorithms exists. This study aimed at evaluating the validity of a 7-IMUs system against the optoelectronic system. Ten asymptomatic subjects were included. They wore IMUs on their feet, shanks, thighs and pelvis. The IMUs were embedded in clusters with reflective markers. Reference kinematics was computed from anatomical markers. Gait kinematics was obtained from accelerometer and gyroscope data after sensor orientation estimation and sensor-to-segment (S2S) calibration steps. The S2S calibration steps were also applied to the cluster data. IMU-based and cluster-based kinematics were compared to the reference through root mean square errors (RMSEs), centered RMSEs (after mean removal), correlation coefficients (CCs) and differences in amplitude. The mean RMSE and centered RMSE were, respectively, 7.5° and 4.0° for IMU-kinematics, and 7.9° and 3.8° for cluster-kinematics. Very good CCs were found in the sagittal plane for both IMUs and cluster-based kinematics at the hip, knee and ankle levels (CCs > 0.85). The overall mean amplitude difference was about 7°. These results reflected good accordance in our system with the reference, especially in the sagittal plane, but the presence of offsets requires caution for clinical use.

Gait stability in ambulant children with cerebral palsy during dual tasks.

AIM: The aim of this cross-sectional study was to measure the effect of dual tasks on gait stability in ambulant children with cerebral palsy (CP) compared to typically developing (TD) children. METHODS: The children of the CP (n = 20) and TD groups (n = 20) walked first without a dual task, then while counting forward and finally while alternatively naming fruits and animals (DTf/a). They then completed the same cognitive exercises while sitting comfortably. We calculated the distance between the foot placement estimator (FPE) and the real foot placement in the anterior direction (DFPEAP) and in the mediolateral direction (DFPEML) as a measure of gait stability, in a gait laboratory using an optoelectronic system. Cognitive scores were computed. Comparisons within and between groups were analysed with linear mixed models. RESULTS: The dual task had a significant effect on the CP group in DFPEAP and DFPEML. The CP group was more affected than the TD group during dual task in the DFPEML. Children in both groups showed significant changes in gait stability during dual tasks. INTERPRETATION: The impact of dual task on gait stability is possibly due to the sharing of attention between gait and the cognitive task. All children favoured a 'posture second' strategy during the dual task of alternatively naming animals and fruits. Children with CP increased their mediolateral stability during dual task.

Simple rule to automatically recognize the orientation of the sagittal plane foot angular velocity for gait analysis using IMUs on the feet of individuals with heterogeneous motor disabilities.

Automatic sensor-to-foot alignment is required in clinical gait analysis using inertial sensors to avoid assumptions about sensors initial positions and orientations. Numerous studies have proposed alignment methods. The current study aimed at describing and accessing the performance of a simple rule to automatically recognize the orientation of the sagittal plane foot angular velocity that can be used with any alignment method and any populations including individuals with severe motor disorders such as patients with cerebral palsy (CP). Fifty-five participants (15 healthy, 15 with CP and 25 with various other motor disorders) wore IMUs on both feet during one or several visits of clinical gait analysis (CGA) with optical motion capture system as reference. The foot coordinate system was determined using acceleration during motionless periods and angular velocity during walking, as previously described in the literature. Based on the foot sagittal plane angular velocity, a novel rule is introduced to determine the latest uncertainty related to mediolateral axis direction which often causes errors. It consisted of massively filtering the signal and applying a simple peak detection, omitting the double peaks with the same sign. The time between the negative and positive peaks can inform on the axis direction. This verification showed excellent results with 99,94% sensibility against the reference. This simple rule could be used to further improve existing sensor-to-segment algorithms with inertial sensors located on the feet, and thus improve pathological gait analysis.

[New tools for movement assessment in children with motor disabilities]. / Nouveaux outils d'évaluation du mouvement chez l'enfant avec handicap moteur.

Until recently, movement analysis of children with motor disabilities has mainly relied on in-lab measurements using optoelectronic systems. The development of new tools is mainly inspired from mainstream devices, such as video cameras associated with artificial intelligence or inertial sensors. These tools have extended the assessment of movement in these children beyond traditional movement analysis laboratories, to take an interest in their movements in everyday life. Through the complementarity of these measurements (and associated tools), which the use of is becoming mainstream, a more exhaustive understanding of children's motor disorders and their impacts will allow clinicians to optimize their therapeutic management.

