Design and Analysis of The Energy Storage and Return (ESAR) Foot Prosthesis Using Finite Element Method

ABSTRACT. Disability issue has increased in recent years due to the high number of accidents and vascular disease. Loss of limb function for people with amputations often results in an abnormal gait. Energy Storage And Return (ESAR) foot prostheses provide an alternative to help improve gait and minimize metabolic energy expenditure during the walking phase of amputees. This study used 3 designs with models from the Catia V5 Software. The finite element method analysis used Ansys Workbench 18.1 software to evaluate the three designs with a loading of 1.2 times the user's body weight with a maximum weight of 70 kg in normal walking activities. The simulated material is carbon fiber prepreg which has tensile strength, Young's modulus, Poisson ratio, and density of 513.72 MPa, 77.71 GPa, 0.14, and 1.37 g/cm3. The decision-making matrix method is used to determine the best foot prosthesis design according to predetermined criteria. The highest value in the decision-making matrix is 76 in Design 3. The chosen design (Design 3) after gait cycle analysis has a maximum von Mises stress value of 76.956 MPa and the safety factor value for each gait cycle heel strike loading model is 1.0762; foot flat 3.2509; toe-off 6.6263.

Investigating the Effect of Real-Time Center of Pressure (CoP) Feedback Training on the Swing Phase of Lower Limb Kinematics in Transfemoral Prostheses with SACH foot

Transfemoral amputee often encounters reduced toe clearance resulting in trip-related falls. Swing phase joint angles have been shown to influence the toe clearance therefore, training intervention that targets shaping the swing phase joint angles can potentially enhance toe clearance. The focus of this study was to investigate the effect of the shift in the location of the center of pressure (CoP) during heel strike on modulation of the swing phase joint angles in able-bodied participants (n=6) and transfemoral amputees (n=3). We first developed a real-time CoP-based visual feedback system such that participants could shift the CoP during treadmill walking. Next, the kinematic data were collected during two different walking sessions- baseline (without feedback) and feedback (shifting the CoP anteriorly/posteriorly at heel strike to match the target CoP location). Primary swing phase joint angle adaptations were observed with feedback such that during the mid-swing phase, posterior CoP shift feedback significantly increases (p<0.05) the average hip and knee flexion angle by 11.55 degrees and 11.86 degrees respectively in amputees, whereas a significant increase (p<0.05) in ankle dorsiflexion, hip and knee flexion angle by 3.60 degrees, 3.22 degrees, and 1.27 degrees respectively compared to baseline was observed in able-bodied participants. Moreover, an opposite kinematic adaptation was seen during anterior CoP shift feedback. Overall, results confirm a direct correlation between the CoP shift and the modulation in the swing phase lower limb joint angles.

Gait Adaptation to a Phase-Specific Nociceptive Electrical Stimulation Applied at the Ankle: A Model to Study Musculoskeletal-Like Pain

Introduction: Lower limb pain, whether induced experimentally or as a result of a musculoskeletal injury, can impair motor control, leading to gait adaptations such as increased muscle stiffness or modified load distribution around joints. These adaptations may initially reduce pain but can also lead to longer-term maladaptive plasticity and to the development of chronic pain. In humans, many current experimental musculoskeletal-like pain models are invasive, and most don’t accurately reproduce the movement-related characteristics of musculoskeletal pain. The main objective of this study was to measure pain adaptation strategies during gait of a musculoskeletal-like experimental pain protocol induced by phase-specific, non-invasive electrical stimulation.Methods: Sixteen healthy participants walked on a treadmill at 4 km/h for three consecutive periods (BASELINE, PAIN, and POST-PAIN). Painful electrical stimulations were delivered at heel strike for the duration of heel contact (HC) using electrodes placed around the right lateral malleolus to mimic ankle sprains. Gait adaptations were quantified bilaterally using instrumented pressure-sensitive insoles. One-way ANOVAs and group time course analyses were performed to characterize the impact of electrical stimulation on heel and forefoot contact pressure and contact duration.Results: During the first few painful strides, peak HC pressure decreased on the painful side (8.6 ± 1.0%, p < 0.0001) and increased on the non-stimulated side (11.9 ± 0.9%, p < 0.0001) while HC duration was significantly reduced bilaterally (painful: 12.1 ± 0.9%, p < 0.0001; non-stimulated: 4.8 ± 0.8%, p < 0.0001). No clinically meaningful modifications were observed for the forefoot. One minute after the onset of painful stimulation, perceived pain levels stabilized and peak HC pressure remained significantly decreased on the painful side, while the other gait adaptations returned to pre-stimulation values.Discussion: These results demonstrate that a non-invasive, phase-specific pain can produce a stable painful gait pattern. Therefore, this protocol will be useful to study musculoskeletal pain locomotor adaptation strategies under controlled conditions.

