Background: Children's motor development can be evaluated through the analysis of gait temporal parameters and their variability. This requires the detection of gait events in a real-world environment, which can be achieved using inertial measurement units. Algorithms have been previously developed for healthy adults; however, the performance of these algorithms in the detection of gait events in toddlers has not been analysed.
Research Question: Can inertial measurement units be used to analyse gait temporal parameters in toddlers?
Methods: Fifteen previously published algorithms using sensors attached on the lower-back or the ankles were used to identify gait events and calculate gait temporal parameters. A total of 1388 initial and 1388 final foot contacts collected from 15 toddlers were included in the analysis. The performance of the algorithms was compared against a GAITRite mat in terms of accuracy and precision. Accuracy in the measurement of gait temporal parameters was evaluated using Bland Altman limits of agreement for repeated measurements, and precision was assessed through the evaluation of correctly identified, falsely identified and missed events.
Results: From our results, no algorithm emerged as a best option from all those analysed. Algorithms using the ankle sensors provide higher accuracy and perfect precision when using only angular velocity about the medio-lateral axis. The best algorithms using the sensor attached at the lower-back use the resultant or global acceleration that reduces the effect of the sensor's alignment. These lower-back-based algorithms compared to the best ankle-based ones have similar accuracy for the calculation of stride time and higher accuracy for step time; however, they do not have perfect precision.
Significance: Inertial measurement units can support research analysing the temporal parameters of toddlers' gait in controlled environments, and may allow future studies in natural, free-living environments that can improve the monitoring of gait in young children.
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http://dx.doi.org/10.1016/j.gaitpost.2025.02.024 | DOI Listing |
Invest Ophthalmol Vis Sci
March 2025
College of Optometry, Nova Southeastern University, Davie, Florida, United States.
Purpose: The purpose of this study was to quantify the corneal power changes after wearing orthokeratology lenses of different back optic zone diameters (BOZDs) and to propose a novel 4-parameter model capable of revealing the associations between each parameter and axial length growth (ALG).
Methods: A prospective self-controlled study was conducted between June 2022 and December 2023. One eye in each subject (N = 33) was randomly assigned to wear a lens with a BOZD of either 5 mm (5 oz) or 6 mm (6 oz).
Biol Open
March 2025
Department of Veterinary Biomedical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, S7N 5B4, Canada.
The Integrator is a metazoan-conserved protein complex with endonuclease activity that functions to cleave various RNA substrates to shape transcriptome homeostasis by coordinating small nuclear RNA biogenesis to premature transcription termination. Depletion of Integrator results in developmental defects across different model systems and has emerged as a causative factor in human neurodevelopmental syndromes. Here, we use the model system Caenorhabditis elegans to enable studying the temporal effects of Integrator depletion on various physiological parameters with the auxin-inducible degron system that permitted depletion of INTS-4 (Integrator subunit) catalytic subunit of the protein complex.
View Article and Find Full Text PDFThis study presents a novel deep learning approach for surface electromyography (sEMG) gesture recognition using stacked autoencoder neural network (SAE)s. The method leverages hierarchical representation learning to extract meaningful features from raw sEMG signals, enhancing the precision and robustness of gesture classification.•Feature Extraction and Classification MODWT Decomposition: The sEMG signals were decomposed using the MODWT DECOMPOSITION(Maximal Overlap Discrete Wavelet Transform) to capture various frequency components.
View Article and Find Full Text PDFEClinicalMedicine
March 2025
VA Boston Cooperative Studies Program, Boston, MA, USA.
Background: Novel strategies that account for population-level changes in dominant variants, immunity, testing practices and changes in individual risk profiles are needed to identify patients who remain at high risk of severe COVID-19. The aim of this study was to develop and prospectively validate a tool to predict absolute risk of severe COVID-19 incorporating dynamic parameters at the patient and population levels that could be used to inform clinical care.
Methods: A retrospective cohort of vaccinated US Veterans with SARS-CoV-2 from July 1, 2021, through August 25, 2023 was created.
BMC Med Imaging
March 2025
Ophthalmology Department and Eye Research Center, Farabi Eye Hospital, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Purpose: Thyroid eye disease (TED) presents challenges in the accurate assessment of disease activity, especially concerning ocular surface manifestations. This study aims to evaluate the potential of anterior segment optical coherence tomography angiography (AS-OCTA) in quantifying vascular changes associated with TED, thereby enhancing understanding of its pathophysiology and aiding in diagnosis and management.
Methods: We conducted a cross-sectional study involving 29 TED patients and 21 healthy controls.
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