BackgroundPhysical 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.MethodsStudy 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.ResultsAccording 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.ConclusionsThe 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.
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).
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. Cerebral palsy (CP) describes a group of motor disorders resulting from early damage to the developing brain 1. It is the most frequent motor disability in children, with a prevalence of 1.8 per 1000 live births in Europe 2. Children with CP have heterogeneous clinical profiles and are classified into five levels of severity with the Gross Motor Function Classification System (I: independent walker; II: independent walker with limitations; III: ambulate with walking aids; IV: ambulate with powered mobility; and V: dependent for all mobility) 3,4. In CP, gait disorders are among the leading limitations, with a negative impact on participation and self-perception 5. Current management of gait deviations is largely based on assessments of body structures and body functions of individuals measured in clinical settings 6. 'Clinical gait analysis' (CGA) measures multiple gait parameters in order to identify and understand the main causes of gait deviations 7. Although CGA has become a widely accepted tool in clinical practice, it is not clear whether in-laboratory assessments reflect the usual walking performance of the patients in daily life. Patients are often considered to perform better when walking under clinical supervision to please caregivers 8 , known as the 'Hawthorne effect' 9 , and thanks to improved concentration in the absence of external distractors requiring additional attention 10. Integrating unsupervised assessments of the patients' daily walking into the clinical process could improve clinicians' understanding of their real behavior and overall difficulties, beyond the observation of functional limitations in a purely clinical setting 10. The link between capacity (what an individual can do in ...
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