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Divandari N, Bird ML, Vakili M, Jaberzadeh S. The association between dynamic balance and executive function: Which dynamic balance test has the strongest association with executive function? A systematic review and meta-analysis. Curr Neurol Neurosci Rep 2024; 24:151-161. [PMID: 38730213 PMCID: PMC11143012 DOI: 10.1007/s11910-024-01340-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/02/2024] [Indexed: 05/12/2024]
Abstract
AIM The aging global population poses increasing challenges related to falls and dementia. Early identification of cognitive decline, particularly before noticeable symptoms manifest, is crucial for effective intervention. This review aims to determine the dynamic balance test most closely associated with executive function, potentially serving as a biomarker for cognitive decline. RECENT FINDINGS Based on recent reviews, inhibitory control, a component of executive function, holds significance in influencing balance performance. Studies suggest that the strength of the correlation between cognition and balance tends to be domain-specific and task-specific. Despite these findings, inconclusive evidence remains regarding the connection between executive function and various dynamic balance assessments. Our review identifies a significant association between all dynamic balance tests and executive function, albeit with varying strengths. Notably, a medium effect size is observed for the Timed Up and Go and Functional Reach Test, a small effect size for balance scales, and a strong effect size for postural sway. This review underscores a clear relationship between dynamic balance task performance and executive function. Dynamic posturography holds potential as a clinical biomarker for early detection of cognitive decline, with a note of caution due to observed heterogeneity and limited studies.
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Affiliation(s)
- Nahid Divandari
- Monash Neuromodulation Research Unit, Department of Physiotherapy, School of Primary and Allied Health Care, Faculty of Medicine, Nursing and Health Science, Monash University, PO Box 527, Melbourne, Frankston, VIC, 3199, Australia.
| | - Marie-Louise Bird
- School of Health Sciences, University of Tasmania, Newnham Tasmania, 7248, Australia
| | | | - Shapour Jaberzadeh
- Monash Neuromodulation Research Unit, Department of Physiotherapy, School of Primary and Allied Health Care, Faculty of Medicine, Nursing and Health Science, Monash University, PO Box 527, Melbourne, Frankston, VIC, 3199, Australia
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Jamshed M, Shahzad A, Riaz F, Kim K. Exploring inertial sensor-based balance biomarkers for early detection of mild cognitive impairment. Sci Rep 2024; 14:9829. [PMID: 38684687 PMCID: PMC11059265 DOI: 10.1038/s41598-024-59928-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 04/16/2024] [Indexed: 05/02/2024] Open
Abstract
Dementia is characterized by a progressive loss of cognitive abilities, and diagnosing its early stages Mild Cognitive Impairment (MCI), is difficult since it is a transitory state that is different from total cognitive collapse. Recent clinical research studies have identified that balance impairments can be a significant indicator for predicting dementia in older adults. Accordingly, the current research focuses on finding innovative postural balance-based digital biomarkers by using wearable inertial sensors and pre-screening of MCI in home settings using machine learning techniques. For this research, sixty subjects (30 cognitively normal and 30 MCI) with waist-mounted inertial sensor performed balance tasks in four different standing postures: eyes-open, eyes-closed, right-leg-lift, and left-leg-lift. The significant balance biomarkers for MCI identification are discovered by our research, demonstrating specific characteristics in each of these four states. A robust feature selection approach is ensured by the multi-step methodology that combines the strengths of Filter techniques, Wrapper methods, and SHAP (Shapley Additive exPlanations) technique. The proposed balance biomarkers have the potential to detect MCI (with 75.8% accuracy), as evidenced by the results of machine learning algorithms for classification. This work adds to the growing body of literature targeted at enhancing understanding and proactive management of cognitive loss in older populations and lays the groundwork for future research efforts aimed at refining digital biomarkers, validating findings, and exploring longitudinal perspectives.
