ArticleBMC neurology2021
Validation of quantitative gait analysis systems for Parkinson's disease for use in supervised and unsupervised environments.
Article in BMC neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Use of Wearable Sensors to Assess Fall Risk in Neurological Disorders: Systematic Review.JMIR mHealth and uHealth · 2025Pooled it
- Clinical utility and methodological implementation of smartphone-based mobility analysis: a scoping review.Journal of neurology · 2026Article
- Multimodal machine learning mobility assessment in Parkinson's disease within supervised and unsupervised settings.Journal of neuroengineering and rehabilitation · 2026Article
- Uncovering the Kinematic Signature of Freezing of Gait in Parkinson's Disease Through Wearable Inertial Sensors.Sensors (Basel, Switzerland) · 2025Article
- Three-dimensional gait analysis in spinal disorders: biomechanical insights and clinical applications for diagnosis, surgical planning, and rehabilitation.Frontiers in neurology · 2025Review
- Gait Characteristics over the Six-minute Walk Test in Older Women of a Specific Portuguese Community: A Cross-Sectional Study.Current aging science · 2025Article
- Mobile Health for Obsessive-Compulsive Disorder: Patients' Preferences and Perception of Patient-Centeredness.Actas espanolas de psiquiatria · 2025Article
- Biomechanical Gait Analysis Using a Smartphone-Based Motion Capture System (OpenCap) in Patients with Neurological Disorders.Bioengineering (Basel, Switzerland) · 2024Article
- A Scoping Review of the Validity and Reliability of Smartphone Accelerometers When Collecting Kinematic Gait Data.Sensors (Basel, Switzerland) · 2023Article
- Deep Learning-Assisted Gait Parameter Assessment for Neurodegenerative Diseases: Model Development and Validation.Journal of medical Internet research · 2023Article
- Gait Analysis in Neurorehabilitation: From Research to Clinical Practice.Bioengineering (Basel, Switzerland) · 2023Review
- Validation of Pressure-Sensing Insoles in Patients with Parkinson's Disease during Overground Walking in Single and Cognitive Dual-Task Conditions.Sensors (Basel, Switzerland) · 2022Article
- Distinct gait dimensions are modulated by physical activity in Parkinson's disease patients.Journal of neural transmission (Vienna, Austria : 1996) · 2022Article
- Smartphone-Based Body Location-Independent Functional Mobility Analysis in Patients with Parkinson's Disease: A Step towards Precise Medicine.Journal of personalized medicine · 2022Article
- Cognitive parameters can predict change of walking performance in advanced Parkinson's disease - Chances and limits of early rehabilitation.Frontiers in aging neuroscience · 2022Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGait impairments are among the most common and impactful symptoms of Parkinson's disease (PD). Recent technological advances aim to quantify these impairments using low-cost wearable systems for use in either supervised clinical consultations or long-term unsupervised monitoring of gait in ecological environments. However, very few of these wearable systems have been validated comparatively to a criterion of established validity.
objectiveWe developed two movement analysis solutions (3D full-body kinematics based on inertial sensors, and a smartphone application) in which validity was assessed versus the optoelectronic criterion in a population of PD patients.
methodsNineteen subjects with PD (7 female) participated in the study (age: 62 ± 12.27 years; disease duration: 6.39 ± 3.70 years; HY: 2 ± 0.23). Each participant underwent a gait analysis whilst barefoot, at a self-selected speed, for a distance of 3 times 10 m in a straight line, assessed simultaneously with all three systems.
resultsOur results show excellent agreement between either solution and the optoelectronic criterion. Both systems differentiate between PD patients and healthy controls, and between PD patients in ON or OFF medication states (normal difference distributions pooled from published research in PD patients in ON and OFF states that included an age-matched healthy control group). Fair to high waveform similarity and mean absolute errors below the mean relative orientation accuracy of the equipment were found when comparing the angular kinematics between the full-body inertial sensor-based system and the optoelectronic criterion.
conclusionsWe conclude that the presented solutions produce accurate results and can capture clinically relevant parameters using commodity wearable sensors or a simple smartphone. This validation will hopefully enable the adoption of these systems for supervised and unsupervised gait analysis in clinical practice and clinical trials.
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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.