Published at : 19 Oct 2022
Volume : IJtech
Vol 13, No 5 (2022)
DOI : https://doi.org/10.14716/ijtech.v13i5.5824
Lau, L.W., Kok, C.K., Chen, G.M., Tso, C.-P., 2022. Modelling Human-Structure Interaction in Sideways Fall for Hip Impact Force Estimation. International Journal of Technology. Volume 13(5), pp. 1149-1158
Lin Wei Lau | Pixel Automation Pte Ltd, 10 Admiralty Street #04-13 North Link Building Singapore, Singapore 757695 |
Chee Kuang Kok | Center for Advanced Mechanical and Green Technology, Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450 Bukit Beruang, Melaka, Malaysia |
Gooi Mee Chen | Center for Advanced Mechanical and Green Technology, Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450 Bukit Beruang, Melaka, Malaysia |
Chih-Ping Tso | Center for Advanced Mechanical and Green Technology, Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450 Bukit Beruang, Melaka, Malaysia |
Sideways fall-induced hip fracture is a primary
global health concern among the elderly. Existing impact models for predicting
peak hip impact force mostly consider the human body-related parameters rather
than impact surface parameters. This study proposed improving existing
spring-mass-damper models by accounting for the human-structure dynamic
interaction during sideways fall for better predicting peak impact force on the
hip. Information required to construct the models was extracted from the
literature. Different peak hip impact forces were estimated by considering
differences in gender, body height, body mass, stiffness, damping
coefficients of body tissue over the greater trochanter, and the impact surface
stiffness. The predicted peak hip impact forces were compared to measured or
simulated results in the literature and found to agree reasonably. Simulation
results show that interactions with impact surfaces with lower stiffness can
reduce the value of peak impact force applied on the hip by at least 16%.
Flooring material; Hip fracture; Impact force attenuation; Spring-mass-damper; Trochanteric tissue stiffness
Sideway fall often results in osteoporotic hip
fracture, which is a major health care issue over the world that leads to
immobility or even death (Nor-Izmin et
al., 2020). According
to statistics (Burns
& Kakara, 2018), 55% of unintentional injuries among Americans over
the age of 65 were caused by falls. Major clinical risk assessment tools
available today includinge
bone densitometry based on hip Dual-energy X-ray absorptiometry (DXA), hip
structural analysis (HSA), and fracture risk assessment tool (FRAX) (Sarvi & Luo, 2015) could provide hip fracture risk assessment due to
sideways fall with reasonable accuracy
Biomechanics models (Kroonenberg
et al., 1995) have shown that effective
mass can vary from 25% to 75% of the overall
mass depending on different kinematic configurations right before the fall
impact. Sarvi and Luo
Previous research
2.1. Model Development
Sarvi and
Luo’s framework (2015) was adopted in
developing our peak hip force model. The authors' model is made up of two
sub-models that work sequentially. First, a dynamic sub-model determines the
effective mass and the impact velocity of the fallen body. Second, an impact
sub-model predicts the peak hip force based on two spring-mass-damper stacked
in series. For the dynamic sub-model, a two-link model with a 45-degree
inclined torso (a.k.a. jack-knife) (Kroonenberg et
al., 1995) was used for simulating sideways fall from a standing position,
and a point mass dynamic model for simulating very short-distance sideways hip
release experiment (Laing et al., 2006).
