ArticleDigital biomarkers
Smartphone-Based Gait Cadence to Identify Older Adults with Decreased Functional Capacity.
Article in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Walking cadence as a measure of activity intensity and impact on functional capacity for prefrail and frail older adults.PloS one · 2025Trial
- Measuring Walking Stability with a Mobile Phone in Older Adults: A Validation Study.Sensors (Basel, Switzerland) · 2026Article
- Development and validation of a multi-modal contactless sensing system for surgical risk analysis in a real-world environment.PLOS digital health · 2025Article
- Daily Diary Smartphone Assessment of Subjective Cognitive Concerns in Motoric Cognitive Risk Syndrome: A Pilot Study.Health science reports · 2025Article
- Challenges and Prospects of Sensing Technology for the Promotion of Tele-Physiotherapy: A Narrative Review.Sensors (Basel, Switzerland) · 2024Review
- Gait Assessment Using Smartphone Applications in Older Adults: A Scoping Review.Geriatrics (Basel, Switzerland) · 2024Article
- Validity and Reliability of a Smartphone Application for Home Measurement of Four-Meter Gait Speed in Older Adults.Bioengineering (Basel, Switzerland) · 2024Article
- Incorporating Wearable Technology for Enhanced Rehabilitation Monitoring after Hip and Knee Replacement.Sensors (Basel, Switzerland) · 2024Article
- Open-Source, Step-Counting Algorithm for Smartphone Data Collected in Clinical and Nonclinical Settings: Algorithm Development and Validation Study.JMIR cancer · 2023Article
- Digital health technology combining wearable gait sensors and machine learning improve the accuracy in prediction of frailty.Frontiers in public health · 2023Observational
- Analytical Validation of Wrist-Worn Accelerometer-Based Step-Count Methods during Structured and Free-Living Activities.Digital biomarkersArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Background: Functional capacity assessment is a critical step in the preoperative evaluation to identify patients at increased risk of cardiac complications and disability after major noncardiac surgery. Smartphones offer the potential to objectively measure functional capacity but are limited by inaccuracy in patients with poor functional capacity. Open-source methods exist to analyze accelerometer data to estimate gait cadence (steps/min), which is directly associated with activity intensity. Here, we used an updated Step Test smartphone application with an open-source method to analyze accelerometer data to estimate gait cadence and functional capacity in older adults. Methods: We performed a prospective observational cohort study within the Frailty, Activity, Body Composition and Energy Expenditure in Aging study at the University of Chicago. Participants completed the Duke Activity Status Index (DASI) and performed an in-clinic 6-min walk test (6MWT) while using the Step Test application on a study smartphone. Gait cadence was measured from the raw accelerometer data using an adaptive empirical pattern transformation method, which has been previously validated. A 6MWT distance of 370 m was used as an objective threshold to identify patients at high risk. We performed multivariable logistic regression to predict walking distance using a priori explanatory variables. Results: Sixty patients were enrolled in the study. Thirty-seven patients completed the protocol and were included in the final data analysis. The median (IQR) age of the overall cohort was 71 (69-74) years, with a body mass index of 31 (27-32). There were no differences in any clinical characteristics or functional measures between participants that were able to walk 370 m during the 6MWT and those that could not walk that distance. Median (IQR) gait cadence for the entire cohort was 110 (102-114) steps/min during the 6MWT. Median (IQR) gait cadence was higher in participants that walked more than 370 m during the 6MWT 112 (108-118) versus 106 (96-114) steps/min; Conclusions: Our pilot study demonstrates the feasibility of using gait cadence as a measure to estimate functional capacity. Our study was limited by a smaller than expected sample size due to COVID-19, and thus, a prospective study with preoperative patients that measures outcomes is necessary to validate our findings.
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