Search

Total ankle arthroplasty (TAA) is a motion-preserving treatment for end-stage ankle arthritis. An effective tool for analyzing these implants' mechanical performance and longevity in silico is finite element analysis (FEA). An FEA in ABAQUS was used to statically analyze the mechanical behavior of the ultra-high-molecular-weight polyethylene (UHMWPE) bearing component at varying dorsiflexion/plantarflexion ankle angles and axial loading conditions during the stance phase of the gait cycle for a single cycle. The von Mises stress and contact pressure were examined on the articulating surface of the bearing component in two newly installed fixed-bearing TAA implants (Wright Medical INBONE II and Exactech Vantage). Six different FEA models of variable ankle compressive load levels and ankle angle positions, for the varying subphases of the stance phase of the gait cycle, were created. The components in these models were constrained to be conducive to the bone–implant interface, where implant loosening occurs. Our results showed that the von Mises stress and contact pressure distributions increased as the compressive load increased. The highest stress was noted at dorsiflexion angles > 15°, in areas where the UHMWPE liner was thinnest, at the edges of the talar and UHMWPE components, and during the terminal stance phase of the gait cycle. This static structural analysis highlighted these failure regions are susceptible to yielding and wear and indicated stress magnitudes that are in agreement (within 25%) with those in previous static structural TAA FEAs. The mechanical wear of the UHMWPE bearing component in TAA can lead to aseptic loosening and peri-implant cyst formation over time, requiring surgical revision. This study provides ankle replacement manufacturers and orthopedic surgeons with a better understanding of the stress response and contact pressure sustained by TAA implants, which is critical to optimizing implant longevity and improving patient care. [ABSTRACT FROM AUTHOR]

Gait cycle variability during steady walking, described by the stride interval time series, has been used as a gait-stability-related measure. In particular, the positive persistency in the stride intervals with 1/f-like fluctuation and reduction of the persistency are the well-documented metrics that can characterize gait patterns of healthy young adults and elderly including patients with neurological diseases, respectively. Here, we examined effects of a dual task on gait cycle variability in healthy young adults, based on the mean and standard deviation statistics as well as the positive persistency of the stride intervals during steady walking on a treadmill. Specifically, three gait conditions were examined: control condition, non-cognitive task with holding a smartphone in front of the chest using their dominant hand and looking fixedly at a blank screen of the smartphone, and cognitive motor task with holding a smartphone as in the non-cognitive task and playing a puzzle game displayed on the smartphone by one-thumb operation. We showed that only the positive persistency, not the mean and standard deviation statistics, was affected by the cognitive and motor load of smartphone usage in the cognitive condition. More specifically, the positive persistency exhibited in the control and the non-cognitive conditions was significantly reduced in the cognitive condition. Our results suggest that the decrease in the positive persistency during the cognitive task, which might represent the deterioration of healthy gait pattern, is caused endogenously by the cognitive and motor load, not necessarily by the reduction of visual field as often hypothesized. [ABSTRACT FROM AUTHOR]

Accurate detection of gait events is crucial for gait analysis, enabling the assessment of gait patterns and abnormalities. Inertial measurement unit (IMU) sensors have gained traction for event detection, mainly focusing on initial contact (IC) and toe-off (TO) events. However, effective detection of other key events such as heel rise (HR), feet adjacent (FA), and tibia vertical (TBV) is essential for comprehensive gait analysis. Can a novel IMU-based method accurately detect HR, TO, FA, and TBV events, and how does its performance compare with existing methods? We developed and validated an IMU-based method using cumulative mediolateral shank angular velocity (CSAV) for event detection. A dataset of nearly 25,000 gait cycles from healthy adults walking at varying speeds and footwear conditions was used for validation. The method's accuracy was assessed against force plate and motion capture data and compared with existing TO detection methods. The CSAV method demonstrated high accuracy in detecting TO, FA, and TBV events and moderate accuracy in HR event detection. Comparisons with existing TO detection methods showcased superior performance. The method's stability across speed and shoe variations underscored its robustness. This study introduces a highly accurate IMU-based method for detecting gait events needed to divide the gait cycle into seven phases. The effectiveness of the CSAV method in capturing essential events across different scenarios emphasizes its potential applications. Although HR event detection can be further improved, the precision of the CSAV method in TO, FA, and TBV detection advance the field. This study bridges a critical gap in IMU-based gait event detection by introducing a method for subdividing the swing phase into its subphases. Further research can focus on refining HR detection and expanding the method's utility across diverse gait contexts, thereby enhancing its clinical and scientific significance. • 15 healthy participants, 24,519 steps, and 9 scenarios. • Using shank angular velocity, novel method detects gait events with precision. • Validated for initial contact, heel rise, toe-off, feet adjacent, and tibia vertical. • Bland-Altman plots, ICC scores show high agreement with gold standard techniques. [ABSTRACT FROM AUTHOR]

This article introduces a data‐driven locomotion style controller for full‐body human characters using gait cycle features. Based on gait analysis, we define a set of gait features that can represent various locomotion styles as spatio‐temporal patterns within a single gait cycle. We compute the gait features for every single gait cycle in motion capture data and use them to search for the desired motion. Our real‐time style controller provides users with visual feedback for the changing inputs, exploiting the Motion Matching algorithm. We also provide a graphical controller interface that visualizes our style representation to enable intuitive control for users. We show that the proposed method is capable of retrieving appropriate locomotions for various gait cycle features, from simple walking motions to single‐foot motions such as hopping and dragging. To validate the effectiveness of our method, we conducted a user study that compares the usability and performance of our system with those of an existing footstep animation tool. The results show that our method is preferred over the baseline method for intuitive control and fast visual feedback. [ABSTRACT FROM AUTHOR]

