ArticlePloS one2019
Validity of accelerometry in step detection and gait speed measurement in orthogeriatric patients.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 37 citations in OpenAlex.
- How wearable sensors have been utilised to evaluate frailty in older adults: a systematic review.Journal of neuroengineering and rehabilitation · 2021Pooled it
- Pooled it
- Real-world walking speed as a digital biomarker and outcome measure for clinical trials-a systematic review, regulatory status and future directions.Frontiers in digital health · 2026Review
- Wearable technology for mobility measurement in orthopedics and traumatology: a comparison of commercially available systems.Archives of orthopaedic and trauma surgery · 2025Article
- Correction: Validity of accelerometry in step detection and gait speed measurement in orthogeriatric patients.PloS one · 2025Article
- Changes in real-world walking speed following 60-day bed-rest.NPJ microgravity · 2024Article
- Mobility improvement in the first 6 postoperative weeks in orthogeriatric fracture patients.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2022Article
- Use of activPAL to Measure Physical Activity in Community-Dwelling Older Adults: A Systematic Review.Archives of rehabilitation research and clinical translation · 2022Review
- Prediction of Physical Frailty in Orthogeriatric Patients Using Sensor Insole-Based Gait Analysis and Machine Learning Algorithms: Cross-sectional Study.JMIR medical informatics · 2022Article
- Self-Assessment of Mobility of People over 65 Years of Age.Medicina (Kaunas, Lithuania) · 2021Article
- Walking speed measurement technology: A review.Current geriatrics reports · 2021Article
- Accelerometric Gait Analysis Devices in Children-Will They Accept Them? Results From the AVAPed Study.Frontiers in pediatrics · 2020Article
- Robust Step Detection from Different Waist-Worn Sensor Positions: Implications for Clinical Studies.Digital biomarkers · 2020Article
- Continuous Digital Monitoring of Walking Speed in Frail Elderly Patients: Noninterventional Validation Study and Longitudinal Clinical Trial.JMIR mHealth and uHealth · 2019Article
- Article
- Device- and Analytics-Agnostic Infrastructure for Continuous Inpatient Monitoring: A Technical Note.Digital biomarkersArticle
- Evaluation, Acceptance, and Qualification of Digital Measures: From Proof of Concept to Endpoint.Digital biomarkersReview
- Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMobile accelerometry is a powerful and promising option to capture long-term changes in gait in both clinical and real-world scenarios. Increasingly, gait parameters have demonstrated their value as clinical outcome parameters, but validation of these parameters in elderly patients is still limited.
objectiveThe aim of this study was to implement a validation framework appropriate for elderly patients and representative of real-world settings, and to use this framework to test and improve algorithms for mobile accelerometry data in an orthogeriatric population.
methodsTwenty elderly subjects wearing a 3D-accelerometer completed a parcours imitating a real-world scenario. High-definition video and mobile reference speed capture served to validate different algorithms.
resultsParticularly at slow gait speeds, relevant improvements in accuracy have been achieved. Compared to the reference the deviation was less than 1% in step detection and less than 0.05 m/s in gait speed measurements, even for slow walking subjects (< 0.8 m/s).
conclusionWith the described setup, algorithms for step and gait speed detection have successfully been validated in an elderly population and demonstrated to have improved performance versus previously published algorithms. These results are promising that long-term and/or real-world measurements are possible with an acceptable accuracy even in elderly frail patients with slow gait speeds.
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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.