Literature DB >> 35684760

Static Balance Digital Endpoints with Mon4t: Smartphone Sensors vs. Force Plate.

Keren Tchelet Karlinsky1, Yael Netz2, Jeremy M Jacobs3, Moshe Ayalon2, Ziv Yekutieli1.   

Abstract

Static balance tests are conducted in various clinics for diagnosis and treatment adjustment. As a result of population aging, the accessibility of these tests should be increased, in the clinic, and for remote patient examination. A number of publications have already conducted static balance evaluations using the sensors embedded in a smartphone. This study focuses on the applicability of using smartphone-based balance assessment on a large scale while considering ease of use, safety, and reliability. The Mon4t® app was used to acquire the postural motion using different smartphone devices, different smartphone locations, and various standing postures. The signals derived from the app were compared to the center of pressure displacement derived from a force plate. The results showed moderate to high agreement between the two methods, particularly at the tandem stance (0.69 ≤ r ≤ 0.91). Preliminary data collection was conducted on three healthy participants, followed by 50 additional healthy volunteers, aged 65+. The results demonstrated that the Mon4t app can serve as an accessible and inexpensive static balance assessment tool, both in clinical settings and for remote patient monitoring, which is key for enabling telehealth.

Entities:  

Keywords:  center of pressure; digital endpoints; force plate; mobile app; smartphone; static balance; sway

Mesh:

Year:  2022        PMID: 35684760      PMCID: PMC9185439          DOI: 10.3390/s22114139

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.847


  40 in total

1.  Standing balance evaluation using a triaxial accelerometer.

Authors:  Ruth E Mayagoitia; Joost C Lötters; Peter H Veltink; Hermie Hermens
Journal:  Gait Posture       Date:  2002-08       Impact factor: 2.840

2.  Reference values for the Balance Error Scoring System as measured by the Tekscan MobileMat™ in a physically active population.

Authors:  Megan N Houston; Karen Y Peck; Steven R Malvasi; Sean P Roach; Steven J Svoboda; Kenneth L Cameron
Journal:  Brain Inj       Date:  2018-12-02       Impact factor: 2.311

3.  Smartphone technology can measure postural stability and discriminate fall risk in older adults.

Authors:  Katherine L Hsieh; Kathleen L Roach; Douglas A Wajda; Jacob J Sosnoff
Journal:  Gait Posture       Date:  2018-10-09       Impact factor: 2.840

Review 4.  The relevance of clinical balance assessment tools to differentiate balance deficits.

Authors:  M Mancini; F B Horak
Journal:  Eur J Phys Rehabil Med       Date:  2010-06       Impact factor: 2.874

Review 5.  Gait and balance in the aging population: Fall prevention using innovation and technology.

Authors:  Kavisha Khanuja; Jaclyn Joki; Gloria Bachmann; Sara Cuccurullo
Journal:  Maturitas       Date:  2018-01-31       Impact factor: 4.342

6.  Psychiatric Patients on Neuroleptics: Evaluation of Parkinsonism and Quantified Assessment of Gait.

Authors:  Hila Yahalom; Simon Israeli-Korn; Muli Linder; Ziv Yekutieli; Keren Tchelet Karlinsky; Yarin Rubel; Vered Livneh; Tsvia Fay-Karmon; Sharon Hassin-Baer; Gilad Yahalom
Journal:  Clin Neuropharmacol       Date:  2020 Jan/Feb       Impact factor: 1.592

7.  Quantitative falls risk estimation through multi-sensor assessment of standing balance.

Authors:  Barry R Greene; Denise McGrath; Lorcan Walsh; Emer P Doheny; David McKeown; Chiara Garattini; Clodagh Cunningham; Lisa Crosby; Brian Caulfield; Rose A Kenny
Journal:  Physiol Meas       Date:  2012-11-15       Impact factor: 2.833

8.  The harmonic ratio of trunk acceleration predicts falling among older people: results of a 1-year prospective study.

Authors:  Takehiko Doi; Soichiro Hirata; Rei Ono; Kota Tsutsumimoto; Shogo Misu; Hiroshi Ando
Journal:  J Neuroeng Rehabil       Date:  2013-01-28       Impact factor: 4.262

9.  Validity and reliability of balance assessment software using the Nintendo Wii balance board: usability and validation.

Authors:  Dae-Sung Park; GyuChang Lee
Journal:  J Neuroeng Rehabil       Date:  2014-06-10       Impact factor: 4.262

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