BACKGROUND: At present, most of biomechanical studies on medial meniscus posterior root tearing to accelerate knee joint degeneration are limited to testing the complete tear model of the posterior root of the medial meniscus on the basis of static simulation design. However, the biomechanical behavior of medial meniscus posterior root tear in the full gait cycle is not clear. OBJECTIVE: To compare the biomechanical differences between the normal knee joint model and the medial meniscus posterior root partial tear model in the complete gait cycle using dynamic finite element analysis method. METHODS: Based on the CT scan data of the right knee joint of healthy adults, the finite element model of healthy knee joint including bone, meniscus and articular cartilage was established, and the posterior root tear model of medial meniscus of knee joint was further established on the basis of healthy model. The standard gait load of ISO was applied to the two models for simulation test. The differences of stress, displacement and contact area of the corresponding parts of the two models were compared. RESULTS AND CONCLUSION: (1) Under the complete gait cycle, the stress distribution of the posterior root of the medial meniscus in the healthy model was uniform, while the pathological model showed stress concentration in the injured area. The maximum stress of the former appeared at the inner edge of the lateral meniscus at 30% time, with a value of 29.68 MPa. The latter maximum stress appeared at the inner edge of the lateral meniscus at 50% time, with a value of 30.34 MPa. (2) During the complete gait cycle, the stress distribution of tibial cartilage in healthy and pathological models was roughly the same. The maximum stress of the two models appeared at 50% and 20% around the gait, respectively, and the values were 5.11 MPa and 6.85 MPa, respectively. (3) The difference between the medial intercompartment group and the lateral intercompartment group was greater than that in the lateral intercompartment group. The average stress of the medial tibial plateau of the pathological model was 9.3% higher than that of the normal model, and the maximum value of 5.73 MPa appeared in the middle of the support phase. The peak contact area of femur and tibia appeared at 40% time, and the average contact area of femoral cartilage in each phase of the pathological model decreased by 14.6% compared with the normal model. (4) The results show that alterations in the biomechanical properties of the knee joint after a partial tear of the medial meniscus posterior root increase the risk of osteoarthritis. [ABSTRACT FROM AUTHOR]

BACKGROUND: High plantar pressure is one of the critical factors causing diabetic foot ulcers. Studying the plantar pressure in multi-phase during gait cycle of diabetic patients contributes to offloading footwear development. OBJECTIVE: To analyze the plantar pressure distribution in diabetic patients at heel strike and push off, and design midsole to optimize offloading effect. METHODS: Plantar pressure was tested to analyze the difference in plantar pressure at heel strike and push off between diabetics patients with diabetic peripheral neuropathy and without diabetic peripheral neuropathy and healthy subjects. Finite element model of foot was constructed. Ethylene vinyl acetate copolymer midsole and thermoplastic polyurethane diamond lattice structure midsole with different modulus were designed. Changes in plantar pressure and stress of soft tissue at heel strike and push off in diabetic peripheral neuropathy patient were analyzed to optimize the structure size of diabetes footwear. RESULTS AND CONCLUSION: (1) The peak plantar pressure at push off in diabetic peripheral neuropathy group (22.2%) was higher than healthy control group (P < 0.05). (2) Ethylene vinyl acetate copolymer midsole reduced the peak plantar pressure at heel strike and push off by 13.0% and 12.9%, reduced the peak stress of soft tissue at two phases by 18.2% and 11.1%. (3) The optimized diamond lattice structure reduced the peak plantar pressure at two phases by 41.6% and 48.4%, reduced the peak stress of soft tissue at two phases by 41.4% and 49.8%. (4) In conclusion, offloading at push off should be noticed in development of diabetic footwear. The diamond lattice structure midsole could archive better effect than ethylene vinyl acetate copolymer midsole. [ABSTRACT FROM AUTHOR]

Knee kinematics during gait is an important assessment tool in health-promotion and clinical fields. This study aimed to determine the validity and reliability of a wearable goniometer sensor for measuring knee flexion angles throughout the gait cycle. Twenty-two and seventeen participants were enrolled in the validation and reliability study, respectively. The knee flexion angle during gait was assessed using a wearable goniometer sensor and a standard optical motion analysis system. The coefficient of multiple correlation (CMC) between the two measurement systems was 0.992 ± 0.008. Absolute error (AE) was 3.3 ± 1.5° (range: 1.3–6.2°) for the entire gait cycle. An acceptable AE (<5°) was observed during 0–65% and 87–100% of the gait cycle. Discrete analysis revealed a significant correlation between the two systems (R = 0.608–0.904, p ≤ 0.001). The CMC between the two measurement days with a 1-week interval was 0.988 ± 0.024, and the AE was 2.5 ± 1.2° (range: 1.1–4.5°). A good-to-acceptable AE (<5°) was observed throughout the gait cycle. These results indicate that the wearable goniometer sensor is useful for assessing knee flexion angle during the stance phase of the gait cycle. [ABSTRACT FROM AUTHOR]

Hip joint prostheses are used to replace hip joint function in the human body. The latest dual-mobility hip joint prosthesis has an additional component of an outer liner that acts as a cover for the liner component. Research on the contact pressure generated on the latest model of a dual-mobility hip joint prosthesis under a gait cycle has never been done before. The model is made of ultrahigh molecular weight polyethylene (UHMWPE) on the inner liner and 316L stainless steel (SS 316L) on the outer liner and acetabular cup. Simulation modeling using the finite element method is considered static loading with an implicit solver for studying the geometric parameter design of dual-mobility hip joint prostheses. In this study, simulation modeling was carried out by applying varying inclination angles of 30°, 40°, 45°, 50°, 60°, and 70° to the acetabular cup component. Three-dimensional loads were placed on femoral head reference points with variations of femoral head diameter used at 22 mm, 28 mm, and 32 mm. The results in the inner surface of the inner liner, the outer surface of the outer liner, and the inner surface of the acetabular cup showed that the variations in inclination angle do not have a major effect on the maximum contact pressure value on the liner component, where the acetabular cup with an inclination angle of 45° can reduce contact pressure more than the other studied inclination angle variations. In addition, it was found that the 22 mm diameter of the femoral head increases the contact pressure. The use of a larger diameter femoral head with an acetabular cup configuration at a 45° inclination can minimize the risk of implant failure due to wear. [ABSTRACT FROM AUTHOR]

For time-continuous analysis of gait, the problem of variations in cycle durations is resolved by normalizing to the gait cycle, but results depend on the definition of the cycle start. Gait cycle normalization ignores variations in gait phase durations, which results in averaging and comparing data across different phases. We propose gait phase normalization as part of a comprehensive method for independently analyzing magnitude and timing differences. First, gait phases are identified and differences in absolute and/or relative timing of phase durations or any point of interest between conditions or groups are analyzed using standard statistics. Next, time-continuous gait data is normalized to gait phases, and statistical parametric mapping (SPM) is used to assess magnitude differences in gait data. This approach is demonstrated on data recorded from ten young healthy adults walking on a treadmill at five different speeds. Sagittal knee angle was normalized to gait cycle or gait phase using five different gait cycle start events. Walking at different speeds resulted in significant changes in gait phase durations, highlighting a problem ignored by gait cycle normalization. SPM results for knee angle normalized to gait cycle varied from normalization to gait phases. Gait phase normalized SPM results were robust to the definition of the cycle start, in contrast to gait cycle normalized data. The approach of analyzing phase durations and normalizing data to gait phases overcomes previous limitations and enables a comprehensive analysis of magnitude and timing differences in time-continuous gait data and could be readily adapted to other tasks. [ABSTRACT FROM AUTHOR]

