Experimental Validation of Subject-Specific Dynamics Model for Predicting Impact Force in Sideways Fall

Sarvi, Masoud Nasiri; Luo, Yunhua; Sun, Ping; Ouyang, Jun

doi:10.4236/jbise.2014.77043

Cited by 19 publications

(24 citation statements)

References 19 publications

(24 reference statements)

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“…In this method, the correlation between the pixel intensity in the DXA image and the tissue mass density was used to determine the pixel mass [61] and subsequently the required parameters. The obtained parameters were then used to construct a three-link human-body dynamics model, developed by the authors and validated by experiments [59,62], in order to simulate a lateral fall from standing height. The three links represent respectively the shank, the thigh, and the trunk.…”

Section: Calculation Of Impact Force and Hip Fracture Riskmentioning

confidence: 99%

Study of sex differences in the association between hip fracture risk and body parameters by DXA-based biomechanical modeling

Nasiri

Luo

2016

Bone

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Section: Calculation Of Impact Force and Hip Fracture Riskmentioning

confidence: 99%

Study of sex differences in the association between hip fracture risk and body parameters by DXA-based biomechanical modeling

Nasiri

Luo

2016

Bone

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“…However, a larger body weight is also associated with a thicker soft tissue over the hip, which is able to attenuate the impact energy and thus reduce the impact force to some extent [161,162]. The resulting impact force is dependent on the dominance of the above two effects [8,113,114]. Body height is also associated with the initial potential energy.…”

Section: Weight and Heightmentioning

confidence: 94%

“…1 Load-strength ratio, major and sublevel biomechanical variables before touching the ground may change the magnitude of impact force [8,112,116]. A more accurate way is to determine the impact force by fall simulation using a dynamics model constructed from the subject's whole body medical image [8,111,113,114]. It should be realized that assumptions, for example, the fall type and direction, have been introduced in both fall tests and dynamics simulations, which may be very different from those in a real-world fall.…”

Section: Biomechanical Variables Determining Hip Fracture Riskmentioning

confidence: 99%

“…The effects have been studied by fall tests [14, 17, 107-109] and whole-body dynamics simulations [8,110,[112][113][114]. A greater body weight is associated with a larger initial potential energy if the fall is from standing height.…”

Section: Weight and Heightmentioning

confidence: 99%

“…For assessment purpose, the impact force can be estimated from fall test [14, 17, [106][107][108][109][110] or determined by fall dynamics simulation [8,[111][112][113][114]. Empirical formulas established from experimental data have been proposed to estimate the impact force using the subject's body weight and height [107,110,115].…”

Section: Biomechanical Variables Determining Hip Fracture Riskmentioning

confidence: 99%

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A biomechanical sorting of clinical risk factors affecting osteoporotic hip fracture

Luo

2015

Osteoporos Int

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Osteoporotic fracture has been found associated with many clinical risk factors, and the associations have been explored dominantly by evidence-based and case-control approaches. The major challenges emerging from the studies are the large number of the risk factors, the difficulty in quantification, the incomplete list, and the interdependence of the risk factors. A biomechanical sorting of the risk factors may shed lights on resolving the above issues. Based on the definition of load-strength ratio (LSR), we first identified the four biomechanical variables determining fracture risk, i.e., the risk of fall, impact force, bone quality, and bone geometry. Then, we explored the links between the FRAX clinical risk factors and the biomechanical variables by looking for evidences in the literature. To accurately assess fracture risk, none of the four biomechanical variables can be ignored and their values must be subject-specific. A clinical risk factor contributes to osteoporotic fracture by affecting one or more of the biomechanical variables. A biomechanical variable represents the integral effect from all the clinical risk factors linked to the variable. The clinical risk factors in FRAX mostly stand for bone quality. The other three biomechanical variables are not adequately represented by the clinical risk factors. From the biomechanical viewpoint, most clinical risk factors are interdependent to each other as they affect the same biomechanical variable(s). As biomechanical variables must be expressed in numbers before their use in calculating LSR, the numerical value of a biomechanical variable can be used as a gauge of the linked clinical risk factors to measure their integral effect on fracture risk, which may be more efficient than to study each individual risk factor.

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Explicit Finite Element Models Accurately Predict Subject-Specific and Velocity-Dependent Kinetics of Sideways Fall Impact

Fleps

Guy

Ferguson

et al. 2019

Journal of Bone and Mineral Research

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The majority of hip fractures in the elderly are the result of a fall from standing or from a lower height. Current injury models focus mostly on femur strength while neglecting subject-specific loading. This article presents an injury modeling strategy for hip fractures related to sideways falls that takes subject-specific impact loading into account. Finite element models (FEMs) of the human body were used to predict the experienced load and the femoral strength in a single model. We validated these models for their predicted peak force, effective pelvic stiffness, and fracture status against matching ex vivo sideways fall impacts (n = 11) with a trochanter velocity of 3.1 m/s. Furthermore, they were compared to sideways impacts of volunteers with lower impact velocities that were previously conducted by other groups. Good agreement was found between the ex vivo experiments and the FEMs with respect to peak force (root mean square error [RMSE] = 10.7%, R 2 = 0.85) and effective pelvic stiffness (R 2 = 0.92, RMSE = 12.9%). The FEMs were predictive of the fracture status for 10 out of 11 specimens. Compared to the volunteer experiments from low height, the FEMs overestimated the peak force by 25% for low BMI subjects and 8% for high BMI subjects. The effective pelvic stiffness values that were derived from the FEMs were comparable to those derived from impacts with volunteers. The force attenuation from the impact surface to the femur ranged between 27% and 54% and was highly dependent on soft tissue thickness (R 2 = 0.86). The energy balance in the FEMS showed that at the time of peak force 79% to 93% of the total energy is either kinetic or was transformed to soft tissue deformation. The presented FEMs allow for direct discrimination between fracture and nonfracture outcome for sideways falls and bridge the gap between impact testing with volunteers and impact conditions representative of real life falls. Specimens: n = 11 (6 female, 5 male). BMI = body mass index (subject weight divided by the subject height squared); T ST,GT = thickness of soft tissue over the greater trochanter; aBMD total hip = areal bone mineral density of the proximal femur.

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Experimental Validation of Subject-Specific Dynamics Model for Predicting Impact Force in Sideways Fall

Cited by 19 publications

References 19 publications

Study of sex differences in the association between hip fracture risk and body parameters by DXA-based biomechanical modeling

Study of sex differences in the association between hip fracture risk and body parameters by DXA-based biomechanical modeling

A biomechanical sorting of clinical risk factors affecting osteoporotic hip fracture

Explicit Finite Element Models Accurately Predict Subject-Specific and Velocity-Dependent Kinetics of Sideways Fall Impact

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