Correlation between new activity-based balance index with accelerometer data and postural balance in elderly woman

authors:

avatar Zahra Asadi Samani , avatar Nader Rahnama , avatar Jalil Reisi ORCID , * , avatar Shahram Lenjan Nejadian

Koomesh: Vol.22, issue 1; 92-98
published online: March 01, 2020
article type: Research Article
received: March 01, 2019
accepted: June 02, 2019

how to cite: Asadi Samani Z, Rahnama N, Reisi J, Lenjan Nejadian S. Correlation between new activity-based balance index with accelerometer data and postural balance in elderly woman. koomesh. 2020;22(1):e153154. 

Abstract

Stability and balance in the elderly are measured using several methods. The purpose of this study was to introduce a new activity based balance index using accelerometer and determine the relationship between this index and postural stability in older woman. Materials and Methods: Ninty-two elderly women were selected and participated in this study. For measuring balanace, One Leg Stance, Berg, Functional Reach, 10 m Walking, Timed Up and Go (TUG) and the Fear of Falling tests were used. During the above tests, the acceleration of the center of the body using three axial accelerometer produced by Didehpardaze Saba Co. was recorded. Results: Data showed significantly negative correlation between balance index and TUG and the 10m walking, respectively (p=0.001, r=-0.503, p=0.001, r=-0664). There was a positive and significant correlation between balance index and fear of falling score (p=0.001, r=0.444). Functional reach test and Berg balance scale significantly correlated with balance index (p=0.001, r=0.395, p=0.001, r=0.336), respectively. The area under curve for receiver operating characteristic (ROC) plots in predicting falling were significant showed sensitivity of 0.857 and a specificity of 0.445. Conclusion: It can be concluded that the use of accelerometer and new balance index is a reliable and valid method for measuring balance of elderly women, which indicates that the ABI can predict falling in the elderly.

References

  • 1.

    Pereira JR, Gobbi S, Teixeira CV, Nascimento CM, Corazza DI, Vital TM, et al. Effects of square-stepping exercise on balance and depressive symptoms in older adults. Motriz: Revista de Educao Fsica 2014; 20: 454-460.

  • 2.

    Teixeira CV, Gobbi S, Pereira JR, Ueno DT, Shigematsu R, Gobbi LT. Effect of squarestepping exercise and basic exercises on functional fitness of older adults. Geriatr Gerontol Int 2013; 13: 842-848.

  • 3.

    Halvarsson A, Dohrn IM, Sthle A. Taking balance training for older adults one step further: the rationale for and a description of a proven balance training programme. Clin Rehabil 2015; 29: 417-425.

  • 4.

    Mirzaie M, Darabi S. Population aging in Iran and rising health care costs. Iran J Aging 2017; 12: 156-169.

  • 5.

    Shigematsu R, Okura T, Sakai T, Rantanen T. Square-stepping exercise versus strength and balance training for fall risk factors. Aging Clin Exp Res 2008; 20: 19-24.

  • 6.

    Borhaninejad V, Rashedi V, Tabe R, Delbari A, Ghasemzadeh H. Relationship between fear of falling and physical activity in older adults. Med J Mashhad Univ Med Sci 2015; 58: 446-452. (Persian).

  • 7.

    Seimetz C, Tan D, Katayama R, Lockhart T. A comparison between methods of measuring postrual stability: force plates versus accelerometers. Biomed Sci Instrum 2012; 48: 386-392.

  • 8.

    Mayagoitia RE, Ltters JC, Veltink PH, Hermens H. Standing balance evaluation using a triaxial accelerometer. Gait Posture 2002; 16: 55-59.

  • 9.

    Kramer AF, Hahn S, Cohen NJ, Banich MT, McAuley E, Harrison CR, et al. Ageing, fitness and neurocognitive function. Nature 1999; 400: 418-419.

  • 10.

    Shigematsu R, Okura T. A novel exercise for improving lower-extremity functional fitness in the elderly. Aging Clin Exp Res 2006; 18: 242-248.

  • 11.

    Shigematsu R, Okura T, Nakagaichi M, Tanaka K, Sakai T, Kitazumi S, Rantanen T. Square-stepping exercise and fall risk factors in older adults: a single-blind, randomized controlled trial. J Gerontol A Biol Sci Med Sci 2008; 63: 76-82.

  • 12.

    Kashani VO, Salmanzade M, Bahrami L. Determination of validity and reliability of the Persian version of the 9-item Berg balance scale in elderly people. J Koomesh 2018; 20: 25-33. (Persian).

  • 13.

    Kashani VO, Zarifkar M, Alinaghipoor Z. Determining validity and reliability of the Persian version of activities-specific balance confidence scale for elderly. J Koomesh 2018; 20: 705-712. (Persian).

  • 14.

    Khajavi D. Validation and reliability of Persian version of fall efficacy scale-international (FES-I) in community-dwelling older adults. Iran J Ageing 2013; 8: 39-47. (Persian).

  • 15.

    O'Sullivan M, Blake C, Cunningham C, Boyle G, Finucane C. Correlation of accelerometry with clinical balance tests in older fallers and non-fallers. Age Ageing 2009; 38: 308-313.

  • 16.

    Doi T, Hirata S, Ono R, Tsutsumimoto K, Misu S, Ando H. The harmonic ratio of trunk acceleration predicts falling among older people: results of a 1-year prospective study. J Neuroeng Rehabil 2013; 10: 7.

  • 17.

    Sun R, Moon Y, McGinnis RS, Seagers K, Motl RW, Sheth N, et al. Assessment of postural sway in individuals with multiple sclerosis using a novel wearable inertial sensor. Digital Biomarkers 2018; 2: 1-10.

  • 18.

    Howcroft J, Kofman J, Lemaire ED. Review of fall risk assessment in geriatric populations using inertial sensors. J Neuroeng Rehabil 2013; 10: 91.

  • 19.

    Caby B, Kieffer S, de Saint Hubert M, Cremer G, Macq B. Feature extraction and selection for objective gait analysis and fall risk assessment by accelerometry. Biomed Eng Online 2011; 10: 1.

  • 20.

    Ganea R, Paraschiv-Ionescu A, Bla C, Rochat S, Aminian K. Multi-parametric evaluation of sit-to-stand and stand-to-sit transitions in elderly people. Med Eng Phys 2011; 33: 1086-1093.

  • 21.

    Giansanti D. Investigation of fall-risk using a wearable device with accelerometers and rate gyroscopes. Physiol Meas 2006; 27: 1081-1090.

  • 22.

    Giansanti D, Maccioni G, Cesinaro S, Benvenuti F, Macellari V. Assessment of fall-risk by means of a neural network based on parameters assessed by a wearable device during posturography. Med Eng Phys 2008; 30: 367-372.

  • 23.

    Gietzelt M, Nemitz G, Wolf KH, Meyer Zu Schwabedissen H, Haux R, Marschollek M. A clinical study to assess fall risk using a single waist accelerometer. Inform Health Soc Care 2009; 34: 181-188.

  • 24.

    Liu Y, Redmond SJ, Narayanan MR, Lovell NH. Classification between non-multiple fallers and multiple fallers using a triaxial accelerometry-based system. in 2011 annual international conference of the IEEE engineering in medicine and biology society. 2011; 1499-1502.

  • 25.

    Weiss A, Herman T, Plotnik M, Brozgol M, Giladi N, Hausdorff JM. An instrumented timed up and go: the added value of an accelerometer for identifying fall risk in idiopathic fallers. Physiol Meas 2011; 32: 2003-2018.