Females with acetabular dysplasia and/or labral tears (hip pain) exhibit altered walking kinematics, with studies reporting mixed results in sagittal and frontal planes compared to pain-free controls, often conducting only discrete analyses and warranting further investigation. The objective of this study was to investigate discrete and continuous hip and pelvic kinematics between females with and without hip pain in two walking conditions. We collected kinematic walking data from 69 females (35 with hip pain, 34 controls) using motion capture and an instrumented treadmill in two conditions: preferred and fast (125% preferred). We used a general linear model and one-dimensional statistical parametric mapping to conduct discrete and continuous analyses comparing kinematics between groups, with and without adjustment for gait speed. The hip pain group walked with reduced peak hip extension (Preferred: P =.046, Cohen's d = 0.41; Fast: P =.028, d = 0.48) and greater peak anterior pelvic tilt (Preferred: P =.011, d = 0.57; Fast: P =.012, d = 0.58) compared to controls. From continuous analyses, the hip pain group walked with reduced hip extension during terminal stance (Fast: P =.040), greater anterior pelvic tilt throughout (Preferred: P =.007; Fast: P =.004), and greater contralateral pelvic drop (Preferred: P =.045) during midstance. Adjusting for speed slightly affected p -values, but significance was retained for all prior variables except pelvic drop. Kinematic differences between individuals with and without hip pain may provide insight into potential predisposing factors for hip pathology and/or compensations for pain or pathological processes. This work furthers understanding of altered movement patterns in individuals with hip pain and may inform physical therapy treatments. • Females with dysplasia and/or labral tears (hip pain) walk with altered kinematics. • Females with hip pain walk with less hip extension than pain-free controls. • Females with hip pain walk with more anterior pelvic tilt than pain-free controls. • Kinematic differences exist between groups at peaks and throughout the gait cycle. [ABSTRACT FROM AUTHOR]

Background: Hallux limitus is a common foot disorder whose incidence has increased in the school-age population. Hallux limitus is characterized by musculoskeletal alteration that involves the metatarsophalangeal joint causing structural disorders in different anatomical areas of the locomotor system, affecting gait patterns. The aim of this study was to analyze dynamic plantar pressures in a school-aged population both with functional hallux and without. Methods: A full sample of 100 subjects (50 male and 50 female) 7 to 12 years old was included. The subjects were identified in two groups: the case group (50 subjects characterized as having hallux limitus, 22 male and 28 female) and control group (50 subjects characterized as not having hallux limitus, 28 male and 22 female). Measurements were obtained while subjects walked barefoot in a relaxed manner along a baropodometric platform. The hallux limitus test was realized in a seated position to sort subjects out into an established study group. The variables checked in the research were the surface area supported by each lower limb, the maximum peak pressure of each lower limb, the maximum mean pressure of each lower limb, the body weight on the hallux of each foot, the body weight on the first metatarsal head of each foot, the body weight at the second metatarsal head of each foot, the body weight at the third and fourth metatarsal head of each foot, the body weight at the head of the fifth metatarsal of each foot, the body weight at the midfoot of each foot, and the body weight at the heel of each foot. Results: Non-significant results were obtained in the variable of pressure peaks between both study groups; the highest pressures were found in the hallux with a p-value of 0.127 and in the first metatarsal head with a p-value 0.354 in subjects with hallux limitus. A non-significant result with a p-value of 0.156 was obtained at the second metatarsal head in healthy subjects. However, significant results were observed for third and fourth metatarsal head pressure in healthy subjects with a p-value of 0.031 and regarding rearfoot pressure in subjects with functional hallux limitus with a p-value of 0.023. Conclusions: School-age subjects with hallux limitus during gait exhibit more average peak plantar pressure in the heel and less peak average plantar pressure in the third and fourth metatarsal head as compared to healthy children aged between 7 and 12 years old. [ABSTRACT FROM AUTHOR]

BACKGROUND: There are few studies on dynamic biomechanical analysis of Kirschner wire tension band steel wire in different winding methods for the treatment of transverse patella fractures. OBJECTIVE: To analyze the biomechanical difference between the “8”-shaped Kirschner wire tension band fixation and the “0”-shaped Kirschner wire tension band for the treatment of transverse patella fractures in the complete gait cycle using three-dimensional reconstruction technology METHODS: Based on the CT scan data of the human knee joint, Mimics, Geomagic Studio, Hypermesh and Abaqus and other three-dimensional reconstruction softwares were used to establish the “8” and “0” shape Kirschner wire tension band to treat the finite element model of the patella transverse fracture. A complete gait cycle of the knee joint after surgery was simulated by loading the material properties, setting boundary conditions, applying loads and other operations. The difference in displacement and stress between the two fixed models was analyzed. RESULTS AND CONCLUSION: (1) In the complete gait cycle, the change of stress value was positively correlated with the change of buckling angle, and the maximum stress reached at 70% of the gait cycle. In the same gait instant, the stress of each component of the “0” model was less than that of the “8” model. (2) The displacement value of each component of the two models increased with the increase of the flexion angle during a complete cycle, and reached the peak displacement at 70% of the gait cycle. In the same gait instantaneously, the “0”-shaped model was different. The displacement values of the components were all smaller than those in the “8” model. At the peak of the displacement, the displacement values of the patella, Kirschner wire and steel wire of the “0” model were 10%, 11%, and 13% smaller than those of the “8” model. (3) The results show that during the complete gait cycle, the high stress areas of the two tension band models are mainly concentrated near the patella fracture line and the contact part of the internal fixation, but the stress peak value of each component in the “0” model is less than “8”-shaped model, and it is better than the “8”-shaped tension band model in terms of the stability of the fracture end and internal fixation, and has a better biomechanical effect. [ABSTRACT FROM AUTHOR]

