ArticleBMC research notes2014
Mobile Romberg test assessment (mRomberg).
Article in BMC research notes, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 4 of them syntheses that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 4 syntheses or guidelines pooled it, 43 citations in OpenAlex.
- ICT technologies as new promising tools for the managing of frailty: a systematic review.Aging clinical and experimental research · 2021Pooled it
- ICT technologies as new promising tools for the managing of frailty: a systematic review.Aging clinical and experimental research · 2021Pooled it
- Sensors are Capable to Help in the Measurement of the Results of the Timed-Up and Go Test? A Systematic Review.Journal of medical systems · 2020Pooled it
- A Systematic Review of the Effect of Hearing Aids on Static and Dynamic Balance in Adults with Hearing Impairment.Trends in hearingPooled it
- Effects of Monitoring Frailty Through a Mobile/Web-Based Application and a Sensor Kit to Prevent Functional Decline in Frail and Prefrail Older Adults: FACET (Frailty Care and Well Function) Pilot Randomized Controlled Trial.Journal of medical Internet research · 2024Trial
- Objective estimation of m-CTSIB balance test scores using wearable sensors and machine learning.Frontiers in digital health · 2024Article
- Inertial Measurement Unit-Based Romberg Test for Assessing Adults With Vestibular Hypofunction.IEEE journal of translational engineering in health and medicine · 2024Article
- The Reliability and Accuracy of a Fall Risk Assessment Procedure Using Mobile Smartphone Sensors Compared with a Physiological Profile Assessment.Sensors (Basel, Switzerland) · 2023Article
- Using Smartphones for Clinical Assessment in Cervical Spondylotic Myelopathy a Feasibility Study.Journal of medical devices · 2021Article
- Unobtrusive Sensors for the Assessment of Older Adult's Frailty: A Scoping Review.Sensors (Basel, Switzerland) · 2021Article
- Balance Assessment of Children with Sensorineural Hearing Loss.Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India · 2021Article
- Activities of daily living with motion: A dataset with accelerometer, magnetometer and gyroscope data from mobile devices.Data in brief · 2020Article
- Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults.Sensors (Basel, Switzerland) · 2020Article
- Assessing disability and relapses in multiple sclerosis on tele-neurology.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2020Review
- Impact of Visual Biofeedback of Trunk Sway Smoothness on Motor Learning during Unipedal Stance.Sensors (Basel, Switzerland) · 2020Article
- The Validity, Reliability, and Sensitivity of a Smartphone-Based Seated Postural Control Assessment in Wheelchair Users: A Pilot Study.Frontiers in sports and active living · 2020Article
- The use of smartphone in measuring stance and gait patterns in patients with orthostatic tremor.PloS one · 2019Article
- Article
- Quantification of Axial Abnormality Due to Cerebellar Ataxia with Inertial Measurements.Sensors (Basel, Switzerland) · 2018Article
- Toward Smart Footwear to Track Frailty Phenotypes-Using Propulsion Performance to Determine Frailty.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe diagnosis of frailty is based on physical impairments and clinicians have indicated that early detection is one of the most effective methods for reducing the severity of physical frailty. Maybe, an alternative to the classical diagnosis could be the instrumentalization of classical functional testing, as Romberg test or Timed Get Up and Go Test. The aim of this study was (I) to measure and describe the magnitude of accelerometry values in the Romberg test in two groups of frail and non-frail elderly people through instrumentation with the iPhone 4®, (II) to analyse the performances and differences between the study groups, and (III) to analyse the performances and differences within study groups to characterise accelerometer responses to increasingly difficult challenges to balance.
methodsThis is a cross-sectional study of 18 subjects over 70 years old, 9 frail subjects and 9 non-frail subjects. The non-parametric Mann-Whitney U test was used for between-group comparisons in means values derived from different tasks. The Wilcoxon Signed-Rank test was used to analyse differences between different variants of the test in both independent study groups.
resultsThe highest difference between groups was found in the accelerometer values with eyes closed and feet parallel: maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.01). Subjects with eyes open and feet parallel, greatest differences found between the groups were in the maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.001). With eyes closed and feet in tandem, the greatest differences found between the groups were in the minimum peak acceleration in the lateral axis (p < 0.01).
conclusionsThe accelerometer fitted in the iPhone 4® is able to study and analyse the kinematics of the Romberg test between frail and non-frail elderly people. In addition, the results indicate that the accelerometry values also were significantly different between the frail and non-frail groups, and that values from the accelerometer accelerometer increased as the test was made more complicated.
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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.