![](bg5.png)
limited capacity in rehabilitation programs may cre-
ate need for appropriate planning and/or scheduling.
To this purpose in this paper we proposed an al-
gorithm which can potentially be used to determine
whether or not hydrotherapy is required. This ques-
tion may be of significant resources in scenarios in
which the number of geriatric physiatrists as well as
access to resources and/or their cost may be a limiting
factor. Furthermore we proposed a framework that
can potentially be useful for evaluating performance
of fellows and/or residents and assist them in their
training and educations as well as professional de-
velopment as it can point to potential mistakes. This
could be further used in order to evaluate the cause of
such mistakes and potential was to remedy them.
As a preliminary approach we proposed
computer-aided decision making using linear
and nonlinear models in which parameters were
chosen based on the correlation coefficient. An effort
should be made to compare the performance of these
models to non-parametric, multilevel histograms
in which FIM and BBS can be modelled using the
joint probability density function and consequently
determining a histogram based maximum likelihood
estimate. In addition the residual vector may not
be Gaussian distributed especially in which case
an effort should be made to investigate different
estimation techniques that may be more suitable for
non-Gaussian models.
Finally, a clinical study with a larger number of
patients and different waiting times should be per-
formed in order to evaluate the correlation between
waiting time (time from operation to admission to re-
habilitation program). In this particular data set, due
the similarity between waiting times, this parameter
was not a significant factor. However that may not
be the case if the waiting times are larger than certain
threshold value which should be investigated in future
work.
REFERENCES
Adunsky, A., Arad, M., Koren-Morag, N., Fleissig, Y., and
Mizrahi, E. (2012). Atrial fibrillation is not associ-
ated with rehabilitation outcomes of elderly hip frac-
ture patients. Geriatr Gerontol Int., 10:1320–1325.
Dodds, T., Martin, D., Stolov, W., and R, D. (1993). A val-
idation of the functional independence measurement
and its performance among rehabilitation inpatients.
Arch Phys Med Rehabil, 74:531–536.
Firat, S., Bousamra, M., Gore, E., and RW, B. (2002). Co-
morbidity and kps are independent prognostic factors
in stage i non-small-cell lung cancer. Int J Radiat On-
col Biol Phys, 52:1047–1054.
Jeremic, A., Radosavljevic, N., Nikolic, D., and Lazovic,
M. (2012). Analysis of berg balance scale in hip frac-
ture patients using fuzzy clustering. Proc BIOSIG-
NALS 2012, pages 466–470.
Jeremic, A., Radosavljevic, N., Nikolic, D., and Lazovic,
M. (2013). Blind adaptive decision fusion for dis-
tributed detection. Proc IEEE EMBC, pages 6421–
6424.
Johnell, O. and Kanis, J. (2004). An estimate of the world-
wide prevalence, mortality and disability associated
with hip fracture. Osteoporosis, 15(5):897–902.
Li, H. and Jeremic, A. (2011). Neonatal seizure detection
using blind multichannel information fusion. Proc
IEEE ICASSP, pages 649–652.
Liu, B., Jeremic, A., and Wong, K. (2011). Optimal dis-
tributed detection of multiple hypothesis using blind
algorithm. IEEE Transactions on Aerospace and Elec-
tronic Systems, pages 317–331.
Mirjalily, P., Luo, T., and Davidson, T. (2003). Blind adap-
tive decision fusion for distributed detection. IEEE
Transactions on Aerospace and Electronic Systems,
39:34–52.
of the long-term disability associated with hip fractures., R.
(2011). Bertram, m and norman, r and kemp, l and
vos, t. Inj Prev, 7:365–370.
Roche, J., Wenn, R., Sahota, O., and Moran, C. (2005).
Effect of comorbidities and postoperative complica-
tions on mortality after hip fracture in elderly peo-
ple: prospective observational cohort study. BMJ,
331:1374.
Roudsari, B., Ebel, B., Corso, P., Molinari, N., and
Koepsell, T. (2005). The acute medical care costs of
fall-related injuries among u.s. older adults. Injury,
36(1):1316–132.
Sipila, S., Salpakoski, A., Edgren, J., Heinonen, A., Kaup-
pinen, M., and M, A.-K. (2011). Promoting mobility
after hip fracture (promo): study protocol and selected
baseline results of a year-long randomized controlled
trial among community-dwelling older people. BMC
Musculoskelet Disord, 27:277.
Young, Y., Fan, M., Hebel, J., and Boult, C. (2009). Con-
current validity of administering the functional inde-
pendence measure (fim) instrument by interview. Am
J Phys Med Rehabil, 88:766–770.
OptimalTreatmentSelectionforHipFracturePatientsusingaHybridDecisionMakingSystem
305