BACKGROUND: There are few studies on dynamic biomechanical analysis of Kirschner wire tension band steel wire in different winding methods for the treatment of transverse patella fractures. OBJECTIVE: To analyze the biomechanical difference between the “8”-shaped Kirschner wire tension band fixation and the “0”-shaped Kirschner wire tension band for the treatment of transverse patella fractures in the complete gait cycle using three-dimensional reconstruction technology. METHODS: Based on the CT scan data of the human knee joint, Mimics, Geomagic Studio, Hypermesh and Abaqus and other three-dimensional reconstruction softwares were used to establish the “8” and “0” shape Kirschner wire tension band to treat the finite element model of the patella transverse fracture. A complete gait cycle of the knee joint after surgery was simulated by loading the material properties, setting boundary conditions, applying loads and other operations. The difference in displacement and stress between the two fixed models was analyzed. RESULTS AND CONCLUSION: (1) In the complete gait cycle, the change of stress value was positively correlated with the change of buckling angle, and the maximum stress reached at 70% of the gait cycle. In the same gait instant, the stress of each component of the “0” model was less than that of the “8” model. (2) The displacement value of each component of the two models increased with the increase of the flexion angle during a complete cycle, and reached the peak displacement at 70% of the gait cycle. In the same gait instantaneously, the “0”-shaped model was different. The displacement values of the components were all smaller than those in the “8” model. At the peak of the displacement, the displacement values of the patella, Kirschner wire and steel wire of the “0” model were 10%, 11%, and 13% smaller than those of the “8” model. (3) The results show that during the complete gait cycle, the high stress areas of the two tension band models are mainly concentrated near the patella fracture line and the contact part of the internal fixation, but the stress peak value of each component in the “0” model is less than “8”-shaped model, and it is better than the “8”-shaped tension band model in terms of the stability of the fracture end and internal fixation, and has a better biomechanical effect. [ABSTRACT FROM AUTHOR]

Background: Anterior femoral notching (AFN) is a severe complication of total knee replacement (TKR), which in a percentage of patients may lead to fractures after surgery. The purpose of this study was to investigate the stress distribution in patients with AFN and the safety depth of AFN during the gait cycle.Methods: We performed a finite element (FE) analysis to analyse the mechanics around the femur during the gait cycle in patients with AFN. An adult volunteer was selected as the basis of the model. The TKR models were established in the 3D reconstruction software to simulate the AFN model during the TKR process, and the 1 mm, 2 mm, 3 mm, 4 mm, and 5 mm AFN models were established, after which the prosthesis was assembled. Three key points of the gait cycle (0°, 22°, and 48°) were selected for the analysis.Results: The stress on each osteotomy surface was stable in the 0° phase. In the 22° phase, the maximum equivalent stress at 3 mm was observed. In the 48° phase, with the increase in notch depth, each osteotomy surface showed an overall increasing trend, the stress range was more extended, and the stress was more concentrated. Moreover, the maximum equivalent force value (158.3 MPa) exceeded the yield strength (115.1 MPa) of the femur when the depth of the notch was ≥ 3 mm.Conclusions: During the gait cycle, if there is an anterior femoral cortical notch ≥ 3 mm, the stress will be significantly increased, especially at 22° and 48°. The maximum equivalent stress exceeded the femoral yield strength and may increase the risk of periprosthetic fractures. [ABSTRACT FROM AUTHOR]

BACKGROUND: The ankle joint is one of the most important load-bearing joints in the human body and plays an important role in walking. At present, there is a lack of research on the stress of the ankle joint in the gait cycle. OBJECTIVE: To analyze the stress and area changes of the ankle joint during the gait cycle based on the finite element analysis method. METHODS: First, an ankle finite element model was constructed with Mimics 16.0 software and Rapidform XOR3 64 software. The stress and contact area of this ankle joint model were compared with Anderson’s finite element model to verify the effectiveness of the model. Finally, ABAQUS finite element analysis software was used to simulate the stress state of the ankle joint during the gait cycle in a balanced standing condition and the pre-swing condition. By comparing the stress changes in different conditions in the same area, the role of the ankle joint in the gait cycle was analyzed to explore the changes in ankle stress under joint instability. RESULTS AND CONCLUSION: (1) The ankle joint finite element model constructed in this study included 44 551 units and 16 718 nodes, and verified its validity and rationality. (2) Balanced standing conditions: The main stresses were concentrated in the anterior fibula ligament (A, B), anterior tibiotalar ligament (C, D), the proximal end of the posterior tibial ligament (F), and the lower surface of the tibiotalar joint (H). The maximum stress at the ankle joint was at the proximal attachment point (F) of the posterior tibiofibular ligament, which was 10.670 MPa. The minimum stress was at the medial malleolus tibial articular surface (J), which was 2.965 MPa. (3) The pre-oscillation condition: The main stress was concentrated in the anterior fibula ligament (A, B), tibialis anterior ligament (C, D), inferior surface of the tibiotalar joint (H), and articular surface of the lateral malleolus talus (K). The maximum stress of the ankle joint was at the proximal end of the tibial anterior ligament (D), which was 23.00 MPa. The minimum stress was at the proximal attachment point (F) of the posterior tibial ligament, which was 3.478 MPa. (4) It is concluded that the finite element model of the ankle joint constructed in this study highly restores the mechanical environment of the ankle joint, clarifies the stress law of the ankle joint during the gait cycle, and provides ideas for the diagnosis and treatment of clinical ankle joint-related diseases and postoperative rehabilitation. [ABSTRACT FROM AUTHOR]