Jusqu'à récemment l'analyse du mouvement chez l'enfant avec handicap moteur s'est principalement appuyée sur des mesures détaillées effectuées en laboratoire à l'aide de systèmes optoélectroniques. Le développement de nouveaux outils de mesure s'appuie sur des dispositifs grand public, tels que les caméras vidéo associées à de l'intelligence artificielle ou les capteurs inertiels. Ces outils ont permis d'étendre le champ d'exploration du mouvement de ces enfants hors des laboratoires traditionnels d'analyse du mouvement pour s'intéresser à leurs mouvements dans la vie quotidienne. Par la complémentarité de ces mesures (et outils associés), dont l'utilisation est appelée à se démocratiser, une compréhension plus exhaustive des troubles moteurs de l'enfant et de ses impacts permettra d'optimiser leur prise en charge thérapeutique.

Reliability of single-day walking performance and physical activity measures using inertial sensors in children with cerebral palsy.

BACKGROUND: There is a lack of objective and reliable tools to measure walking performance in children with cerebral palsy (CP). OBJECTIVE: To evaluate the reliability of inertial measurement units (IMUs) measuring daily life walking performance and physical activity (PA) in children with CP and healthy controls. METHODS: Algorithms were developed to analyse data collected with IMUs during 2 standard school days of the same week and 1 weekend day in 15 children with CP and 14 controls. Additionally, within a clinical trial, 10 children with CP were measured twice, on the same weekday 2 to 4 weeks apart. Relative and absolute reliabilities of PA (% time walking, standing, sitting/lying) and gait parameters (e.g., velocity, cadence) were evaluated by using the intraclass correlation coefficient (ICC) and minimal detectable change (MDC95), comparing 2 school days of the same week, a school day with a weekend day, and the same weekday 2 to 4 weeks apart. RESULTS: For the 15 children with CP (mean [SD] age 13.5 [3.4] years), ICCs were very high (0.70-0.98) when comparing gait parameters for 2 school days. ICCs were lower when comparing 2 school days for 14 control children (mean [SD] age 13.9 [3.0] years) and lowest when comparing a school day with a weekend day for both CP and control children. ICCs for PA were 0.90-0.91 when measuring the same weekday 2 to 4 weeks apart but were very low when comparing 2 school days of the same week or a school day with a weekend day. MDC95 values were high for both groups and all comparisons but comparable with findings of in-lab studies of similar parameters. CONCLUSIONS: Our IMU and algorithm setup appears to be a reliable tool to measure daily life gait parameters in children with CP when repeatedly measured on 2 school days. PA was also reliably assessed but when measuring the same school day some weeks apart. However, the high MDC95 values question whether the setup can be used as a responsive outcome measure of interventions.

Multidimensional Measures of Physical Activity and Their Association with Gross Motor Capacity in Children and Adolescents with Cerebral Palsy.

The current lack of adapted performance metrics leads clinicians to focus on what children with cerebral palsy (CP) do in a clinical setting, despite the ongoing debate on whether capacity (what they do at best) adequately reflects performance (what they do in daily life). Our aim was to measure these children's habitual physical activity (PA) and gross motor capacity and investigate their relationship. Using five synchronized inertial measurement units (IMU) and algorithms adapted to this population, we computed 22 PA states integrating the type (e.g., sitting, walking, etc.), duration, and intensity of PA. Their temporal sequence was visualized with a PA barcode from which information about pattern complexity and the time spent in each of the six simplified PA states (PAS; considering PA type and duration, but not intensity) was extracted and compared to capacity. Results of 25 children with CP showed no strong association between motor capacity and performance, but a certain level of motor capacity seems to be a prerequisite for the achievement of higher PAS. Our multidimensional performance measurement provides a new method of PA assessment in this population, with an easy-to-understand visual output (barcode) and objective data for clinical and scientific use.

Walking Speed of Children and Adolescents With Cerebral Palsy: Laboratory Versus Daily Life.

