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      Association between upper limb movements during drumming and cognition in older adults with cognitive impairment and dementia at a nursing home: a pilot study

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          Abstract

          Background

          Despite the association between motor dysfunction and dementia, quantitative assessment of dementia-related specific motor dysfunction in patients with severe dementia is difficult. Thus, this study aimed to develop a new method to measure upper limb motor function in people with dementia.

          Methods

          We examined the relationship between dementia severity and dementia-related specific motor dysfunction using the Mini-Mental State Examination (MMSE), a dementia screening test. Participants comprised 16 nursing home residents with a mean age of 86 years and MMSE score of 14.56 (range, 1–23) Points. Participants were seated in a circle and instructed to play a drum that was placed in their lap using mallets (drumsticks) in their dominant hand. Acceleration and gyroscopic sensors were attached to their wrists to collect data on arm movements while drumming. Upper limb motor characteristics were confirmed by recording acceleration and arm movement during drumming and analyzing the correlation with handgrip strength.

          Results

          Handgrip strength was correlated with arm elevation angle during drumming. The arm elevation angle displayed a significant regression equation with the MMSE score and showed the best regression equation along with handgrip strength (adjusted R 2 = 0.6035, p = 0.0009).

          Conclusion

          We developed a new method using drums to measure upper limb motor function in people with dementia. We also verified that the average arm elevation angle during drumming could predict cognitive dysfunction. This system may be used to monitor people with dementia in a simple and safe way.

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          Most cited references88

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment

            Clinical and research interest in sarcopenia has burgeoned internationally, Asia included. The Asian Working Group for Sarcopenia (AWGS) 2014 consensus defined sarcopenia as "age-related loss of muscle mass, plus low muscle strength, and/or low physical performance" and specified cutoffs for each diagnostic component; research in Asia consequently flourished, prompting this update. AWGS 2019 retains the previous definition of sarcopenia but revises the diagnostic algorithm, protocols, and some criteria: low muscle strength is defined as handgrip strength <28 kg for men and <18 kg for women; criteria for low physical performance are 6-m walk <1.0 m/s, Short Physical Performance Battery score ≤9, or 5-time chair stand test ≥12 seconds. AWGS 2019 retains the original cutoffs for height-adjusted muscle mass: dual-energy X-ray absorptiometry, <7.0 kg/m2 in men and <5.4 kg/m2 in women; and bioimpedance, <7.0 kg/m2 in men and <5.7 kg/m2 in women. In addition, the AWGS 2019 update proposes separate algorithms for community vs hospital settings, which both begin by screening either calf circumference (<34 cm in men, <33 cm in women), SARC-F (≥4), or SARC-CalF (≥11), to facilitate earlier identification of people at risk for sarcopenia. Although skeletal muscle strength and mass are both still considered fundamental to a definitive clinical diagnosis, AWGS 2019 also introduces "possible sarcopenia," defined by either low muscle strength or low physical performance only, specifically for use in primary health care or community-based health promotion, to enable earlier lifestyle interventions. Although defining sarcopenia by body mass index-adjusted muscle mass instead of height-adjusted muscle mass may predict adverse outcomes better, more evidence is needed before changing current recommendations. Lifestyle interventions, especially exercise and nutritional supplementation, prevail as mainstays of treatment. Further research is needed to investigate potential long-term benefits of lifestyle interventions, nutritional supplements, or pharmacotherapy for sarcopenia in Asians.
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              Epidemiology of Sarcopenia among the Elderly in New Mexico