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Affiliation(s)
- Mobeena Jamshed
- Department of Computer and Software Engineering, National University of Sciences and Technology, Islamabad, 44000, Pakistan
| | - Ahsan Shahzad
- Department of Computer and Software Engineering, National University of Sciences and Technology, Islamabad, 44000, Pakistan.
| | - Farhan Riaz
- School of Computer Science, University of Lincoln, Lincoln, LN67TS, UK
| | - Kiseon Kim
- School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, 61005, South Korea
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Schmidt L, Zieschang T, Koschate J, Stuckenschneider T. Impaired Standing Balance in Older Adults with Cognitive Impairment after a Severe Fall. Gerontology 2024; 70:755-763. [PMID: 38679005 DOI: 10.1159/000538598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 03/26/2024] [Indexed: 05/01/2024] Open
Abstract
INTRODUCTION Fall-related sequelae as well as balance and gait impairments are more pronounced in older adults who are cognitively impaired (OACI) compared to older adults who are cognitively healthy (OACH). Evidence is scarce about differences in standing balance and gait in OACH and OACI after a fall, even though these are major risks for recurrent falls. Thus, the aim of this study was to investigate early impairments in gait and balance, by adding inertial measurement units (IMUs) to a functional performance test in OACH and OACI after a severe fall with a presentation to the emergency department (ED) and immediate discharge. METHODS The study sample was stratified into participants with and without probable cognitive impairment using the result of the Montreal Cognitive Assessment total score (maximum of 30 points). The cutoff for probable cognitive impairment was set at ≤ 24. Standing balance and gait parameters were measured using three IMUs in n = 69 OACH (72.0 ± 8.2 years) and n = 76 OACI (78.7 ± 8.1 years). Data were collected at participants' homes as part of a comprehensive geriatric assessment in the "SeFallED" study within 4 weeks after presentation to the ED after a severe fall (German Clinical Trials Register ID: 00025949). ANCOVA was used for statistical analysis, adjusted for age. RESULTS The data indicated significantly more sway for OACI compared to OACH during balance tasks, whereas no differences in gait behavior were found. In detail, differences in standing balance were revealed for mean velocity (m/s) during parallel stance with eyes open (ηp2 = 0.190, p < 0.001) and eyes closed on a balance cushion (ηp2 = 0.059, p = 0.029), as well as during tandem stance (ηp2 = 0.034, p = 0.044) between OACI and OACH. Further differences between the two groups were detected for path length (m/s2) during parallel stance with eyes open (ηp2 = 0.144, p < 0.001) and eyes closed (ηp2 = 0.044, p < 0.027) and for range (m/s2) during tandem (ηp2 = 0.036, p = 0.036) and parallel stance with eyes closed (ηp2 = 0.045, p = 0.032). CONCLUSION Even though both groups have experienced a severe fall with presentation to the ED in the preceding 4 weeks, balance control among OACI indicated a higher fall risk than among OACH. Therefore, effective secondary fall prevention efforts have to be established, particularly for OACI.
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Affiliation(s)
- Laura Schmidt
- Department for Health Services Research, Geriatric Medicine/ School of Medicine and Health Services/Carl von Ossietzky University, Oldenburg, Germany
| | - Tania Zieschang
- Department for Health Services Research, Geriatric Medicine/ School of Medicine and Health Services/Carl von Ossietzky University, Oldenburg, Germany
| | - Jessica Koschate
- Department for Health Services Research, Geriatric Medicine/ School of Medicine and Health Services/Carl von Ossietzky University, Oldenburg, Germany
| | - Tim Stuckenschneider
- Department for Health Services Research, Geriatric Medicine/ School of Medicine and Health Services/Carl von Ossietzky University, Oldenburg, Germany
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Sjaelland NS, Gramkow MH, Hasselbalch SG, Frederiksen KS. Digital Biomarkers for the Assessment of Non-Cognitive Symptoms in Patients with Dementia with Lewy Bodies: A Systematic Review. J Alzheimers Dis 2024; 100:431-451. [PMID: 38943394 PMCID: PMC11307079 DOI: 10.3233/jad-240327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/14/2024] [Indexed: 07/01/2024]
Abstract
Background Portable digital health technologies (DHTs) could help evaluate non-cognitive symptoms, but evidence to support their use in patients with dementia with Lewy bodies (DLB) is uncertain. Objective 1) To describe portable or wearable DHTs used to obtain digital biomarkers in patients with DLB, 2) to assess the digital biomarkers' ability to evaluate non-cognitive symptoms, and 3) to assess the feasibility of applying digital biomarkers in patients with DLB. Methods We systematically searched databases MEDLINE, Embase, and Web of Science from inception through February 28, 2023. Studies assessing digital biomarkers obtained by portable or wearable DHTs and related to non-cognitive symptoms were eligible if including patients with DLB. The quality of studies was assessed using a modified check list based on the NIH Quality assessment tool for Observational Cohort and Cross-sectional Studies. A narrative synthesis of data was carried out. Results We screened 4,295 records and included 20 studies. Seventeen different DHTs were identified for assessment of most non-cognitive symptoms related to DLB. No thorough validation of digital biomarkers for measurement of non-cognitive symptoms in DLB was reported. Studies did not report on aspects of feasibility in a systematic way. Conclusions Knowledge about feasibility and validity of individual digital biomarkers remains extremely limited. Study heterogeneity is a barrier for establishing a broad evidence base for application of digital biomarkers in DLB. Researchers should conform to recommended standards for systematic evaluation of digital biomarkers.
