ArticleSensors (Basel, Switzerland)2018
What is the Best Configuration of Wearable Sensors to Measure Spatiotemporal Gait Parameters in Children with Cerebral Palsy?
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed, 58 citations in OpenAlex.
- Minimal Sensor Configuration for Human Activity Recognition in Patients With Hip Osteoarthritis: Proof-of-Concept Study.JMIR biomedical engineering · 2026Article
- Body position classification using wearable sensors in infants with cerebral palsy.Infant behavior & development · 2026Article
- Wearable sensors in paediatric neurology.Developmental medicine and child neurology · 2025Review
- Wearable Technology and Its Influence on Motor Development and Biomechanical Analysis.International journal of environmental research and public health · 2024Review
- Walking Bout Detection for People Living in Long Residential Care: A Computationally Efficient Algorithm for a 3-Axis Accelerometer on the Lower Back.Sensors (Basel, Switzerland) · 2023Article
- Enhancing Wearable Gait Monitoring Systems: Identifying Optimal Kinematic Inputs in Typical Adolescents.Sensors (Basel, Switzerland) · 2023Article
- Artificial Neural Network-Based Activities Classification, Gait Phase Estimation, and Prediction.Annals of biomedical engineering · 2023Article
- Article
- Inertial sensors for gait monitoring and design of adaptive controllers for exoskeletons after stroke: a feasibility study.Frontiers in bioengineering and biotechnology · 2023Article
- Accuracy and comparison of sensor-based gait speed estimations under standardized and daily life conditions in children undergoing rehabilitation.Journal of neuroengineering and rehabilitation · 2022Article
- A Deep Learning Approach for Gait Event Detection from a Single Shank-Worn IMU: Validation in Healthy and Neurological Cohorts.Sensors (Basel, Switzerland) · 2022Article
- Using a Deep Learning Method and Data from Two-Dimensional (2D) Marker-Less Video-Based Images for Walking Speed Classification.Sensors (Basel, Switzerland) · 2021Article
- Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation.Sensors (Basel, Switzerland) · 2021Article
- Validation of IMU-based gait event detection during curved walking and turning in older adults and Parkinson's Disease patients.Journal of neuroengineering and rehabilitation · 2021Article
- Multidimensional Measures of Physical Activity and Their Association with Gross Motor Capacity in Children and Adolescents with Cerebral Palsy.Sensors (Basel, Switzerland) · 2020Article
- Deep Learning in Gait Parameter Prediction for OA and TKA Patients Wearing IMU Sensors.Sensors (Basel, Switzerland) · 2020Article
- Design, Validity, and Reliability of a New Test, Based on an Inertial Measurement Unit System, for Measuring Cervical Posture and Motor Control in Children with Cerebral Palsy.Diagnostics (Basel, Switzerland) · 2020Article
- Validation of a portable system for spatial-temporal gait parameters based on a single inertial measurement unit and a mobile application.European journal of translational myology · 2020Article
- Concurrent Validity and Reliability of an Inertial Measurement Unit for the Assessment of Craniocervical Range of Motion in Subjects with Cerebral Palsy.Diagnostics (Basel, Switzerland) · 2020Article
- Walking Speed of Children and Adolescents With Cerebral Palsy: Laboratory Versus Daily Life.Frontiers in bioengineering and biotechnology · 2020Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.