BACKGROUND: The ankle joint is one of the most important load-bearing joints in the human body and plays an important role in walking. At present, there is a lack of research on the stress of the ankle joint in the gait cycle. OBJECTIVE: To analyze the stress and area changes of the ankle joint during the gait cycle based on the finite element analysis method. METHODS: First, an ankle finite element model was constructed with Mimics 16.0 software and Rapidform XOR3 64 software. The stress and contact area of this ankle joint model were compared with Anderson’s finite element model to verify the effectiveness of the model. Finally, ABAQUS finite element analysis software was used to simulate the stress state of the ankle joint during the gait cycle in a balanced standing condition and the pre-swing condition. By comparing the stress changes in different conditions in the same area, the role of the ankle joint in the gait cycle was analyzed to explore the changes in ankle stress under joint instability. RESULTS AND CONCLUSION: (1) The ankle joint finite element model constructed in this study included 44 551 units and 16 718 nodes, and verified its validity and rationality. (2) Balanced standing conditions: The main stresses were concentrated in the anterior fibula ligament (A, B), anterior tibiotalar ligament (C, D), the proximal end of the posterior tibial ligament (F), and the lower surface of the tibiotalar joint (H). The maximum stress at the ankle joint was at the proximal attachment point (F) of the posterior tibiofibular ligament, which was 10.670 MPa. The minimum stress was at the medial malleolus tibial articular surface (J), which was 2.965 MPa. (3) The pre-oscillation condition: The main stress was concentrated in the anterior fibula ligament (A, B), tibialis anterior ligament (C, D), inferior surface of the tibiotalar joint (H), and articular surface of the lateral malleolus talus (K). The maximum stress of the ankle joint was at the proximal end of the tibial anterior ligament (D), which was 23.00 MPa. The minimum stress was at the proximal attachment point (F) of the posterior tibial ligament, which was 3.478 MPa. (4) It is concluded that the finite element model of the ankle joint constructed in this study highly restores the mechanical environment of the ankle joint, clarifies the stress law of the ankle joint during the gait cycle, and provides ideas for the diagnosis and treatment of clinical ankle joint-related diseases and postoperative rehabilitation. [ABSTRACT FROM AUTHOR]

Pelvic bone is a complex and robust load-bearing skeletal structure in the human body, the evolution of which might have been influenced by mechanical loads of daily activities like walking, upright standing, and running. Since the main function of skeletal bones is to provide rigidity to the body and provide hard surfaces for muscle attachment as well, in this work we propose a compliance minimization problem to determine whether material distribution guided by topology optimization yields a skeletal structure similar to the pelvic bone under same boundary conditions and volumetric constraints. As bone growth occurs in response to the mechanical loads acting on it, we consider the maximal loads that the pelvic bone may experience for a continued period of time, namely during running. The running gait cycle is divided into seven phases, and the objective function is a weighted combination of these seven phases. The optimal geometries are compared with the natural hemi-pelvis by measuring shape similarity using Procrustes analysis. Results show that the optimal geometries have good shape similarity in stance phases. We also explore the design space by considering a combination of sequence of phases which is an alternative to the weighted multiple load-case objective function. In all cases, the optimal geometries are stiffer than the hip bone. To validate this result, we conducted compression test experiments on selected optimal geometries and natural hemi-pelvis model of same material and found that the experimental results prove that topology optimization based optimal geometries are indeed more stiff than the natural hemi-pelvis geometry. [ABSTRACT FROM AUTHOR]

Balance and walking are fundamental to support common daily activities. Relatively accurate characterizations of normal and impaired gait features were attained at the kinematic and muscular levels. Conversely, the neural processes underlying gait dynamics still need to be elucidated. To shed light on gait‐related modulations of neural activity, we collected high‐density electroencephalography (hdEEG) signals and ankle acceleration data in young healthy participants during treadmill walking. We used the ankle acceleration data to segment each gait cycle in four phases: initial double support, right leg swing, final double support, left leg swing. Then, we processed hdEEG signals to extract neural oscillations in alpha, beta, and gamma bands, and examined event‐related desynchronization/synchronization (ERD/ERS) across gait phases. Our results showed that ERD/ERS modulations for alpha, beta, and gamma bands were strongest in the primary sensorimotor cortex (M1), but were also found in premotor cortex, thalamus and cerebellum. We observed a modulation of neural oscillations across gait phases in M1 and cerebellum, and an interaction between frequency band and gait phase in premotor cortex and thalamus. Furthermore, an ERD/ERS lateralization effect was present in M1 for the alpha and beta bands, and in the cerebellum for the beta and gamma bands. Overall, our findings demonstrate that an electrophysiological source imaging approach based on hdEEG can be used to investigate dynamic neural processes of gait control. Future work on the development of mobile hdEEG‐based brain–body imaging platforms may enable overground walking investigations, with potential applications in the study of gait disorders. [ABSTRACT FROM AUTHOR]

Objective: To construct a comprehensive simulation method of "gait-musculoskeletal system (MS)-finite element (FE)" for analysis of hip joint dynamics characteristics and the changes in the contact stress in the hip throughout a gait cycle. Methods: Two healthy volunteers (male and female) were recruited. The 3D gait trajectories during normal walking and the CT images including the hip and femur of the volunteers were obtained. CT imaging data in the DICOM format were extracted for subjected 3D hip joint reconstruction. The reconstructed 3D model files were used to realize the subject-specific registration of the pelvis and thigh segment of general musculoskeletal model. The captured marker trajectory data were used to drive subject-specific musculoskeletal model to complete inverse dynamic analysis. Results of inverse dynamic analysis were exported and applied as boundary and load settings of the hip joint finite element in ABAQUS. Finally, the finite element analysis (FEA) was performed to analyze contact stress of hip joint during a gait cycle of left foot. Results: In the inverse dynamic analysis, the dynamic changes of the main hip-femoral muscle force with respect to each phase of a single gait cycle were plotted. The hip joint reaction force reached a maximum value of 2.9%BW (body weight) and appeared at the end of the terminal stance phase. Twin peaks appeared at the initial contact phase and the end of the terminal stance phase, respectively. FEA showed the temporal changes in contact stress in the acetabulum. In the visual stress cloud chart, the acetabular contact stress was mainly distributed in the dome of the acetabulum and in the anterolateral area at the top of the femoral head during a single gait cycle. The acetabular contact area was between 293.8 and 998.4 mm2, and the maximum contact area appear at the mid-stance phase or the loading response phase of gait. The maximum contact stress of the acetabulum reached 6.91 MPa for the model 1 and 6.92 MPa for the model 2 at the terminal stance phase. Conclusions: The "Gait-MS-FE" technology is integrated to construct a comprehensive simulation framework. Based on human gait trajectories and their CT images, individualized simulation modeling can be achieved. Subject-specific gait in combination with an inverse dynamic analysis of the MS provides pre-processing parameters for FE simulation for more accurate biomechanical analysis of hip joint. [ABSTRACT FROM AUTHOR]