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Affiliation(s)
- Nikolai S. Sjaelland
- Danish Dementia Research Centre, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Mathias H. Gramkow
- Danish Dementia Research Centre, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Steen G. Hasselbalch
- Danish Dementia Research Centre, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kristian Steen Frederiksen
- Danish Dementia Research Centre, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Tam W, Alajlani M, Abd-Alrazaq A. An Exploration of Wearable Device Features Used in UK Hospital Parkinson Disease Care: Scoping Review. J Med Internet Res 2023; 25:e42950. [PMID: 37594791 PMCID: PMC10474516 DOI: 10.2196/42950] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 03/13/2023] [Accepted: 04/14/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND The prevalence of Parkinson disease (PD) is becoming an increasing concern owing to the aging population in the United Kingdom. Wearable devices have the potential to improve the clinical care of patients with PD while reducing health care costs. Consequently, exploring the features of these wearable devices is important to identify the limitations and further areas of investigation of how wearable devices are currently used in clinical care in the United Kingdom. OBJECTIVE In this scoping review, we aimed to explore the features of wearable devices used for PD in hospitals in the United Kingdom. METHODS A scoping review of the current research was undertaken and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The literature search was undertaken on June 6, 2022, and publications were obtained from MEDLINE or PubMed, Embase, and the Cochrane Library. Eligible publications were initially screened by their titles and abstracts. Publications that passed the initial screening underwent a full review. The study characteristics were extracted from the final publications, and the evidence was synthesized using a narrative approach. Any queries were reviewed by the first and second authors. RESULTS Of the 4543 publications identified, 39 (0.86%) publications underwent a full review, and 20 (0.44%) publications were included in the scoping review. Most studies (11/20, 55%) were conducted at the Newcastle upon Tyne Hospitals NHS Foundation Trust, with sample sizes ranging from 10 to 418. Most study participants were male individuals with a mean age ranging from 57.7 to 78.0 years. The AX3 was the most popular device brand used, and it was commercially manufactured by Axivity. Common wearable device types included body-worn sensors, inertial measurement units, and smartwatches that used accelerometers and gyroscopes to measure the clinical features of PD. Most wearable device primary measures involved the measured gait, bradykinesia, and dyskinesia. The most common wearable device placements were the lumbar region, head, and wrist. Furthermore, 65% (13/20) of the studies used artificial intelligence or machine learning to support PD data analysis. CONCLUSIONS This study demonstrated that wearable devices could help provide a more detailed analysis of PD symptoms during the assessment phase and personalize treatment. Using machine learning, wearable devices could differentiate PD from other neurodegenerative diseases. The identified evidence gaps include the lack of analysis of wearable device cybersecurity and data management. The lack of cost-effectiveness analysis and large-scale participation in studies resulted in uncertainty regarding the feasibility of the widespread use of wearable devices. The uncertainty around the identified research gaps was further exacerbated by the lack of medical regulation of wearable devices for PD, particularly in the United Kingdom where regulations were changing due to the political landscape.