Validation of a Sensor-Based Gait Analysis System with a Gold-Standard Motion Capture System in Patients with Parkinson’s Disease

Digital technologies provide the opportunity to analyze gait patterns in patients with Parkinson’s Disease using wearable sensors in clinical settings and a home environment. Confirming the technical validity of inertial sensors with a 3D motion capture system is a necessary step for the clinical application of sensor-based gait analysis. Therefore, the objective of this study was to compare gait parameters measured by a mobile sensor-based gait analysis system and a motion capture system as the gold standard. Gait parameters of 37 patients were compared between both systems after performing a standardized 5 × 10 m walking test by reliability analysis using intra-class correlation and Bland–Altman plots. Additionally, gait parameters of an age-matched healthy control group (n = 14) were compared to the Parkinson cohort. Gait parameters representing bradykinesia and short steps showed excellent reliability (ICC > 0.96). Shuffling gait parameters reached ICC > 0.82. In a stridewise synchronization, no differences were observed for gait speed, stride length, stride time, relative stance and swing time (p > 0.05). In contrast, heel strike, toe off and toe clearance significantly differed between both systems (p < 0.01). Both gait analysis systems distinguish Parkinson patients from controls. Our results indicate that wearable sensors generate valid gait parameters compared to the motion capture system and can consequently be used for clinically relevant gait recordings in flexible environments.

Human Gait-labeling Uncertainty and a Hybrid Model for Gait Segmentation

<div><div><div><p>Motion capture systems are widely accepted as ground-truth for gait analysis and are used for the validation of other gait analysis systems.To date, their reliability and limitations in manual labeling of gait events have not been studied.</p><p><b>Objectives</b>: Evaluate human manual labeling uncertainty and introduce a new hybrid gait analysis model for long-term monitoring.</p><p><b>Methods</b>: Evaluate and estimate inter-labeler inconsistencies by computing the limits-of-agreement; develop a model based on dynamic time warping and convolutional neural network to identify a valid stride and eliminate non-stride data in walking inertial data collected by a wearable device; Gait events are detected within a valid stride region afterwards; This method makes the subsequent data computation more efficient and robust.</p><p><b>Results</b>: The limits of inter-labeler agreement for key</p><p>gait events of heel off, toe off, heel strike, and flat foot are 72 ms, 16 ms, 22 ms, and 80 ms, respectively; The hybrid model's classification accuracy for a stride and a non-stride are 95.16% and 84.48%, respectively; The mean absolute error for detected heel off, toe off, heel strike, and flat foot are 24 ms, 5 ms, 9 ms, and 13 ms, respectively.</p><p><b>Conclusions</b>: The results show the inherent label uncertainty and the limits of human gait labeling of motion capture data; The proposed hybrid-model's performance is comparable to that of human labelers and it is a valid model to reliably detect strides in human gait data.</p><p><b>Significance</b>: This work establishes the foundation for fully automated human gait analysis systems with performances comparable to human-labelers.</p></div></div></div>