Falls among the elderly are a major societal problem. While observations of medium-distance walking using inertial sensors identified potential fall predictors, classifying individuals at risk based on single gait cycles remains elusive. This challenge stems from individual variability and step-to-step fluctuations, making accurate classification difficult. We recruited 44 participants, equally divided into high and low fall-risk groups. A smartphone secured on their second sacral spinous process recorded data during indoor walking. Features were extracted at each gait cycle from a 6-dimensional time series (tri-axial angular velocity and tri-axial acceleration) and classified using the gradient boosting decision tree algorithm. Mean accuracy across five-fold cross-validation was 0.936. "Age" was the most influential individual feature, while features related to acceleration in the gait direction held the highest total relative importance when aggregated by axis (0.5365). Combining acceleration, angular velocity data, and the gradient boosting decision tree algorithm enabled accurate fall risk classification in the elderly, previously challenging due to lack of discernible features. We reveal the first-ever identification of three-dimensional pelvic motion characteristics during single gait cycles in the high-risk group. This novel method, requiring only one gait cycle, is valuable for individuals with physical limitations hindering repetitive or long-distance walking or for use in spaces with limited walking areas. Additionally, utilizing readily available smartphones instead of dedicated equipment has potential to improve gait analysis accessibility. • Single gait cycle data classifies fall risk. • Combines acceleration, angular velocity, gradient boosting decision tree. • Accurate classification despite individual variability. • First identification of 3D pelvic motion in fall risk. • Smartphone use improves accessibility of gait analysis. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate walking in multiple sclerosis (MS) patients with mild disability. A case control study with 8 mild disability MS patients and 10 controls was conducted. This study analyzed spatiotemporal, kinematic, and kinetic parameters. We also analyzed the timing of these parameters, as a percentage of the gait cycle. The MS patients and controls walked with a similar gait pattern. However, there were differences in the timing of the biomechanical parameters. The timing of toe-off was at 62–63% of gait cycle in MS subjects while in controls it was at 59.94% (p = 0.009 to 0.027 vs. to controls). The peak of knee flexion during swing was at 74–76% of gait cycle in MS subjects while in controls was at 72% (p = 0.027 to 0.034). While the peak of ankle dorsiflexion during stance occurred at 48–50% in MS subjects, while in controls it was at 46% (p = 0.001 to 0.009), and the peak of plantar flexion during pre-swing was at 66% in MS subjects vs. 64% in controls (p = 0.001). At the kinetic pattern, the first peak of the vertical ground reaction force occurred at 14% of gait cycle in controls while in MS patients it was at 17–20% (p = 0.012 to 0.021). MS subjects with mild disability walked with similar spatiotemporal parameters, joint angles and moments compared to controls. However, our results suggest that those changed the temporal occurrences, expressed as percentage of the gait cycle, of the kinematic and kinetic parameters. [ABSTRACT FROM AUTHOR]

This work presents a topology optimization–based approach towards the optimal design of the human hip bone under mechanical loads during walking. The human hip bone is a complex structure that connects the leg with the torso. It transfers body loads from the upper body to the leg during standing, walking, running, and other daily activities during which it bears nearly two to six times the body weight. This indicates that the evolution of the human hip bone might have been guided by mechanical loads during upright gait which is particular in humans. This motivates us to synthesize an optimal hip structure under loads and constraints of the gait cycle using tools of structural topology optimization. The problem is posed as a compliance minimization problem subject to volume constraint under similar boundary conditions and mechanical loads as the natural hip bone. During a few phases of the gait cycle, the optimal designs from topology optimization achieve good similarity with the natural hip bone. The similarity highly increases under a judicious combination of loading of different phases of the gait cycle. No such prior work exists on the optimal design of the human hip bone as a single entity using topology optimization. The new design may find applications in replacement of hip bone and its parts due to failure under high stresses in different types of injuries. [ABSTRACT FROM AUTHOR]

BACKGROUND: The mechanical environment of cartilage with osteoarthritis at all levels has a certain influence on the development of osteoarthritis. Computer simulation provides a method to quantify the mechanical environment of knee joint cartilage, which makes it possible to study the mechanical behavior of osteoarthritis cartilage by finite element method. OBJECTIVE: To study the stress distribution of cartilage and the change rule of fluid velocity in cartilage of healthy adults and cartilage with osteoarthritis at all levels through numerical simulation so as to explore the mechanical behaviors of cartilage with osteoarthritis at gait cycle. METHODS: The knee joint data of healthy adults were obtained by CT and MRI scanning, and the three-dimensional finite element model of the whole knee joint was established by Abaqus software. The software HyperMesh was used to divide the mesh of the total knee joint, and the binding relationship and interaction between internal components of the knee was set. By changing the material properties of cartilage and adjusting the time length of each phase and the angle between femur and tibial plateau, the cartilage load and boundary conditions of healthy adults and osteoarthritis at all levels could be set in the model. RESULTS AND CONCLUSION: (1) The simulation results showed that the mean Mises stress and the change curves of fluid velocity in the femur cartilage and tibia cartilage increased firstly and then decreased in the gait cycle. (2) Compared with healthy adults, the Mises stress of cartilage in patients with osteoarthritis at all levels continually decreased with duration of disease. The flow velocity of fluid in cartilage firstly increased and then decreased when it developed to osteoarthritis grade 3, and the change range of Mises stress and fluid flow velocity of cartilage with osteoarthritis at all levels decreased. (3) Therefore, with the continuous development of osteoarthritis, the fluid flow velocity increased, the Mises stress decreased and the range of joint surface stress changes decreased in a gait cycle, which lead to the weakening of joint bearing and cushioning capacity. [ABSTRACT FROM AUTHOR]

In a study based on a tibia bone fractured in the diaphyseal region, a Circular External Fixator (CEF) was implanted in this region and its effects were investigated during gait. The CEF mounted on the adult human tibial fracture line is constructed from four standard rings. The six most effective states were selected in terms of force and moment values on the tibia during the human gait cycle. According to the results, it was determined that the stresses are at a maximum in the Kirschner wires in the lower segment. Hence, it was ascertained that the wire and bone junction regions are important and that the geometric and mechanical properties of the wires close to the fracture line should be improved. [ABSTRACT FROM AUTHOR]