Therefore, the impact velocity, v (m/s), and effective mass, meff
(kg), reduce to:
|
where h is the height (in unit m) of the
falling person, and H is the effective mass drop height. The selection
of the two-link model was based on the fact that this model exhibited the
lowest error (i.e., 22% to 36%) among the non-subject specific models
The stiffness and damping coefficients of the
trochanteric tissue are key parameters in the impact sub-model. Recent findings
on these coefficients will first be presented first, followed by
the justification of the current model. There are contradicting views on how
age and soft tissue thickness (STT) affect trochanteric tissue stiffness and
damping coefficients. Sarvi and Luo
It is also very likely that the stiffness of the tissue
is nonlinear (Choi et al.,
2015; Laing & Robinovitch, 2010; Makhsous et al., 2008). For an individual with average weight, it could be
induced from Makhsous et
al.’s
To model the effect of the impact surface, two
spring-mass-dampers are stacked to form a two-degree-of-freedom vibration
system, as illustrated in Figure 1. In this figure, M is the mass, K
is the spring stiffness, and C is the damping coefficient. The subscripts
h and f represent the falling human and the impacted floor,
respectively
|
This model is very similar to
Shahabpoor and Pavic’s
The variables M, K, C, and P
in Equations (8) to (10) are to be substituted with corresponding mass, spring
stiffness, damping coefficients, and residual force of the human or the floor,
according to Equations (6) and (7), respectively.
The initial stiffness (K1) damping
coefficients and estimated thickness of human tissues (STT) over the greater
trochanter used in this study were as reported in (Nasiri & Luo, 2016). Table 1 shows the mean stiffness data reduced to
simple regressions with correlation coefficients greater than 0.94. Damping
coefficients were treated as categorical data corresponding to BMI and gender
categories (Nasiri &
Luo, 2016). Furthermore,
the trochanteric tissue stiffness was represented by a trilinear nested-spring
design in Fig 2, and K1 is the tissue stiffness according to
Equations (12b) and (13b). It should be noted that the stiffness and damping
coefficients of the greater trochanter tissue reported in (Nasiri & Luo, 2016) were originally obtained by Robinovitch et al.
Table
1 Simple
regressions between BMI, STT, and mean stiffness
Gender |
Variable |
Expression |
|
Male |
STT
(mm) |
STT
= 3.8429*BMI - 45.254 |
(12a) |
|
K
(kN/m) |
K
= 395.6*(BMI)-0.755 |
(12b) |
Female |
STT
(mm) |
STT
= 2.4991*BMI - 14.189 |
(13a) |
|
K
(kN/m) |
K
= 1935.6*(BMI)-1.4 |
(13b) |
The effective stiffness and effective damping
coefficient of an impact surface used in the current study were taken from Ref.
(Laing et al., 2006). Table 2 depicts the range of effective stiffness of
compliant flooring as reported by Laing et al.
Figure 2 (a) Trilinear approximation (i.e., three red lines to approximate the blue curve); (b) Nested spring representation of trilinear tissue stiffness.
Table 2 Effective stiffness of compliant flooring (Laing et al., 2006)
Floor Type |
Floor Thickness (cm) |
Flooring Stiffness, k (kN/m) |
Rigid |
NIL |
~? |
Firm |
1.5 |
263 |
Semifirm |
4.5 |
95 |
Semisoft |
7.5 |
67 |
Soft |
10.5 |
59 |
3.1. Fall on Rigid Flooring
The predictions of impact forces using the proposed
model will be verified using four different cases of sideways fall or
small-distance hip release on rigid flooring from the literature. The input
parameters and predicted impact force are summarized in Table 3. Case 1 is a
simulated sideways fall from standing height on a rigid impact surface on
non-subject-specific individuals. Case 2, a protected fall experiment by Sarvi et. al
In estimating peak impact force due to a sideways fall
from standing height in Case 1, the interaction between a human body with a
rigid flooring was simulated. The mean values of human body parameters (as in