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Affiliation(s)
- William Tam
- Insitute of Digital Healthcare, Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom
| | - Mohannad Alajlani
- Insitute of Digital Healthcare, Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom
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Yamada Y, Shinkawa K, Nemoto M, Ota M, Nemoto K, Arai T. Speech and language characteristics differentiate Alzheimer's disease and dementia with Lewy bodies. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12364. [PMID: 36320609 PMCID: PMC9614050 DOI: 10.1002/dad2.12364] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 09/11/2022] [Indexed: 11/04/2022]
Abstract
Introduction Early differential diagnosis of Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) is important, but it remains challenging. Different profiles of speech and language impairments between AD and DLB have been suggested, but direct comparisons have not been investigated. Methods We collected speech responses from 121 older adults comprising AD, DLB, and cognitively normal (CN) groups and investigated their acoustic, prosodic, and linguistic features. Results The AD group showed larger differences from the CN group than the DLB group in linguistic features, while the DLB group showed larger differences in prosodic and acoustic features. Machine-learning classifiers using these speech features achieved 87.0% accuracy for AD versus CN, 93.2% for DLB versus CN, and 87.4% for AD versus DLB. Discussion Our findings indicate the discriminative differences in speech features in AD and DLB and the feasibility of using these features in combination as a screening tool for identifying/differentiating AD and DLB.
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Affiliation(s)
| | | | - Miyuki Nemoto
- Department of PsychiatryDivision of Clinical MedicineFaculty of MedicineUniversity of TsukubaTsukubaIbarakiJapan
| | - Miho Ota
- Department of PsychiatryDivision of Clinical MedicineFaculty of MedicineUniversity of TsukubaTsukubaIbarakiJapan
| | - Kiyotaka Nemoto
- Department of PsychiatryDivision of Clinical MedicineFaculty of MedicineUniversity of TsukubaTsukubaIbarakiJapan
| | - Tetsuaki Arai
- Department of PsychiatryDivision of Clinical MedicineFaculty of MedicineUniversity of TsukubaTsukubaIbarakiJapan
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Tam W, Alajlani M, Abd-alrazaq A. An Exploration of Wearable Device Features Used in UK Hospital Parkinson Disease Care: Scoping Review (Preprint).. [DOI: 10.2196/preprints.42950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
BACKGROUND
The prevalence of Parkinson disease (PD) is becoming an increasing concern owing to the aging population in the United Kingdom. Wearable devices have the potential to improve the clinical care of patients with PD while reducing health care costs. Consequently, exploring the features of these wearable devices is important to identify the limitations and further areas of investigation of how wearable devices are currently used in clinical care in the United Kingdom.
OBJECTIVE
In this scoping review, we aimed to explore the features of wearable devices used for PD in hospitals in the United Kingdom.
METHODS
A scoping review of the current research was undertaken and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The literature search was undertaken on June 6, 2022, and publications were obtained from MEDLINE or PubMed, Embase, and the Cochrane Library. Eligible publications were initially screened by their titles and abstracts. Publications that passed the initial screening underwent a full review. The study characteristics were extracted from the final publications, and the evidence was synthesized using a narrative approach. Any queries were reviewed by the first and second authors.
RESULTS
Of the 4543 publications identified, 39 (0.86%) publications underwent a full review, and 20 (0.44%) publications were included in the scoping review. Most studies (11/20, 55%) were conducted at the Newcastle upon Tyne Hospitals NHS Foundation Trust, with sample sizes ranging from 10 to 418. Most study participants were male individuals with a mean age ranging from 57.7 to 78.0 years. The AX3 was the most popular device brand used, and it was commercially manufactured by Axivity. Common wearable device types included body-worn sensors, inertial measurement units, and smartwatches that used accelerometers and gyroscopes to measure the clinical features of PD. Most wearable device primary measures involved the measured gait, bradykinesia, and dyskinesia. The most common wearable device placements were the lumbar region, head, and wrist. Furthermore, 65% (13/20) of the studies used artificial intelligence or machine learning to support PD data analysis.