Among older people, walking difficulty results from actual and perceived declines in physical capacities and environmental requirements for walking. We investigated whether the physiological complexity of the gait cycle covaries with experience of walking difficulty. Walking difficulty, gait speed, and gait cycle complexity were evaluated among 702 community-dwelling older people aged 75, 80, and 85 years who took part in the six-minute walking test in the research laboratory. Walking difficulty for 500 m was self-reported. Complexity was quantified as trunk acceleration multiscale entropy during the gait cycle. Complexity was then compared between those with no reported walking difficulty, walking with modifications but no difficulty, and those reporting walking difficulty. Higher entropy differentiated those reporting no difficulty walking from those reporting walking difficulties, while those reporting having modified their walking, but no difficulty formed an intermediate group that could not be clearly distinguished from the other categories. The higher complexity of the gait cycle is associated with slower gait speed and the presence of self-reported walking difficulty. Among older people, gait cycle complexity which primarily reflects the biomechanical dimensions of gait quality, could be a clinically meaningful measure reflecting specific features of the progression of walking decline. This encourages further investigation of the sensitivity of gait cycle complexity to detect early signs of gait deterioration and to support targeted interventions among older people. • Older people with walking issues show higher gait complexity in multiscale entropy than those with no walking difficulties. • Walking difficulty aligns with gait complexity, yet self-efficacy in declining gait varies among individuals. • Gait cycle complexity is associated with biomechanical aspects of walking difficulties. [ABSTRACT FROM AUTHOR]

Obesity impacts a child's ability to walk with resulting biomechanical adaptations; however, existing research has not comprehensively compared differences across the gait cycle. We examined differences in lower extremity biomechanics across the gait cycle between children with and without obesity at three walking speeds. Full gait cycles of age-matched children with obesity (N = 10; BMI: 25.7 ± 4.2 kg/m2) and without obesity (N = 10; BMI: 17.0 ± 1.9 kg/m2) were analyzed at slow, normal, and fast walking speeds. Main and interaction effects of group and speed across hip, knee, and ankle joint angles and moments in sagittal, frontal, and transverse planes were analyzed using one-dimensional statistical parametric mapping. Compared to children without obesity, children with obesity had greater hip adduction during mid-stance, while also producing greater hip extensor moments during early stance phase, abductor moments throughout most of stance, and hip external rotator moments during late stance. Children with obesity recorded greater knee flexor, knee extensor and knee internal rotator moments during early stance, and knee external rotator moments in late stance than children without obesity; children with obesity also demonstrated greater ankle plantarflexor moments throughout mid and late stance. Interaction effects existed within joint kinetics data; children with obesity produced greater hip extensor moments at initial contact and toe-off when walking at fast compared to normal walking speed. While few kinematic differences existed between the two groups, children with obesity exhibited greater moments at the hip, knee, and ankle during critical periods of controlling and stabilizing mass. • Gait kinematics and kinetics were analyzed with statistical parametric mapping. • Greater lower extremity joint moments in children with obesity during transitions. • Kinetic differences occur during phases that could increase osteoarthritis risk. [ABSTRACT FROM AUTHOR]

In quadruped robot locomotion using parallel mechanisms, researchers have used equal link lengths as legs for walking. However, force requirements are not the same in the forward and return strokes. An unsymmetrical parallel mechanism can be considered to accommodate such requirements. This work presents optimized dimensions of a 5R planar parallel mechanism (5R-PPM) with two degrees of freedom (DoF). Optimized dimensions are determined by formulating an optimization problem using kinematics and dynamics equations for the 5R-PPM. Genetic algorithm is considered to obtain solutions for the optimization problem formulated in this study. The constraint condition expressed here for optimization will attempt to minimize the peak torque essential to displace the links in the mechanism for the given height of the robot body and the path to be traced by the end-effector. After analysing all the four possible working modes for the same end-effector movement, the best working mode is selected for the quadruped legs. The equations are formulated and solved in MATLAB, and validated in the MATLAB Simscape Multibody toolbox. [ABSTRACT FROM AUTHOR]

The threshold for surgical stabilization for an open-book pelvic fracture is not well defined. The purpose of this research was to validate the biomechanical behavior of a specimen-specific pelvic finite element (FE) model with an open-book fracture with the biomechanical behavior of a cadaveric pelvis in double leg stance configuration under physiologic loading, and to utilize the validated model to compare open book versus intact strain patterns during gait. A cadaveric pelvis was experimentally tested under compressive loading in double leg stance, intact, and with a simulated open-book fracture. An intact FE model of this specimen was reanalyzed with an equivalent simulated open-book fracture. Comparison of the FE generated and experimentally measured strains yielded an R2 value of 0.92 for the open-book fracture configuration. Strain patterns in the intact and fractured models were compared throughout the gait cycle. In double leg stance and heel-strike/heel-off models, tensile strains decreased, especially in the pubic ramus contralateral to the injury, and compressive strains increased in the sacroiliac region of the injured side. In the midstance/midswing gait configuration, higher tensile and compressive FE strains were observed on the midstance side of the fractured versus intact model and decreased along the superior and inferior pubic rami and ischium, with midswing side strains reduced almost to zero in the fractured model. Identified in silico patterns align with clinical understanding of open-book fracture pathology suggesting future potential of FE models to quantify instability and optimize fixation strategies. [ABSTRACT FROM AUTHOR]

The threshold for surgical stabilization for an open-book pelvic fracture is not well defined. The purpose of this research was to validate the biomechanical behavior of a specimen-specific pelvic finite element (FE) model with an open-book fracture with the biomechanical behavior of a cadaveric pelvis in double leg stance configuration under physiologic loading, and to utilize the validated model to compare open book versus intact strain patterns during gait. A cadaveric pelvis was experimentally tested under compressive loading in double leg stance, intact, and with a simulated open-book fracture. An intact FE model of this specimen was reanalyzed with an equivalent simulated open-book fracture. Comparison of the FE generated and experimentally measured strains yielded an R2 value of 0.92 for the open-book fracture configuration. Strain patterns in the intact and fractured models were compared throughout the gait cycle. In double leg stance and heel-strike/heel-off models, tensile strains decreased, especially in the pubic ramus contralateral to the injury, and compressive strains increased in the sacroiliac region of the injured side. In the midstance/midswing gait configuration, higher tensile and compressive FE strains were observed on the midstance side of the fractured versus intact model and decreased along the superior and inferior pubic rami and ischium, with midswing side strains reduced almost to zero in the fractured model. Identified in silico patterns align with clinical understanding of open-book fracture pathology suggesting future potential of FE models to quantify instability and optimize fixation strategies. [ABSTRACT FROM AUTHOR]

