A Statistical Analysis for the Evaluation of the Use of Wearable and Wireless Sensors for Fall Risk Reduction
Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro
2017
Abstract
The aim of this study is to investigate the correlation between, on the one hand, personal and life-style indicators and, on the other hand, the risk of falling. As indicators we consider here for each subject age, body mass index, and information about physical activity habits, while a subject’s risk of falling is estimated by the Mini-BES test score. Three different groups of subjects are taken into account, namely healthy, suffering from metabolic diseases and suffering from cardiovascular diseases. Firstly, we aim at finding explicit linear correlations for any pair of parameters. Secondly, we wish to pay attention to whether or not these correlations change as the health state of the subjects does. The final goal is to move the first steps towards the design of a system composed by wearable sensors, a mobile device, and an app that would be able to help people in improving their life-style so as to decrease their falling risk.
References
- Carroll, R., Cnossen, R., Schnell, M., and Simons, D. (2007). Continua: An interoperable personal healthcare ecosystem. IEEE Pervasive Computing, 6(4):90- 94.
- Craig, C. L., Marshall, A. L., Sjstrm, M., Bauman, A. E., Booth, M. L., Ainsworth, B. E., Pratt, M., Ekelund, U., Yngve, A., Sallis, J. F., and Oja, P. (2003). International physical activity questionnaire: 12-country reliability and validity. Medicine and science in sports and exercise, 35(8):13811395.
- Faulkner, K. A., Cauley, J. A., Studenski, S. A., Landsittel, D. P., Cummings, S. R., Ensrud, K. E., Donaldson, M., Nevitt, M., of Osteoporotic Fractures Research Group, S., et al. (2009). Lifestyle predicts falls independent of physical risk factors. Osteoporosis international, 20(12):2025-2034.
- Forastiere, M., De Pietro, G., and Sannino, G. (2016). An mhealth application for a personalized monitoring of ones own wellness: Design and development. In Innovation in Medicine and Healthcare 2016, pages 269- 278. Springer.
- Franchignoni, F., Horak, F., Godi, M., Nardone, A., and Giordano, A. (2010). Using psychometric techniques to improve the balance evaluation systems test: the mini-bestest. Journal of Rehabilitation Medicine, 42(4):323-331.
- Gardner, M. M., Robertson, M. C., and Campbell, A. J. (2000). Exercise in preventing falls and fall related injuries in older people: a review of randomised controlled trials. British journal of sports medicine, 34(1):7-17.
- Goldberger, A. L., Amaral, L. A., Glass, L., Hausdorff, J. M., Ivanov, P. C., Mark, R. G., Mietus, J. E., Moody, G. B., Peng, C.-K., and Stanley, H. E. (2000). Physiobank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals. Circulation, 101(23):e215-e220.
- Hue, O., Simoneau, M., Marcotte, J., Berrigan, F., Doré, J., Marceau, P., Marceau, S., Tremblay, A., and Teasdale, N. (2007). Body weight is a strong predictor of postural stability. Gait & posture, 26(1):32-38.
- Kempen, G. I., Yardley, L., Van Haastregt, J. C., Zijlstra, G. R., Beyer, N., Hauer, K., and Todd, C. (2008). The short fes-i: a shortened version of the falls efficacy scale-international to assess fear of falling. Age and ageing, 37(1):45-50.
- Ku, P., Osman, N. A., Yusof, A., and Abas, W. W. (2012). Biomechanical evaluation of the relationship between postural control and body mass index. Journal of biomechanics, 45(9):1638-1642.
- Mozumdar, A. and Liguori, G. (2011). Persistent increase of prevalence of metabolic syndrome among us adults: Nhanes iii to nhanes 1999-2006. Diabetes care, 34(1):216-219.
- Pereira, C. L., Baptista, F., and Infante, P. (2014). Role of physical activity in the occurrence of falls and fallrelated injuries in community-dwelling adults over 50 years old. Disability and rehabilitation, 36(2):117- 124.
- Sannino, G., De Falco, I., and De Pietro, G. (2015). A supervised approach to automatically extract a set of rules to support fall detection in an mhealth system. Applied Soft Computing, 34:205-216.
- Sannino, G. and De Pietro, G. (2014). A mobile system for real-time context-aware monitoring of patients health and fainting. International journal of data mining and bioinformatics, 10(4):407-423.
- Santos, D. A. and Duarte, M. (2016). A public data set of human balance evaluations. PeerJ, 4:e2648.
- Shahudin, N. N., Yusof, S. M., Razak, F. A., Sariman, M. H., Azam, M. Z. M., and Norman, W. M. N. W. (2016). Effects of age on physical activity level, strength and balance towards fall risk index among women aged 20-73 years. In Proceedings of the 2nd International Colloquium on Sports Science, Exercise, Engineering and Technology 2015 (ICoSSEET 2015), pages 25-34. Springer.
- Shekharappa, K., Smilee, J. S., Mallikarjuna, P. T., Vedavathi, K. J., and Jayarajan, M. P. (2011). Correlation between body mass index and cardiovascular parameters in obese and non obese in different age groups. International Journal of Biological & Medical Research, 2(2):551-555.
- World Health Organization . Ageing and Life Course Unit (2008). WHO global report on falls prevention in older age. World Health Organization.
- World Health Organization and others (2005). Preventing chronic diseases: a vital investment: Who global report.
Paper Citation
in Harvard Style
Sannino G., De Falco I. and De Pietro G. (2017). A Statistical Analysis for the Evaluation of the Use of Wearable and Wireless Sensors for Fall Risk Reduction . In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: SmartMedDev, (BIOSTEC 2017) ISBN 978-989-758-213-4, pages 508-516. DOI: 10.5220/0006295805080516
in Bibtex Style
@conference{smartmeddev17,
author={Giovanna Sannino and Ivanoe De Falco and Giuseppe De Pietro},
title={A Statistical Analysis for the Evaluation of the Use of Wearable and Wireless Sensors for Fall Risk Reduction},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: SmartMedDev, (BIOSTEC 2017)},
year={2017},
pages={508-516},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006295805080516},
isbn={978-989-758-213-4},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: SmartMedDev, (BIOSTEC 2017)
TI - A Statistical Analysis for the Evaluation of the Use of Wearable and Wireless Sensors for Fall Risk Reduction
SN - 978-989-758-213-4
AU - Sannino G.
AU - De Falco I.
AU - De Pietro G.
PY - 2017
SP - 508
EP - 516
DO - 10.5220/0006295805080516