CONCLUSIONS
This study demonstrated that wearable devices could help provide a more detailed analysis of PD symptoms during the assessment phase and personalize treatment. Using machine learning, wearable devices could differentiate PD from other neurodegenerative diseases. The identified evidence gaps include the lack of analysis of wearable device cybersecurity and data management. The lack of cost-effectiveness analysis and large-scale participation in studies resulted in uncertainty regarding the feasibility of the widespread use of wearable devices. The uncertainty around the identified research gaps was further exacerbated by the lack of medical regulation of wearable devices for PD, particularly in the United Kingdom where regulations were changing due to the political landscape.
CLINICALTRIAL
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Yamada Y, Kobayashi M, Shinkawa K, Nemoto M, Ota M, Nemoto K, Arai T. Characteristics of Drawing Process Differentiate Alzheimer’s Disease and Dementia with Lewy Bodies. J Alzheimers Dis 2022; 90:693-704. [DOI: 10.3233/jad-220546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Early differential diagnosis of Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB) is important for treatment and disease management, but it remains challenging. Although computer-based drawing analysis may help differentiate AD and DLB, it has not been extensively studied. Objective: We aimed to identify the differences in features characterizing the drawing process between AD, DLB, and cognitively normal (CN) individuals, and to evaluate the validity of using these features to identify and differentiate AD and DLB. Methods: We collected drawing data with a digitizing tablet and pen from 123 community-dwelling older adults in three clinical diagnostic groups of mild cognitive impairment or dementia due to AD (n = 47) or Lewy body disease (LBD; n = 27), and CN (n = 49), matched for their age, sex, and years of education. We then investigated drawing features in terms of the drawing speed, pressure, and pauses. Results: Reduced speed and reduced smoothness in speed and pressure were observed particularly in the LBD group, while increased pauses and total durations were observed in both the AD and LBD groups. Machine-learning models using these features achieved an area under the receiver operating characteristic curve (AUC) of 0.80 for AD versus CN, 0.88 for LBD versus CN, and 0.77 for AD versus LBD. Conclusion: Our results indicate how different types of drawing features were particularly discriminative between the diagnostic groups, and how the combination of these features can facilitate the identification and differentiation of AD and DLB.
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Affiliation(s)
| | | | | | - Miyuki Nemoto
- Department of Psychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan
| | - Miho Ota
- Department of Psychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan
| | - Kiyotaka Nemoto
- Department of Psychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan
| | - Tetsuaki Arai
- Department of Psychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan
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Estévez-Pedraza ÁG, Hernandez-Laredo E, Millan-Guadarrama ME, Martínez-Méndez R, Carrillo-Vega MF, Parra-Rodríguez L. Reliability and Usability Analysis of an Embedded System Capable of Evaluating Balance in Elderly Populations Based on a Modified Wii Balance Board. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:11026. [PMID: 36078742 PMCID: PMC9518410 DOI: 10.3390/ijerph191711026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/26/2022] [Accepted: 08/30/2022] [Indexed: 06/15/2023]
Abstract
This paper analyzes the reliability and usability of a portable electronic instrument that measures balance and balance impairment in older adults. The center of pressure (CoP) metrics are measured with a modified Wii Balance Board (mWBB) platform. In the intra- and inter-rater testing, 16 and 43 volunteers (mean 75.66 and standard deviation (SD) of 7.86 years and 72.61 (SD 7.86) years, respectively) collaborated. Five volunteer raters (5.1 (SD 3.69) years of experience) answered the System Usability Scale (SUS). The most reliable CoP index in the intra-examiner tests was the 95% power frequency in the medial-lateral displacement of the CoP with closed-eyes. It had excellent reliability with an intraclass correlation coefficient ICC = 0.948 (C.I. 0.862-0.982) and a Pearson's correlation coefficient PCC = 0.966 (p < 0.001). The best index for the inter-rater reliability was the centroidal frequency in the anterior-posterior direction closed-eyes, which had an ICC (2,1) = 0.825. The mWBB also obtained a high usability score. These results support the mWBB as a reliable complementary tool for measuring balance in older adults. Additionally, it does not have the limitations of laboratory-grade systems and clinical screening instruments.
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Affiliation(s)
- Ángel Gabriel Estévez-Pedraza
- Faculty of Medicine, Universidad Autónoma del Estado de México, Toluca de Lerdo 50180, Mexico
- Faculty of Engineering, Universidad Autónoma del Estado de México, Toluca de Lerdo 50100, Mexico
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