The purpose of this pilot study was to compare walking speed, an important component of gait, in the laboratory and daily life, in young individuals with cerebral palsy (CP) and with typical development (TD), and to quantify to what extent gait observed in clinical settings compares to gait in real life. Fifteen children, adolescents and young adults with CP (6 GMFCS I, 2 GMFCS II, and 7 GMFCS III) and 14 with TD were included. They wore 4 synchronized inertial sensors on their shanks and thighs while walking at their spontaneous self-selected speed in the laboratory, and then during 2 week-days and 1 weekend day in their daily environment. Walking speed was computed from shank angular velocity signals using a validated algorithm. The median of the speed distributions in the laboratory and daily life were compared at the group and individual levels using Wilcoxon tests and Spearman's correlation coefficients. The corresponding percentile of daily life speed equivalent to the speed in the laboratory was computed and observed at the group level. Daily-life walking speed was significantly lower compared to the laboratory for the CP group (0.91 [0.58-1.23] m/s vs 1.07 [0.73-1.28] m/s, p = 0.015), but not for TD (1.29 [1.24-1.40] m/s vs 1.29 [1.20-1.40] m/s, p = 0.715). Median speeds correlated highly in CP (p < 0.001, rho = 0.89), but not in TD. In children with CP, 60% of the daily life walking activity was at a slower speed than in-laboratory (corresponding percentile = 60). On the contrary, almost 60% of the daily life activity of TD was at a faster speed than in-laboratory (corresponding percentile = 42.5). Nevertheless, highly heterogeneous behaviors were observed within both populations and within subgroups of GMFCS level. At the group level, children with CP tend to under-perform during natural walking as compared to walking in a clinical environment. The heterogeneous behaviors at the individual level indicate that real-life gait performance cannot be directly inferred from in-laboratory capacity. This emphasizes the importance of completing clinical gait analysis with data from daily life, to better understand the overall function of children with CP.

Comparison of gait characteristics between clinical and daily life settings in children with cerebral palsy.

Gait assessments in standardized settings, as part of the clinical follow-up of children with cerebral palsy (CP), may not represent gait in daily life. This study aimed at comparing gait characteristics in laboratory and real life settings on the basis of multiple parameters in children with CP and with typical development (TD). Fifteen children with CP and 14 with TD wore 5 inertial sensors (chest, thighs and shanks) during in-laboratory gait assessments and during 3 days of daily life. Sixteen parameters belonging to 8 distinct domains were computed from the angular velocities and/or accelerations. Each parameter measured in the laboratory was compared to the same parameter measured in daily life for walking bouts defined by a travelled distance similar to the laboratory, using Wilcoxon paired tests and Spearman's correlations. Most gait characteristics differed between both environments in both groups. Numerous high correlations were found between laboratory and daily life gait parameters for the CP group, whereas fewer correlations were found in the TD group. These results demonstrated that children with CP perform better in clinical settings. Such quantitative evidence may enhance clinicians' understanding of the gap between capacity and performance in children with CP and improve their decision-making.

A Personalized Approach to Improve Walking Detection in Real-Life Settings: Application to Children with Cerebral Palsy.

Although many methods have been developed to detect walking by using body-worn inertial sensors, their performances decline when gait patterns become abnormal, as seen in children with cerebral palsy (CP). The aim of this study was to evaluate if fine-tuning an existing walking bouts (WB) detection algorithm by various thresholds, customized at the individual or group level, could improve WB detection in children with CP and typical development (TD). Twenty children (10 CP, 10 TD) wore 4 inertial sensors on their lower limbs during laboratory and out-laboratory assessments. Features extracted from the gyroscope signals recorded in the laboratory were used to tune thresholds of an existing walking detection algorithm for each participant (individual-based personalization: Indiv) or for each group (population-based customization: Pop). Out-of-laboratory recordings were analyzed for WB detection with three versions of the algorithm (i.e., original fixed thresholds and adapted thresholds based on the Indiv and Pop methods), and the results were compared against video reference data. The clinical impact was assessed by quantifying the effect of WB detection error on the estimated walking speed distribution. The two customized Indiv and Pop methods both improved WB detection (higher, sensitivity, accuracy and precision), with the individual-based personalization showing the best results. Comparison of walking speed distribution obtained with the best of the two methods showed a significant difference for 8 out of 20 participants. The personalized Indiv method excluded non-walking activities that were initially wrongly interpreted as extremely slow walking with the initial method using fixed thresholds. Customized methods, particularly individual-based personalization, appear more efficient to detect WB in daily-life settings.

The effects of dual tasks on gait in children with cerebral palsy.

