ArticleSensors (Basel, Switzerland)2022
High Specificity of Single Inertial Sensor-Supplemented Timed Up and Go Test for Assessing Fall Risk in Elderly Nursing Home Residents.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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.
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Who cites it
15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Meta-analysis of the quantitative assessment of lower extremity motor function in elderly individuals based on objective detection.Journal of neuroengineering and rehabilitation · 2024Pooled it
- A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults.Sensors (Basel, Switzerland) · 2022Pooled it
- Multidimensional Assessment of Fall Risk Using the Timed Up and Go Test and Complementary Measures in a Charcot-Marie-Tooth Type 1A Neuropathy.Archives of rehabilitation research and clinical translation · 2026Article
- Validation of World Guideline gait speed and TUG cut-offs for fall risk stratification in ambulatory nursing home residents aged ≥ 80 years: a multicenter cross-sectional diagnostic study.BMC geriatrics · 2026Article
- Movement smoothness and turning deficits during the timed up and go in older adults with chronic neck pain.Frontiers in sports and active living · 2026Article
- Fall Risk Management in Nursing Homes: A Scoping Review.Healthcare (Basel, Switzerland) · 2025Review
- Epidemiology and assessments of delirium in nursing homes and rehabilitation facilities: a cross-country perspective.European geriatric medicine · 2025Article
- Fall Risk Assessment and Prevention Strategies in Nursing Homes: A Narrative Review.Healthcare (Basel, Switzerland) · 2025Review
- Validation of a 3D Markerless Motion Capture Tool Using Multiple Pose and Depth Estimations for Quantitative Gait Analysis.Sensors (Basel, Switzerland) · 2024Article
- Identifying sensors-based parameters associated with fall risk in community-dwelling older adults: an investigation and interpretation of discriminatory parameters.BMC geriatrics · 2024Article
- Identifying sensors-based parameters associated with fall risk in community-dwelling older adults: an investigation and interpretation of discriminatory parameters.BMC geriatrics · 2024Article
- Evaluation of Lower-Limb Kinematics during Timed Up and Go (TUG) Test in Subjects with Locomotive Syndrome (LS) Using Wearable Gait Sensors (H-Gait System).Sensors (Basel, Switzerland) · 2023Article
- Quasi-experimental pilot study to improve mobility and balance in recurrently falling nursing home residents by voluntary non-targeted side-stepping exercise intervention.BMC geriatrics · 2022Article
- Wearable Sensors Applied in Movement Analysis.Sensors (Basel, Switzerland) · 2022Article
- Gait as a vital sign: integrating wearables and AI into vestibular and balance medicine.Frontiers in neurologyReview
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Timed Up and Go test (TUG) is commonly used to estimate the fall risk in the elderly. Several ways to improve the predictive accuracy of TUG (cameras, multiple sensors, other clinical tests) have already been proposed. Here, we added a single wearable inertial measurement unit (IMU) to capture the residents' body center-of-mass kinematics in view of improving TUG's predictive accuracy. The aim is to find out which kinematic variables and residents' characteristics are relevant for distinguishing faller from non-faller patients. Data were collected in 73 nursing home residents with the IMU placed on the lower back. Acceleration and angular velocity time series were analyzed during different subtasks of the TUG. Multiple logistic regressions showed that total time required, maximum angular velocity at the first half-turn, gender, and use of a walking aid were the parameters leading to the best predictive abilities of fall risk. The predictive accuracy of the proposed new test, called i + TUG, reached a value of 74.0%, with a specificity of 95.9% and a sensitivity of 29.2%. By adding a single wearable IMU to TUG, an accurate and highly specific test is therefore obtained. This method is quick, easy to perform and inexpensive. We recommend to integrate it into daily clinical practice in nursing homes.
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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.