Sharif Digital Repository

Spinal fusion surgery is usually followed by accelerated degenerative changes in the unfused segments above and below the treated segment(s), i.e., adjacent segment disease (ASD). While a number of risk factors for ASD have been suggested, its exact pathogenesis remains to be identified. Finite element (FE) models are indispensable tools to investigate mechanical effects of fusion surgeries on post-fusion changes in the adjacent segment kinematics and kinetics. Existing modeling studies validate only their intact FE model against in vitro data and subsequently simulate post-fusion in vivo conditions. The present study provides a novel approach for the comprehensive validation of a lumbar... 

Purpose: Although it has been proposed that individuals with patellofemoral pain show less lower limb intersegmental coordination variability, the evidence to support this hypothesis is rare. The purpose of this study was, therefore, to evaluate whether individuals with patellofemoral pain exhibit less intersegmental coordination variability compared with healthy individuals during walking and running. Also, it was hypothesized that increasing task demand would exacerbate group differences regarding coordination variability measures. Methods: Three-dimensional kinematics were collected while 17 females with patellofemoral pain and 17 healthy females walked at preferred speed, and ran at... 

Passive finite element (FE) models of the spine are commonly used to simulate intact and various pre- and postoperative pathological conditions. Being devoid of muscles, these traditional models are driven by simplistic loading scenarios, e.g., a constant moment and compressive follower load (FL) that do not properly mimic the complex in vivo loading condition under muscle exertions. We aim to develop novel passive FE models that are driven by more realistic yet simple loading scenarios, i.e., in vivo vertebral rotations and pathological-condition dependent FLs (estimated based on detailed musculoskeletal finite element (MS-FE) models). In these novel force–displacement control FE models,... 

Body posture measurement approaches, required in biomechanical models to assess risk of musculoskeletal injuries, are usually costly and/or impractical for use in real workplaces. Therefore, we recently developed three artificial neural networks (ANNs), based on measured posture data on several individuals, to predict whole body 3D posture (coordinates of 15 markers located on body's main joints), segmental orientations (Euler angles of 14 body segments), and lumbosacral (L5-S1) moments during static manual material handling (MMH) activities (ANNPosture, ANNAngle, and ANNMoment, respectively). These ANNs require worker's body height, body weight (only for ANNMoment), hand-load 3D position,... 

We propose a new image recovery method to improve the resolution in microwave imaging applications. Scattered field data obtained from a simplified breast model with closely located targets is used to formulate an electromagnetic inverse scattering problem, which is then solved using the Distorted Born Iterative Method (DBIM). At each iteration of the DBIM method, an underdetermined set of linear equations is solved using our proposed sparse recovery algorithm, IMATCS. Our results demonstrate the ability of the proposed method to recover small targets in cases where traditional DBIM approaches fail. Furthermore, in order to regularize the sparse recovery algorithm, we propose a novel... 

Different lifting analysis tools are commonly used to assess spinal loads and risk of injury. Distinct musculoskeletal models with various degrees of accuracy are employed in these tools affecting thus their relative accuracy in practical applications. The present study aims to compare predictions of six tools (HCBCF, LSBM, 3DSSPP, AnyBody, simple polynomial, and regression models) for the L4-L5 and L5-S1 compression and shear loads in twenty-six static activities with and without hand load. Significantly different spinal loads but relatively similar patterns for the compression (R2>0.87) were computed. Regression models and AnyBody predicted intradiscal pressures in closer agreement with... 

The objective of this study was to quantify individual muscle function differences between level walking and backpack load carriage at the same speed by using a muscle-actuated forward dynamics simulation. As experimental investigations have revealed that backpack loads of up to 64 per cent of an individual's body mass have little effect on the sagittal plane gait kinema-tics, further biomechanical analyses are necessary to investigate the contributions of individual muscle coordination strategies to achieve a given motor task by mechanical power generation, absorption, and transference to each body segment. A biomechanical framework consisting of a musculoskeletal model actuated by 18... 

Purpose: An abdominal aortic aneurysm (AAA) is known as a cardiovascular disease involving localized deformation (swelling or enlargement) of aorta occurring between the renal and iliac arteries. AAA would jeopardize patients’ lives due to its rupturing risk, so prompt recognition and diagnosis of this disorder is vital. Although computed tomography angiography (CTA) is the preferred imaging modality used by radiologist for diagnosing AAA, computed tomography (CT) images can be used too. In the recent decade, there has been several methods suggested by experts in order to find a precise automated way to diagnose AAA without human intervention base on CT and CTA images. Despite great... 

Objective: A novel electrocardiogram (ECG) classification algorithm is proposed for continuous cardiac monitoring on wearable devices with limited processing capacity. Methods: The proposed solution employs a novel architecture consisting of wavelet transform and multiple long short-term memory (LSTM) recurrent neural networks (see Fig. 1). Results: Experimental evaluations show superior ECG classification performance compared to previous works. Measurements on different hardware platforms show the proposed algorithm meets timing requirements for continuous and real-time execution on wearable devices. Conclusion: In contrast to many compute-intensive deep-learning based approaches, the... 

The relative vulnerability of spinal motion segments to different loading combinations remains unknown. The meta-analysis described here using the results of a validated L2-L3 nonlinear viscoelastic finite element model was designed to investigate the critical loading and its effect on the internal mechanics of the human lumbar spine. A Box-Behnken experimental design was used to design the magnitude of seven independent variables associated with loads, rotations and velocity of motion. Subsequently, an optimization method was used to find the primary and secondary variables that influence spine mechanical output related to facet forces, disc pressure, ligament forces, annulus matrix... 

Background: Longitudinal data on the association of quantitative thigh muscle MRI markers with knee osteoarthritis (KOA) outcomes are scarce. These associations are of clinical importance, with potential use for thigh muscle–directed disease-modifying interventions. Purpose: To measure KOA-associated longitudinal changes in MRI-derived muscle cross-sectional area (CSA) and adipose tissue and their association with downstream symptom worsening and knee replacement (KR). Materials and Methods: In a secondary analysis of the Osteoarthritis Initiative multicenter prospective cohort (February 2004 through October 2015), knees of participants with available good-quality thigh MRI scans at baseline...