ArticleMedical & biological engineering & computing2023
A robust walking detection algorithm using a single foot-worn inertial sensor: validation in real-life settings.
Article in Medical & biological engineering & computing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Wearable Sensors in Gait Assessment for Parkinson Disease and Stroke in Real-World Environments: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Construct validity of instrumented gait assessments in hospital and daily life mobility in patients with Parkinson's disease and atypical Parkinson's syndromes: an exploratory study.Journal of neurology · 2026Trial
- Real-Time Gait Analysis of the Pelvis and Lower Limbs Using a Seven-Node IMU Network.Sensors (Basel, Switzerland) · 2026Article
- WearGait-PD: An Open-Access Wearables Dataset for Gait in Parkinson's Disease and Age-Matched Controls.Scientific data · 2026Article
- Moving beyond the hospital: in-depth characterization of daily-life mobility in patients with atypical Parkinsonian disorders.NPJ Parkinson's disease · 2026Article
- IMU-based gait analysis methods: a systematic review of techniques for different body locations.Frontiers in sports and active living · 2026Review
- A Review of Gait Analysis Using Gyroscopes and Inertial Measurement Units.Sensors (Basel, Switzerland) · 2025Review
- Improved running gait parameter estimation from single foot-mounted IMU data based on refined event detection.Frontiers in bioengineering and biotechnology · 2025Article
- Innovative Detection and Segmentation of Mobility Activities in Patients Living with Parkinson's Disease Using a Single Ankle-Positioned Smartwatch.Sensors (Basel, Switzerland) · 2024Article
- Effects of multidisciplinary inpatient rehabilitation on everyday life physical activity and gait in patients with multiple sclerosis.Journal of neuroengineering and rehabilitation · 2024Article
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Authors and funding
13 authors.
Funding
Abstract
Walking activity and gait parameters are considered among the most relevant mobility-related parameters. Currently, gait assessments have been mainly analyzed in laboratory or hospital settings, which only partially reflect usual performance (i.e., real world behavior). In this study, we aim to validate a robust walking detection algorithm using a single foot-worn inertial measurement unit (IMU) in real-life settings. We used a challenging dataset including 18 individuals performing free-living activities. A multi-sensor wearable system including pressure insoles, multiple IMUs, and infrared distance sensors (INDIP) was used as reference. Accurate walking detection was obtained, with sensitivity and specificity of 98 and 91% respectively. As robust walking detection is needed for ambulatory monitoring to complete the processing pipeline from raw recorded data to walking/mobility outcomes, a validated algorithm would pave the way for assessing patient performance and gait quality in real-world conditions.
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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.