Table 4) were taken from the Centrers
for Disease Control and Prevention
Figure 3 Predicted
peak impact force for (a) male and (b) female with mean heights and mass
Table
3 Input
parameters and predicted impact force for four different cases on rigid
flooring
|
Input |
Output: Hip Peak Impact force (N) |
||||||
Case/ Input |
Gender |
Height (m) |
Weight (kg) |
Impact Velocity (m/s) |
Effective Mass (kg) |
Experiment |
Model |
Percent Error
|
Case 1 |
Male |
1.757 |
88.8 |
Eq (1a) |
Eq (2a) |
From 4050 to 6420 |
4777 |
Within Range |
Female |
1.616 |
76.4 |
Eq (1a) |
Eq (2a) |
3245 |
19.9% |
||
Case 2 (Sarvi, et al., 2014) |
Male |
1.73 |
77 |
1.063 |
35.56 |
1900.8 |
1722 |
9.4% |
Male |
1.72 |
72 |
1.236 |
29.75 |
1714.4 |
1905 |
11.1% |
|
Male |
1.74 |
64 |
2.493 |
24.62 |
2961.8 |
3406 |
15.0% |
|
Case 3 |
Female |
1.70 |
59.6 |
Eq (1b) |
Eq (2b) |
1059±42 |
1273 |
16% |
Case 4 (Fleps, et al., 2019) |
Female |
1.63 |
40.8 |
3.1 |
Eq (2b) |
2910 |
5145 |
76.8% |
Female |
1.78 |
49.0 |
3.1 |
Eq (2b) |
6131 |
5627 |
8.2% |
|
Female |
1.65 |
59.0 |
3.1 |
Eq (2b) |
5641 |
4797 |
15.0% |
|
Female |
1.68 |
61.3 |
3.1 |
Eq (2b) |
4907 |
4869 |
0.8% |
|
Female |
1.63 |
84.0 |
3.1 |
Eq (2b) |
4958 |
4305 |
13.2% |
|
Female |
1.58 |
99.8 |
3.1 |
Eq (2b) |
4910 |
3950 |
19.6% |
|
Male |
1.75 |
45.4 |
3.1 |
Eq (2a) |
5242 |
5840 |
11.4% |
|
Male |
1.83 |
63.5 |
3.1 |
Eq (2a) |
5043 |
6193 |
22.8% |
|
Male |
1.75 |
68.1 |
3.1 |
Eq (2a) |
7601 |
6105 |
19.7% |
Using the current impact model in Case 2, experimental
peak hip impact forces and the predictions agree with experiments to within 15%
of error, although the drop configurations and subsequent kinematics were
subject-specific in the experiment. Unlike the work of Laing and Robinovitch
Similarly, when benchmarked against Fleps et al.
3.2. Fall on Non-rigid Flooring
Laing et al.
Table 4 Hip impact force attenuation
Floor Type |
% attenuation |
% attenuation (Current study) |
Firm |
6-10 |
16 |
Semi-firm |
14-16 |
23 |
Semisoft |
15-18 |
25 |
Soft |
16-19 |
27 |
Although the current model slightly overpredicted the
percent attenuation in the simulated fall experiments by an extra 6-8%, the
trend of decreasing gain in the attenuation rate from semi-firm to soft
flooring material matches the observation in Ref. (Laing et al., 2006) well. The 6-8% extra attenuation could be taken as
the percent error of the model, and the error may have come from the
uncertainty related to the prediction of trochanteric tissue stiffness based on
BMI and gender.
The authors demonstrated that factors such as body
height, body weight (and thence BMI), gender of the individuals, and impact
velocity alone appear sufficient in a non-subject-specific model for estimating
the peak hip impact force. In contrast, age and actual trochanteric tissue
thickness may be less significant. Except for one scenario, the proposed model
could predict the mean peak hip impact force of a sideways fall from standing
height with 77% accuracy. The amount of attenuation indicated in the hip impact
force (i.e., 16%-27%) due to compliant flooring also agrees with previous work
(i.e., 6%-19%). Regressions were made
on the trochanteric tissue stiffness in published literature. The predictions were
made using a tri-linear spring-mass-damper stacked model, and no individual
measurements of trochanteric tissue stiffness and damping coefficients were
required. To be sure, the inclusion of a third spring in the trilinear spring
model is not entirely justified. More testing may be required to validate its
use.
This
research work has not received any grant from any funding agency. The authors
are grateful to Multimedia University for granting them access to a MATLAB
license to produce this work.
Filename | Description |
---|---|
R1-ME-5824-20220811114120.JPG | Revised Figure 1 |
R1-ME-5824-20220811114143.JPG | Revised Figure 2 |
R1-ME-5824-20220811114201.JPG | Revised Figure 3 |
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