Human Gait-labeling Uncertainty and a Hybrid Model for Gait Segmentation

<div><div><div><p>Motion capture systems are widely accepted as ground-truth for gait analysis and are used for the validation of other gait analysis systems.To date, their reliability and limitations in manual labeling of gait events have not been studied.</p><p><b>Objectives</b>: Evaluate human manual labeling uncertainty and introduce a new hybrid gait analysis model for long-term monitoring.</p><p><b>Methods</b>: Evaluate and estimate inter-labeler inconsistencies by computing the limits-of-agreement; develop a model based on dynamic time warping and convolutional neural network to identify a valid stride and eliminate non-stride data in walking inertial data collected by a wearable device; Gait events are detected within a valid stride region afterwards; This method makes the subsequent data computation more efficient and robust.</p><p><b>Results</b>: The limits of inter-labeler agreement for key</p><p>gait events of heel off, toe off, heel strike, and flat foot are 72 ms, 16 ms, 22 ms, and 80 ms, respectively; The hybrid model's classification accuracy for a stride and a non-stride are 95.16% and 84.48%, respectively; The mean absolute error for detected heel off, toe off, heel strike, and flat foot are 24 ms, 5 ms, 9 ms, and 13 ms, respectively.</p><p><b>Conclusions</b>: The results show the inherent label uncertainty and the limits of human gait labeling of motion capture data; The proposed hybrid-model's performance is comparable to that of human labelers and it is a valid model to reliably detect strides in human gait data.</p><p><b>Significance</b>: This work establishes the foundation for fully automated human gait analysis systems with performances comparable to human-labelers.</p></div></div></div>

In Silico of Different Gait Cycle in Customised Leg Orthosis: A Finite Element Approach

Leg orthosis is one of medical device for fracture bone treatment. Several complications have been reported when patients are wearing the conventional Plaster of Paris or fibreglass leg orthosis. Its including numbness due to tight application, swelling, venous congestion and skin irritation. Therefore, the aim of this study is to develop and biomechanical analyse a customized leg cast that could tackle those complications. First, the leg was scanned using a 3D scanner. The leg cast was constructed from a 3D scanned leg model and designed using 3-Matic software which later simulated in finite element analysis using Marc software. The study focuses on three gait cycles; midstance, heel strike and toe off where stress and deformation were predicted. From the results, the cast only supported the ankle in midstance phase with only 7.297MPa stress and not capable to support the ankle in heel strike and toe off phases with maximum stress of 106.99 MPa and 213.12 MPa, respectively, which are beyond its yield strength of ABS, 23MPa. The average of overall displacement occurred for both skin and cast were less than 1.5mm. In short, the cast could only support the ankle in midstance phase and cannot be used for heel strike.

In vivo analysis of hip joint loading on Nordic walking novices

Objective To evaluate the influence of Nordic walking (NW) on hip joint loads in order to determine whether it can be safely performed during postoperative physiotherapy in patients after orthopeadic surgery of the hip. Methods Internal hip joint loads were directly measured in vivo in 6 patients using instrumented hip prostheses during NW and ordinary walking (OW). All patients received training in two different NW techniques (double-poling and the diagonal technique) by a certified NW instructor. Measurements were conducted on a treadmill at a speed of 4 km/h on level ground, at 10% inclination and at 10% slope as well as on a level lawn at a self chosen comfortable speed. Resultant contact force (Fres), bending moment (Mbend) and torsional torque (Mtors) were compared between NW and OW as well as between both NW techniques. Results Joint loads showed a double peak pattern during all setups. Neither NW technique significantly influenced hip joint loads at the time of the first load peak during contralateral toe-off (CTO), which was also the absolute load peak, in comparison to OW. Compared to OW, double-poling significantly reduced Fres and Mbend at the time of the second load peak during the contralateral heel strike (CHS) on level ground both on the treadmill (− 6% and − 7%, respectively) and on the lawn (− 7% and − 9%). At 10% inclination, the diagonal technique increased Fres and Mbend at CHS (by + 6% and + 7%), but did not increase the absolute load peak at CTO. Conclusion Joint loads during NW are comparable to those of OW. Therefore, NW can be considered a low-impact activity and seems to be safe for patients that are allowed full weight bearing, e.g. during postoperative rehabilitation after THA.

Influence of Carrying Unstable Load on Thoracic Kinematics While Walking on a Curved Path

This study investigated the effect of carrying unstable load on thoracic kinematics while walking on a curved path. Three-dimensional spinal kinematics were defined as the rotations between thoracic and the Virtual laboratory coordinate system (Tho/Virtual lab) which consisted of lateral bending (LB), flexion/extension (FE) and axial rotation (AR) in the frontal plane, sagittal plane and transverse plane, respectively. Eight healthy young adults (4 males and 4 females) performed loads carrying and walking on one meter radius curved path. Spinal kinematics was determined at the left leg heel strike and just before the right toe off during the curved path walking. As a result, a significant main effect of load intensity was found only on FE of (Tho/Virtual lab) at both left leg heel strike and right leg toe off. The study concluded that an increase in the load intensity of unstable load from 10% of body weight likely to generate more thorax extension.