AIM: To assess the gait and cognitive performances of children with cerebral palsy (CP) during dual tasks (DT) in comparison to typically developing (TD) children. METHOD: This prospective, observational, case-control study included 18 children with CP (7 girls, 11 boys; median age 12 [10:13] years and 19 controls (9 girls, 10 boys; median age 12 [10:13y6mo] years). Performances were recorded during a simple walking task, 5 DT (walking + cognitive tasks with increasing cognitive load), and 5 simple cognitive tasks (while sitting). Gait parameters were computed using an optoelectronic system during walking tasks. Six parameters were selected for analysis by a principal component analysis. Cognitive performance was measured for each cognitive task. The dual-task cost (DTC) was calculated for each DT. RESULTS: Gait performance decreased in both groups as DT cognitive load increased (e.g., walking speed normalized by leg length, in simple task: 1.25 [1.15:1.46] s-1 for CP, 1.53 [1.38:1.62] s-1 for TD; DT with highest load: 0.64 [0.53:0.80] s-1 for CP, 0.95 [0.75:1.08] s-1 for TD). The CP group performed significantly worse than TD group in every task (including the simple task), but DTC were similar in both groups. A task effect was found for the majority of the gait parameters. INTERPRETATION: The reduced gait performance induced by DT may generate underestimated difficulties for children with CP in daily-life situations, where DT are common. This should be considered in clinical assessments.

Correction to: Locomotion and cadence detection using a single trunk-fixed accelerometer: validity for children with cerebral palsy in daily life-like conditions.

The original article [1] contained a minor error whereby the middle initial of Christopher J. Newman's name was mistakenly omitted.

Locomotion and cadence detection using a single trunk-fixed accelerometer: validity for children with cerebral palsy in daily life-like conditions.

BACKGROUND: Physical therapy interventions for ambulatory youth with cerebral palsy (CP) often focus on activity-based strategies to promote functional mobility and participation in physical activity. The use of activity monitors validated for this population could help to design effective personalized interventions by providing reliable outcome measures. The objective of this study was to devise a single-sensor based algorithm for locomotion and cadence detection, robust to atypical gait patterns of children with CP in the real-life like monitoring conditions. METHODS: Study included 15 children with CP, classified according to Gross Motor Function Classification System (GMFCS) between levels I and III, and 11 age-matched typically developing (TD). Six IMU devices were fixed on participant's trunk (chest and low back/L5), thighs, and shanks. IMUs on trunk were independently used for development of algorithm, whereas the ensemble of devices on lower limbs were used as reference system. Data was collected according to a semi-structured protocol, and included typical daily-life activities performed indoor and outdoor. The algorithm was based on detection of peaks associated to heel-strike events, identified from the norm of trunk acceleration signals, and included several processing stages such as peak enhancement and selection of the steps-related peaks using heuristic decision rules. Cadence was estimated using time- and frequency-domain approaches. Performance metrics were sensitivity, specificity, precision, error, intra-class correlation coefficient, and Bland-Altman analysis. RESULTS: According to GMFCS, CP children were classified as GMFCS I (n = 7), GMFCS II (n = 3) and GMFCS III (n = 5). Mean values of sensitivity, specificity and precision for locomotion detection ranged between 0.93-0.98, 0.92-0.97 and 0.86-0.98 for TD, CP-GMFCS I and CP-GMFCS II-III groups, respectively. Mean values of absolute error for cadence estimation (steps/min) were similar for both methods, and ranged between 0.51-0.88, 1.18-1.33 and 1.94-2.3 for TD, CP-GMFCS I and CP-GMFCS II-III groups, respectively. The standard deviation was higher in CP-GMFCS II-III group, the lower performances being explained by the high variability of atypical gait patterns. CONCLUSIONS: The algorithm demonstrated good performance when applied to a wide range of gait patterns, from normal to the pathological gait of highly affected children with CP using walking aids.

What is the Best Configuration of Wearable Sensors to Measure Spatiotemporal Gait Parameters in Children with Cerebral Palsy?

Wearable inertial devices have recently been used to evaluate spatiotemporal parameters of gait in daily life situations. Given the heterogeneity of gait patterns in children with cerebral palsy (CP), the sensor placement and analysis algorithm may influence the validity of the results. This study aimed at comparing the spatiotemporal measurement performances of three wearable configurations defined by different sensor positioning on the lower limbs: (1) shanks and thighs, (2) shanks, and (3) feet. The three configurations were selected based on their potential to be used in daily life for children with CP and typically developing (TD) controls. For each configuration, dedicated gait analysis algorithms were used to detect gait events and compute spatiotemporal parameters. Fifteen children with CP and 11 TD controls were included. Accuracy, precision, and agreement of the three configurations were determined in comparison with an optoelectronic system as a reference. The three configurations were comparable for the evaluation of TD children and children with a low level of disability (CP-GMFCS I) whereas the shank-and-thigh-based configuration was more robust regarding children with a higher level of disability (CP-GMFCS II-III).