Abstract
Fall prevention is an important and complex
multifactorial challenge, since one third of people over
65 years old fall at least once every year. A novel
application of Disease State Fingerprint (DSF) algorithm
is presented for holistic visualization of fall risk
factors and identifying persons with falls history or
decreased level of physical functioning based on fall
risk assessment data. The algorithm is tested with data
from 42 older adults, that went through a comprehensive
fall risk assessment. Within the study population the
Activities-specific Balance Confidence (ABC) scale score,
Berg Balance Scale (BBS) score and the number of drugs in
use were the three most relevant variables, that differed
between the fallers and non-fallers. This study showed
that the DSF visualization is beneficial in inspection of
an individual's significant fall risk factors, since
people have problems in different areas and one single
assessment scale is not enough to expose all the people
at risk.
Original language | English |
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Title of host publication | 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
Publisher | IEEE Institute of Electrical and Electronic Engineers |
Pages | 3176-3179 |
ISBN (Electronic) | 978-1-4244-7929-0 |
DOIs | |
Publication status | Published - 2014 |
MoE publication type | A4 Article in a conference publication |
Event | 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States Duration: 26 Aug 2014 → 30 Aug 2014 Conference number: 36 |
Publication series
Series | Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
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Volume | 36 |
ISSN | 1094-687X |
Conference
Conference | 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 |
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Abbreviated title | EMBC 2014 |
Country/Territory | United States |
City | Chicago |
Period | 26/08/14 → 30/08/14 |
Keywords
- aging
- diseases
- fingerprint recognition
- muscles
- risk management
- sociology
- statistics