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Background: Gait disturbances found in patients with idiopathic normal pressure hydrocephalus (iNPH) are unspecific to the diagnosis and commonly occur in neurodegenerative or vascular conditions (iNPH-like conditions). This current retrospective pre-post intervention study aims to determine whether changes in quantitative gait parameters during dual task condition differed between iNPH and iNPH-like conditions before and after cerebrospinal fluid (CSF) tapping.Methods: 49 patients assessed before and after CSF tapping were included in this study (27 with iNPH and 22 with iNPH-like conditions). Gait analysis during single and dual task conditions (walking and backward counting) was performed before and after a CSF spinal tap of 40 ml. Gait parameters were compared between iNPH and iNPH-like conditions patients. Logistic regressions were used to examine the association between iNPH and gait parameters.Results: Improvements of step width (-9.03 (20.75)% for iNPH group; +0.28 (21.76)% for iNPH-like conditions group), stride length (+7.82 (20.71)% for iNPH group; -0.62 (19.22)% for iNPH-like conditions group), walking speed (+12.20 (29.79)% for iNPH group; +2.38 (32.50)% for iNPH-like conditions group) and stance duration (-1.23 (4.03)% for iNPH group; +0.49 (5.12)% for iNPH-like conditions group) during dual task, after CSF spinal tapping, were significant in patients with iNPH compared to patients with iNPH-like conditions. No between group difference was observed for the single walking task evaluation. The multiple logistic regression revealed that among these four gait parameters, only the improvement in step width was associated with the diagnosis of iNPH.Conclusion: Dual-task related changes in spatio-temporal gait parameters before and after CSF tapping might be a novel and discriminative method of identifying iNPH patients from other similar conditions. [ABSTRACT FROM AUTHOR]

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

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. [ABSTRACT FROM AUTHOR]