              Muscle mass decreases with age, leading to "sarcopenia," or low relative muscle mass, in elderly people. Sarcopenia is believed to be associated with metabolic, physiologic, and functional impairments and disability. Methods of estimating the prevalence of sarcopenia and its associated risks in elderly populations are lacking. Data from a population-based survey of 883 elderly Hispanic and non-Hispanic white men and women living in New Mexico (the New Mexico Elder Health Survey, 1993-1995) were analyzed to develop a method for estimating the prevalence of sarcopenia. An anthropometric equation for predicting appendicular skeletal muscle mass was developed from a random subsample (n = 199) of participants and was extended to the total sample. Sarcopenia was defined as appendicular skeletal muscle mass (kg)/height2 (m2) being less than two standard deviations below the mean of a young reference group. Prevalences increased from 13-24% in persons under 70 years of age to >50% in persons over 80 years of age, and were slightly greater in Hispanics than in non-Hispanic whites. Sarcopenia was significantly associated with self-reported physical disability in both men and women, independent of ethnicity, age, morbidity, obesity, income, and health behaviors. This study provides some of the first estimates of the extent of the public health problem posed by sarcopenia.
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                Author and article information

                Contributors
                Journal
                Front Rehabil Sci
                Front Rehabil Sci
                Front. Rehabil. Sci.
                Frontiers in Rehabilitation Sciences
                Frontiers Media S.A.
                2673-6861
                2673-6861
                25 May 2023
                2023
                : 4
                : 1079781
                Affiliations
                [ 1 ]Information Somatics Laboratory, Research Center for Advanced Science and Technology, The University of Tokyo , Tokyo, Japan
                [ 2 ]Computational Engineering Applications Unit, Head Office for Information Systems and Cybersecurity, RIKEN , Saitama, Japan
                [ 3 ]Moff Inc. , Tokyo, Japan
                [ 4 ]Department of Public Health, Kobe University Graduate School of Health Sciences, Kobe University , Kobe, Japan
                [ 5 ]Super Reha, LLC. , Tokyo, Japan
                [ 6 ]Care 21 Co., Ltd. , Osaka, Japan
                [ 7 ]Student and Staff Health Support Center, Tokyo Medical University , Tokyo, Japan
                [ 8 ]Center for the Promotion of Social Data Science Education and Research, Hitotsubashi University , Tokyo, Japan
                [ 9 ]2LPN (Laboratoire Lorrain de Psychologie et Neurosciences de la Dynamique des Comportements), Université de Lorraine , Nancy, France
                [ 10 ]Department of Cognitive Health Science, Institute of Development, Aging and Cancer (IDAC), Tohoku University , Sendai, Japan
                [ 11 ]Smart Aging Research Center, Tohoku University , Sendai, Japan
                Author notes

                Edited by: Shuo-Hsiu (James) Chang, University of Texas Health Science Center at Houston, United States

                Reviewed by: Kornanong Yuenyongchaiwat, Thammasat University, Thailand Bin Huang, BrainCheck Inc, United States

                [* ] Correspondence: Atsuko Miyazaki miyazaki@ 123456star.rcast.u-tokyo.ac.jp

                Abbreviations ADLs, activities of daily living; AIC, Akaike information criterion; AD, Alzheimer's disease; BIA, bioelectrical impedance analysis; BMI, body mass index; MCI, mild cognitive impairment; MMSE, Mini-Mental State Examination; MoCA, Montreal Cognitive Assessment; RAS, Rhythmic auditory stimulation; PIP, Proximal Inter-Phalangeal; ROM, range of motion; sd, standard deviation; SMI, skeletal muscle mass index; VIF, variance inflation factor.

                Article
                10.3389/fresc.2023.1079781
                10281057
                9111f6c9-715a-45fe-a377-21554a3fb65d
                © 2023 Miyazaki, Ito, Okuyama, Mori, Sato, Ichiki, Hiyama, Dinet and Nouchi.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 28 October 2022
                : 05 May 2023
                Page count
                Figures: 1, Tables: 4, Equations: 3, References: 81, Pages: 0, Words: 0
                Funding
                Funded by: JSPS
                Award ID: 16K15363
                Funded by: Japan Society for the Promotion of Science
                This work was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant-in-Aid for Challenging Exploratory Research (grant no. 16K15363).
                Categories
                Rehabilitation Sciences
                Original Research
                Custom metadata
                Interventions for Rehabilitation

                upper limb motor function,upper limb range of motion,drum,acceleration sensors,gyro sensors

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