Literature DB >> 32095755

Assessment of Postural Sway in Individuals with Multiple Sclerosis Using a Novel Wearable Inertial Sensor.

Ruopeng Sun1, Yaejin Moon1, Ryan S McGinnis2, Kirsten Seagers3, Robert W Motl4, Nirav Sheth3, John A Wright3, Roozbeh Ghaffari3, Shyamal Patel3, Jacob J Sosnoff1.   

Abstract

Balance impairment is common in individuals with multiple sclerosis (MS). However, objective assessment of balance usually requires clinical expertise and/or the use of expensive and obtrusive measuring equipment. These barriers to the objective assessment of balance may be overcome with the development of a lightweight inertial sensor system. In this study, we examined the concurrent validity of a novel wireless, skin-mounted inertial sensor system (BioStamp®, MC10 Inc.) to measure postural sway in individuals with MS by comparing measurement agreement between this novel sensor and gold standard measurement tools (force plate and externally validated inertial sensor). A total of 39 individuals with MS and 15 healthy controls participated in the study. Participants with MS were divided into groups based on the amount of impairment (MS<sub>Mild</sub>: EDSS 2-4, n = 19; MS<sub>Severe</sub>: EDSS ≥6, n = 20). The balance assessment consisted of two 30-s quiet standing trials in each of three conditions: eyes open/firm surface, eyes closed/firm surface, and eyes open/foam surface. For each trial, postural sway was recorded with a force plate (Bertec) and simultaneously using two accelerometers (BioStamp and Xsens) mounted on the participant's posterior trunk at L5. Sway metrics (sway area, sway path length, root mean square amplitude, mean velocity, JERK, and total power) were derived to compare the measurement agreement among the measurement devices. Excellent agreement (intraclass correlation coefficients >0.9) between sway metrics derived from the BioStamp and the MTx sensors were observed across all conditions and groups. Good to excellent correlations (r >0.7) between devices were observed in all sway metrics and conditions. Additionally, the acceleration sway metrics were nearly as effective as the force plate sway metrics in differentiating individuals with poor balance from healthy controls. Overall, the BioStamp sensor is a valid and objective measurement tool for postural sway assessment. This novel, lightweight and portable sensor may offer unique advantages in tracking patient's postural performance.
Copyright © 2018 by S. Karger AG, Basel.

Entities:  

Keywords:  Inertial sensors; Multiple sclerosis; Postural sway

Year:  2018        PMID: 32095755      PMCID: PMC7015350          DOI: 10.1159/000485958

Source DB:  PubMed          Journal:  Digit Biomark        ISSN: 2504-110X


  23 in total

1.  Trunk accelerometry as a measure of balance control during quiet standing.

Authors:  Rolf Moe-Nilssen; Jorunn L Helbostad
Journal:  Gait Posture       Date:  2002-08       Impact factor: 2.840

2.  Body-worn motion sensors detect balance and gait deficits in people with multiple sclerosis who have normal walking speed.

Authors:  R I Spain; R J St George; A Salarian; M Mancini; J M Wagner; F B Horak; D Bourdette
Journal:  Gait Posture       Date:  2012-01-25       Impact factor: 2.840

3.  Frailty assessment based on wavelet analysis during quiet standing balance test.

Authors:  A Martínez-Ramírez; P Lecumberri; M Gómez; L Rodriguez-Mañas; F J García; M Izquierdo
Journal:  J Biomech       Date:  2011-06-30       Impact factor: 2.712

4.  The Activities-specific Balance Confidence (ABC) Scale.

Authors:  L E Powell; A M Myers
Journal:  J Gerontol A Biol Sci Med Sci       Date:  1995-01       Impact factor: 6.053

Review 5.  Postural control in multiple sclerosis: implications for fall prevention.

Authors:  Michelle H Cameron; Stephen Lord
Journal:  Curr Neurol Neurosci Rep       Date:  2010-09       Impact factor: 5.081

6.  Disease steps in multiple sclerosis: a longitudinal study comparing disease steps and EDSS to evaluate disease progression.

Authors:  M J Hohol; E J Orav; H L Weiner
Journal:  Mult Scler       Date:  1999-10       Impact factor: 6.312

7.  Assessing postural control and postural control strategy in diabetes patients using innovative and wearable technology.

