ArticleSensors (Basel, Switzerland)2023
Evaluating Gait Impairment in Parkinson's Disease from Instrumented Insole and IMU Sensor Data.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 39 citations in OpenAlex.
- Validity of a Wearable Digital Insole for Assessing Gait ON and OFF in Parkinson's Disease.Annals of clinical and translational neurology · 2026Article
- Instrumental assessment of Sit-to-Stand in Parkinson's disease: a scoping review.Journal of neuroengineering and rehabilitation · 2026Article
- Multimodal Intelligent Monitoring of Parkinson Disease: Scoping Review of Progress and Translational Challenges.Journal of medical Internet research · 2026Article
- AI-Enabled Wearables for Motor Function Assessment and Rehabilitation in Parkinson Disease: Scoping Review.Journal of medical Internet research · 2026Review
- Gait Parameters of Women Before Knee Joint Arthritis-Analysis Using the MoKA System.Sensors (Basel, Switzerland) · 2025Article
- Gait Event Detection and Gait Parameter Estimation from a Single Waist-Worn IMU Sensor.Sensors (Basel, Switzerland) · 2025Article
- Multi-Domain CoP Feature Analysis of Functional Mobility for Parkinson's Disease Detection Using Wearable Pressure Insoles.Sensors (Basel, Switzerland) · 2025Article
- Analyzing Mobility Indicators Using Machine Learning to Detect Mild Cognitive Impairment: A Systematic Scoping Review.Applied clinical informatics · 2025Article
- IMU-Based quantitative assessment of stroke from gait.Scientific reports · 2025Article
- A multi-sensor approach to improve interpretability of the 6-min walk test as an outcome in muscular dystrophies: an observational study.Brain communications · 2025Article
- Wearable system for the measurement of gait cycle kinematic and kinetic signals.Wearable technologies · 2025Article
- New gait performance indices and cognitive functions: a pilot study on correlation in people with Parkinson's disease.Frontiers in human neuroscience · 2025Article
- Sensor-based quantification of items used in the MDS-UPDRS-III scale: repetitive lower-limb movements in healthy human participants.Frontiers in neurology · 2025Article
- A Wearable Gait Monitoring System for 17 Gait Parameters Based on Computer Vision.IEEE transactions on instrumentation and measurement · 2025Article
- Evaluating gait and postural responses to subthalamic stimulation and levodopa: A prospective study using wearable technology.European journal of neurology · 2025Article
- Digital biomarkers for precision diagnosis and monitoring in Parkinson's disease.NPJ digital medicine · 2024Review
- Assessing the clinical utility of inertial sensors for home monitoring in Parkinson's disease: a comprehensive review.NPJ Parkinson's disease · 2024Article
- Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease.Sensors (Basel, Switzerland) · 2024Article
- Assisted technology in Parkinson's disease gait: what's up?Arquivos de neuro-psiquiatria · 2024Review
- A Computer Vision-Based System to Help Health Professionals to Apply Tests for Fall Risk Assessment.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
Abstract
Parkinson's disease (PD) is characterized by a variety of motor and non-motor symptoms, some of them pertaining to gait and balance. The use of sensors for the monitoring of patients' mobility and the extraction of gait parameters, has emerged as an objective method for assessing the efficacy of their treatment and the progression of the disease. To that end, two popular solutions are pressure insoles and body-worn IMU-based devices, which have been used for precise, continuous, remote, and passive gait assessment. In this work, insole and IMU-based solutions were evaluated for assessing gait impairment, and were subsequently compared, producing evidence to support the use of instrumentation in everyday clinical practice. The evaluation was conducted using two datasets, generated during a clinical study, in which patients with PD wore, simultaneously, a pair of instrumented insoles and a set of wearable IMU-based devices. The data from the study were used to extract and compare gait features, independently, from the two aforementioned systems. Subsequently, subsets comprised of the extracted features, were used by machine learning algorithms for gait impairment assessment. The results indicated that insole gait kinematic features were highly correlated with those extracted from IMU-based devices. Moreover, both had the capacity to train accurate machine learning models for the detection of PD gait impairment.
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Registered trials
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.