Evidence map›Paper›PMID 28475201›Full record

Trial reportJournal of rehabilitation research and development2016

Sensor-based balance training with motion feedback in people with mild cognitive impairment.

Michael Schwenk, Marwan Sabbagh, Ivy Lin, Pharah Morgan, Gurtej S Grewal, Jane Mohler, David W Coon, Bijan Najafi

Open access · diamondAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of rehabilitation research and development, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 13 pooled it
12.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed, 13 syntheses or guidelines pooled it, 99 citations in OpenAlex.

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  20. Effects of balance physical therapy with or without cognitive training in adults with cognitive and balance impairments : a systematic review.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 2 countries.

Michael SchwenkInterdisciplinary Consortium on Advanced Motion Performance-Arizona (iCAMP-A), Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ.
Marwan SabbaghCleo Roberts Memory and Movement Disorders Center, Banner Sun Health Research Institute, Sun City, AZ.
Ivy LinInterdisciplinary Consortium on Advanced Motion Performance-Arizona (iCAMP-A), Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ.
Pharah MorganInterdisciplinary Consortium on Advanced Motion Performance-Arizona (iCAMP-A), Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ.
Gurtej S GrewalInterdisciplinary Consortium on Advanced Motion Performance-Arizona (iCAMP-A), Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ.
Jane MohlerInterdisciplinary Consortium on Advanced Motion Performance-Arizona (iCAMP-A), Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ.
David W CoonCollege of Nursing & Health Innovation, Arizona State University, Phoenix, AZ.
Bijan NajafiInterdisciplinary Consortium on Advanced Motion Performance-Arizona (iCAMP-A), Department of Surgery, College of Medicine, University of Arizona, Tucson, AZ.
University of Arizona · USArizona State University · USBanner Sun Health Research Institute · US

Funding

Research Education ComponentP30AG019610 · NIA · SUN HEALTH RESEARCH INSTITUTE · PI GONZALEZ HERNANDEZ, GRACIELA · 2001 to 2020
$32.5M
A Virtually Supervised Web-Based Home Exercise Technology for Older AdultsR43AG044882 · NIA · BIOSENSICS, LLC · PI GWIN, JOSEPH T, NAJAFI, BIJAN · 2013 to 2014
$398k
NIA NIH HHS P30 AG019610NIA NIH HHS R43 AG044882
6 · The paper itself

Abstract

Some individuals with mild cognitive impairment (MCI) experience not only cognitive deficits but also a decline in motor function, including postural balance. This pilot study sought to estimate the feasibility, user experience, and effects of a novel sensor-based balance training program. Patients with amnestic MCI (mean age 78.2 yr) were randomized to an intervention group (IG, n = 12) or control group (CG, n = 10). The IG underwent balance training (4 wk, twice a week) that included weight shifting and virtual obstacle crossing. Real-time visual/audio lower-limb motion feedback was provided from wearable sensors. The CG received no training. User experience was measured by a questionnaire. Postintervention effects on balance (center of mass sway during standing with eyes open [EO] and eyes closed), gait (speed, variability), cognition, and fear of falling were measured. Eleven participants (92%) completed the training and expressed fun, safety, and helpfulness of sensor feedback. Sway (EO, p = 0.04) and fear of falling (p = 0.02) were reduced in the IG compared to the CG. Changes in other measures were nonsignificant. Results suggest that the sensor-based training paradigm is well accepted in the target population and beneficial for improving postural control. Future studies should evaluate the added value of the sensor-based training compared to traditional training.

Indexed as

Exercise TherapyFeedback, PhysiologicalPostural BalanceAccidental FallsAgedAged, 80 and overCognitive DysfunctionFemaleGaitHumansMalePilot Projectsbalancebiofeedbackcognitive impairmentdementiaexerciseexergamefall preventionfall riskinteractiveolder adultspostural controlwearable sensor

Identifiers

PMID28475201
PMCPMC6644036
OpenAlexW2594925199

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.