ArticleJMIR mHealth and uHealth2019
Continuous Digital Monitoring of Walking Speed in Frail Elderly Patients: Noninterventional Validation Study and Longitudinal Clinical Trial.
Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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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
40 citing papers in PubMed, 1 synthesis or guideline pooled it, 60 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
- Trial
- Recovery of daily-life walking after total knee arthroplasty: A two-year longitudinal study and comparison with healthy controls.Osteoarthritis and cartilage open · 2026Article
- Feasibility of Activity Monitors to Assess Physical Capacity After Critical Illness: An Observational Study Nested Within a Randomized Clinical Trial.Mayo Clinic proceedings. Digital health · 2026Article
- Article
- IMU-based gait analysis methods: a systematic review of techniques for different body locations.Frontiers in sports and active living · 2026Review
- 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
- Comparability of Daily-Life Walking Speed Measured by Smartphone GPS and Ankle-Band Accelerometer: Cross-Sectional Study.JMIR formative research · 2025Article
- Advancements and Innovation Trends of Information Technology Empowering Elderly Care Community Services Based on CiteSpace and VOSViewer.Healthcare (Basel, Switzerland) · 2025Article
- Ability of Heart Rate Recovery and Gait Kinetics in a Single Wearable to Predict Frailty: Quasiexperimental Pilot Study.JMIR formative research · 2024Article
- In-Clinic and Natural Gait Observations master protocol (I-CAN-GO) to validate gait using a lumbar accelerometer.Scientific reports · 2024Article
- Daily-Life Walking Speed, Quality and Quantity Derived from a Wrist Motion Sensor: Large-Scale Normative Data for Middle-Aged and Older Adults.Sensors (Basel, Switzerland) · 2024Article
- GPS Suitability for Physical Frailty Assessment.Sensors (Basel, Switzerland) · 2024Article
- Monitoring Gait and Physical Activity of Elderly Frail Individuals in Free-Living Environment: A Feasibility Study.Gerontology · 2024Article
- Validity and reliability of the Apple Health app on iPhone for measuring gait parameters in children, adults, and seniors.Scientific reports · 2023Article
- Editorial: Multimodal digital approaches to personalized medicine.Frontiers in big data · 2023Article
- Digital health technology combining wearable gait sensors and machine learning improve the accuracy in prediction of frailty.Frontiers in public health · 2023Observational
- Capturing Measures That Matter: The Potential Value of Digital Measures of Physical Behavior for Alzheimer's Disease Drug Development.Journal of Alzheimer's disease : JAD · 2023Review
- Review
- How Much Data Is Enough? A Reliable Methodology to Examine Long-Term Wearable Data Acquisition in Gait and Postural Sway.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDigital technologies and advanced analytics have drastically improved our ability to capture and interpret health-relevant data from patients. However, only limited data and results have been published that demonstrate accuracy in target indications, real-world feasibility, or the validity and value of these novel approaches.
objectiveThis study aimed to establish accuracy, feasibility, and validity of continuous digital monitoring of walking speed in frail, elderly patients with sarcopenia and to create an open source repository of raw, derived, and reference data as a resource for the community.
methodsData described here were collected as a part of 2 clinical studies: an independent, noninterventional validation study and a phase 2b interventional clinical trial in older adults with sarcopenia. In both studies, participants were monitored by using a waist-worn inertial sensor. The cross-sectional, independent validation study collected data at a single site from 26 naturally slow-walking elderly subjects during a parcours course through the clinic, designed to simulate a real-world environment. In the phase 2b interventional clinical trial, 217 patients with sarcopenia were recruited across 32 sites globally, where patients were monitored over 25 weeks, both during and between visits.
resultsWe have demonstrated that our approach can capture in-clinic gait speed in frail slow-walking adults with a residual standard error of 0.08 m per second in the independent validation study and 0.08, 0.09, and 0.07 m per second for the 4 m walk test (4mWT), 6-min walk test (6MWT), and 400 m walk test (400mWT) standard gait speed assessments, respectively, in the interventional clinical trial. We demonstrated the feasibility of our approach by capturing 9668 patient-days of real-world data from 192 patients and 32 sites, as part of the interventional clinical trial. We derived inferred contextual information describing the length of a given walking bout and uncovered positive associations between the short 4mWT gait speed assessment and gait speed in bouts between 5 and 20 steps (correlation of 0.23) and longer 6MWT and 400mWT assessments with bouts of 80 to 640 steps (correlations of 0.48 and 0.59, respectively).
conclusionsThis study showed, for the first time, accurate capture of real-world gait speed in slow-walking older adults with sarcopenia. We demonstrated the feasibility of long-term digital monitoring of mobility in geriatric populations, establishing that sufficient data can be collected to allow robust monitoring of gait behaviors outside the clinic, even in the absence of feedback or incentives. Using inferred context, we demonstrated the ecological validity of in-clinic gait assessments, describing positive associations between in-clinic performance and real-world walking behavior. We make all data available as an open source resource for the community, providing a basis for further study of the relationship between standardized physical performance assessment and real-world behavior and independence.
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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.