A prospective field study for sensor-based identification of fall risk in older people with dementia

Informatics for Health and Social Care

Volumn 39, Issue 3-4, 2014, Pages 249-261

  Gietzelt, Matthias ^a   Feldwieser, Florian ^b   Gövercin, Mehmet ^b   Steinhagen Thiessen, Elisabeth ^b   Marschollek, Michael ^a  

^a TECHNICAL UNIVERSITY OF BRAUNSCHWEIG   (Germany)

^b CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

Author keywords

Accelerometer; Dementia; Fall risk; Health enabling technologies

Indexed keywords

ACCELEROMETRY; AGED; DEMENTIA; FALLING; FEMALE; GAIT; GERIATRIC ASSESSMENT; HOME FOR THE AGED; HUMAN; LONGITUDINAL STUDY; MALE; NURSING HOME; PHYSIOLOGY; PREVENTION AND CONTROL; PROCEDURES; PROGNOSIS; PROSPECTIVE STUDY; RISK ASSESSMENT; VERY ELDERLY;

ACCELEROMETRY; ACCIDENTAL FALLS; AGED; AGED, 80 AND OVER; DEMENTIA; FEMALE; GAIT; GERIATRIC ASSESSMENT; HOMES FOR THE AGED; HUMANS; LONGITUDINAL STUDIES; MALE; NURSING HOMES; PROGNOSIS; PROSPECTIVE STUDIES; RISK ASSESSMENT;

EID: 84906558321     PISSN: 17538157     EISSN: 17538165     Source Type: Journal    
DOI: 10.3109/17538157.2014.931851     Document Type: Article

References (29)

1. von Renteln-Kruse W, Krause T, Dieckmann P, Vogel J. Geriatric patients' mobility status as reflected by the relevant items of the Barthel index and in-hospital falls. J Am Geriatr Soc 2006;54:1012-13.
2. Scanaill CN, Garattini C, Greene BR, McGrath MJ. Technology innovation enabling falls risk assessment in a community setting. Ageing Int 2011;36:217-31.
3. Podsiadlo D, Richardson S. The timed ''Up & Go'': A test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 1991;39:142-8.
4. Tinetti ME. Performance-oriented assessment of mobility problems in elderly patients. J Am Geriatr Soc 1986;34:119-26.
5. Duncan PW, Weiner DK, Chandler J, Studenski S. Functional reach: A new clinical measure of balance. J Gerontol 1990;45:M192-7.
6. Oliver D, Britton M, Seed P, et al. Development and evaluation of evidence based risk assessment tool (STRATIFY) to predict which elderly inpatients will fall: Casecontrol and cohort studies. BMJ 1997;315:1049-53.
7. Oliver D, Daly F, Martin FC, McMurdo ME. Risk factors and risk assessment tools for falls in hospital in-patients: A systematic review. Age Ageing 2004;33:122-30.
8. Myers H. Hospital fall risk assessment tools: A critique of the literature. Int J Nurs Pract 2003;9:223-35.
9. Merom D, Cumming R, Mathieu E, et al. Can social dancing prevent falls in older adults? A protocol of the Dance, Aging, Cognition, Economics (DAnCE) fall prevention randomised controlled trial. BMC Public Health 2013;13:477.
10. Giansanti D. Investigation of fall-risk using a wearable device with accelerometers and rate gyroscopes. Physiol Meas 2006;27:1081-90.
11. S ? krba Z, O'Mullane B, Greene BR, et al. Objective real-time assessment of walking and turning in elderly adults. Proceedings of the 31st Annual International Conference of the IEEE EMBS; 2009 Sep 2-6; Minneapolis, MN, USA; 2009:807-10.
12. Scanaill CN, Greene BR, Doheny EP, et al. Clinical gait assessment of older adults using open platform tools. Proceedings of the 33rd Annual International Conference of the IEEE EMBS; 2011 Aug 30-Sep 3; Boston, MA, USA; 2011:462-5.
13. Doheny EP, Greene BR, Foran T, et al. Diurnal variations in the outcomes of instrumented gait and quiet standing balance assessments and their association with falls history. Physiol Meas 2012;33:361-73.
14. Narayanan MR, Redmond SJ, Scalzi ME, et al. Longitudinal falls-risk estimation using triaxial accelerometry. IEEE Trans Biomed Eng 2010;57:534-41.
15. Senden R, Savelberg HH, Grimm B, et al. Accelerometry-based gait analysis, an additional objective approach to screen subjects at risk for falling. Gait Posture 2012;36:296-300.
16. Laessoe U, Hoeck HC, Simonsen O, et al. Fall risk in an active elderly population-can it be assessed? J Neg Results Biomed 2007;6:2. doi: 10.1186/1477-5751-6-2.
17. Marschollek M, Rehwald A, Wolf KH, et al. Sensor-based fall risk assessment-an expert ?to go'. Methods Inf Med 2011;50:420-6.
18. Marschollek M, Rehwald A, Wolf KH, et al. Sensors vs. experts-A performance comparison of sensor-based fall risk assessment vs. conventional assessment in a sample of geriatric patients. BMC Med Inform Decis Mak 2011;11:48.
19. Greene BR, Doheny EP, Walsh C, et al. Evaluation of falls risk in communitydwelling older adults using body-worn sensors. Gerontology 2012;58:472-80.
20. Folstein MF, Folstein SE, McHugh PR. ''Mini-mental state''. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12: 189-8.
21. Mahoney FI, Barthel DW. Functional evaluation: The Barthel index. Md State Med J 1965;14:61-5.
22. Haux R, Hein A, Eichelberg M, et al. The Lower Saxony research network design of environments for ageing: Towards interdisciplinary research on information and communication technologies in ageing societies. Inform Health Soc Care 2010;35: 92-103.
23. Gietzelt M, Wolf KH, Kohlmann M, et al. Measurement of accelerometry-based gait parameters in people with and without dementia in the field-A technical feasibility study. Methods Inf Med 2013;52:319-25.
24. Gietzelt M, Schnabel S, Wolf KH, et al. A method to align the coordinate system of accelerometers to the axes of a human body: The depitch algorithm. Comput Methods Programs Biomed 2012;106:97-103.
25. Quinlan JR. C4.5: Programs for machine learning. Revised ed. San Mateo (CA): Morgan Kaufmann Publishers; 1993.
26. Hall MA. Correlation-based feature selection for machine learning [dissertation]. Hamilton, New Zealand: University of Waikato; 1999.
27. Burns A, Greene BR, McGrath MJ, et al. SHIMMERTM-A wireless sensor platform for noninvasive biomedical research. IEEE Sensors J 2010;10:1527-34.
28. Hall M, Frank E, Holmes G, et al. The WEKA data mining software: An update. SIGKDD Explorations 2009;11:10-18.
29. Cohen J. A coefficient of agreement for nominal scales. Educ Psychol Meas 1960;20: 37-46.