Authors:  Bijan Najafi; Deena Horn; Samuel Marclay; Ryan T Crews; Stephanie Wu; James S Wrobel
Journal:  J Diabetes Sci Technol       Date:  2010-07-01

8.  Abnormalities in posturography and estimations of visual vertical and horizontal in multiple sclerosis.

Authors:  R T Jackson; C M Epstein; W R De l'Aune
Journal:  Am J Otol       Date:  1995-01

Review 9.  Objective biomarkers of balance and gait for Parkinson's disease using body-worn sensors.

Authors:  Fay B Horak; Martina Mancini
Journal:  Mov Disord       Date:  2013-09-15       Impact factor: 10.338

10.  ISway: a sensitive, valid and reliable measure of postural control.

Authors:  Martina Mancini; Arash Salarian; Patricia Carlson-Kuhta; Cris Zampieri; Laurie King; Lorenzo Chiari; Fay B Horak
Journal:  J Neuroeng Rehabil       Date:  2012-08-22       Impact factor: 4.262

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  16 in total

Review 1.  The Digital Neurologic Examination.

Authors:  Adam B Cohen; Brain V Nahed
Journal:  Digit Biomark       Date:  2021-04-26

2.  A New Wearable System for Home Sleep Apnea Testing, Screening, and Classification.

Authors:  Alessandro Manoni; Federico Loreti; Valeria Radicioni; Daniela Pellegrino; Luigi Della Torre; Alessandro Gumiero; Damian Halicki; Paolo Palange; Fernanda Irrera
Journal:  Sensors (Basel)       Date:  2020-12-08       Impact factor: 3.576

3.  Metrics extracted from a single wearable sensor during sit-stand transitions relate to mobility impairment and fall risk in people with multiple sclerosis.

Authors:  Lindsey J Tulipani; Brett Meyer; Dale Larie; Andrew J Solomon; Ryan S McGinnis
Journal:  Gait Posture       Date:  2020-06-20       Impact factor: 2.840

4.  Investigation of postural control and spatiotemporal parameters of gait during dual tasks in ataxic individuals.

Authors:  Gülşah Sütçü; Mert Doğan; Semra Topuz
Journal:  Neurol Sci       Date:  2022-07-07       Impact factor: 3.830

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

Authors:  Keren Tchelet Karlinsky; Yael Netz; Jeremy M Jacobs; Moshe Ayalon; Ziv Yekutieli
Journal:  Sensors (Basel)       Date:  2022-05-30       Impact factor: 3.847

Review 6.  An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis.

Authors:  Katherine Hope Kenyon; Frederique Boonstra; Gustavo Noffs; Helmut Butzkueven; Adam P Vogel; Scott Kolbe; Anneke van der Walt
Journal:  Cerebellum       Date:  2022-06-27       Impact factor: 3.648

7.  Structural Neural Correlates of Impaired Postural Control in People with Secondary Progressive Multiple Sclerosis.

Authors:  Ishu Arpan; Brett Fling; Katherine Powers; Fay B Horak; Rebecca I Spain
Journal:  Int J MS Care       Date:  2019-08-29

8.  Anxiety does not always affect balance: the predominating role of cognitive engagement in a video gaming task.

Authors:  B S DeCouto; A M Williams; K R Lohse; S H Creem-Regehr; D L Strayer; P C Fino
Journal:  Exp Brain Res       Date:  2021-04-28       Impact factor: 2.064

9.  Internal Consistency of Sway Measures via Embedded Head-Mounted Accelerometers: Implications for Neuromotor Investigations.

Authors:  Andrew P Lapointe; Jessica N Ritchie; Rachel V Vitali; Joel S Burma; Ateyeh Soroush; Ibukunoluwa Oni; Jeff F Dunn
Journal:  Sensors (Basel)       Date:  2021-06-30       Impact factor: 3.576

10.  Evaluation of Concurrent Validity between a Smartphone Self-Test Prototype and Clinical Instruments for Balance and Leg Strength.

Authors:  Linda Mansson; Pernilla Bäckman; Fredrik Öhberg; Jonas Sandlund; Jonas Selling; Marlene Sandlund
Journal:  Sensors (Basel)       Date:  2021-03-04       Impact factor: 3.576

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