Gait models and reference motions are essential for the objective assessment of walking patterns and therapy progress, as well as research in the field of wearable robotics and rehabilitation devices in general. A human can achieve a desired gait speed by adjusting stride length and/or stride frequency. It is hypothesized that sex, age, and physique of a person have a significant influence on the combination of these parameters. A mathematical description of the relation between gait speed and its determinants is presented in the form of a parameterized analytic function. Based on the statistical significance of the parameters, three models are derived. The first two models are valid for slow to fast walking, which is defined as the interval of approximately 0.6–2.0 m s−1, assuming a linear relation of gait speed and stride length, and a non-linear relation of gait speed and stride duration, respectively. The third model is valid for a defined range of walking speed centered at a certain (preferred or spontaneous) gait speed. The latter assumes a constant walk ratio, i.e. the ratio between step or stride length and step or stride frequency, and is recommended for walking at a speed of 1.0–1.6 m s−1. On the basis of a large pool of gait datasets, regression coefficients with significance for age and/or body mass index are identified. The presented models allow to estimate the gait cycle duration based on gait speed, sex, age and body mass index of healthy persons walking on even ground. [ABSTRACT FROM AUTHOR]

BACKGROUND: The biomechanical characteristics of knee meniscus have been studied extensively at home and abroad, but most of them focus on the knee flexion motion. The finite element analysis of biomechanics of knee joint meniscus under the complete gait cycle is not yet perfect. OBJECTIVE: To understand the mechanism of biomechanical changes after meniscus injury in the complete gait cycle by comparing the lateral meniscus tear model with the healthy meniscus model. METHODS: Based on the CT scan data of healthy adult knee joints, a finite element model of healthy knee joint including tibia, meniscus and articular cartilage was established. The lateral meniscus tear of knee joint was constructed based on the healthy model. The biomechanical mechanism of lateral meniscus tear in the knee during complete gait cycle was explored and compared with the healthy knee model. RESULTS AND CONCLUSION: (1) The instantaneous stress variation of the tibia cartilage during the complete gait cycle was consistent in both models. The tibial cartilage stress at each instant in the meniscus tear model was higher than that of the healthy meniscus model. The maximum stress values of tibia cartilage in the meniscus tear model and the healthy meniscus model was 30 and 20.5 MPa. (2) The instantaneous stress variation of the meniscus during the complete gait cycle was consistent in both models. The meniscus stress at each instant in the meniscus tear model was higher than that of the healthy meniscus model. The maximum stress values of meniscus in the meniscus tear model and the healthy meniscus model was 69.8 and 41.3 MPa. (3) In the first 60% of the gait cycle, the maximum stress distribution of the tibia cartilage in the meniscus tear model was much larger than that in the healthy model, and as the gait cycle grew, the contact range gradually spread to the outer edge of the cartilage. After 60% of the gait cycle, the stress on the tibia cartilage was small, and the distribution range of the maximum stress was also small. (4) The stress distribution of the healthy medial meniscus was basically the same in the two models, while the maximum stress distribution of the torn outer meniscus was wider than that of the healthy medial meniscus. A more severe stress concentration phenomenon occurred around the crack, and with the gait cycle, the stress concentration area gradually shifted toward the crack near the anterior corner of the meniscus. (5) These results suggest that the meniscus is an important load-bearing component in human knee joint. From the perspective of biomechanics, the hazard of the meniscus injury on the human knee joint can be observed more intuitively. [ABSTRACT FROM AUTHOR]

A novel approach was designed to regulate the stepping movements in human by means of noninvasive electrical transcutaneous spinal cord stimulation (TSCS) to activate the flexor/extensor motor pools of the lower limbs in the gait cycle. Selective stimulation was delivered automatically based on signals from gyroscope sensors, which served to detect the stance and swing phases. The initiation of hip extension was a trigger for stimulating extensor pools (L1) during the stance phase, and the initiation of hip flexion was a trigger for stimulating flexor motor pools (T11) during the swing phase. In healthy subjects (n = 6) walking on a treadmill, stimulation at L1 with a frequency of 15 Hz decreased the duration of stance phase by 4% (p = 0.0457), increased the amplitude of movements in the hip joint by 11% (p = 0.0266), decreased the movement amplitude in the ankle joint by 17% (p = 0.0081), and increased EMG activities of the extensors vastus lateralis (VL) (by 31%, p = 0.0441) and gastrocnemius medialis (GM) (by 17%, p = 0.0465) and flexors biceps femoris (BF) (by 26%, p = 0.4637) and tibialis anterior (TA) (by 21%, p = 0.0215) relative to walking without stimulation. Stimulation at Т11 with a frequency of 30 Hz reduced the stance phase duration by 3% (p = 0.0318) and increased the amplitude of movements in the hip joint by 12% (p = 0.0467), the knee lifting by 25% (p = 0.0001), and the terminal anthropometric point height above the surface of support by 19% (p = 0.0001). The changes were accompanied by increases in muscle activities of the flexors BF (by 18%, p = 0.230) and TA (by 14%, p = 0.0170). The reciprocity coefficient decreased in thigh muscles by 15% (p = 0.0301) and increased in shin muscles by 5% (p = 0.0452). Alternating spatiotemporal stimulation at L1 and T11 did not significantly change the durations of the gait cycle and its phases, but changed the kinematic characteristics of movements. The amplitude of movements in the hip joint increased in the stance phase. In the swing phase, higher values were observed for the amplitude of movements in the hip joint, the knee lifting, and the terminal anthropometric point height above the surface of support. EMG activities of thigh and shin muscles increased during stimulation at L1 + T11. EMG activity of extensors was higher than that of flexors in the stance phase, while flexor EMG activity exceeded extensor activity in the swing phase. Thus, the data obtained show the possibility of TSCS selectively to activate the motor pools of the lower extremities, and control their activity to regulate the phases of the stepping cycle during human locomotion. [ABSTRACT FROM AUTHOR]

Background: It is unclear how dual-task gait influences the lower limb range of motion (RoM) in people with Parkinson's disease (PD) and freezing of gait (FOG). The lower limb kinematics during dual-task gait might differ from regular gait, but during what events in the gait cycle? Methods: This is an observational within-subjects study. Thirty-two individuals with PD and FOG underwent a gait analysis. Single and dual-task gait was assessed by a 3D motion analysis system and the RoM data of the lower limb were extracted from hips, knees and ankles in the sagittal plane. Dual-task assignment was performed using word-color interference test. To compare both gait conditions, we used two different analyses: (1) common discrete analysis to provide lower limb RoM and (2) Statistical Parametric Mapping analysis (SPM) to provide lower limb joint kinematics. A correlation between lower limb RoM and spatiotemporal gait parameters was also performed for each gait condition. Results: Common discrete analysis evidenced reductions in RoM of hips, knees and ankles during the dual task gait when compared to single gait. SPM analysis showed reductions in flexion-extension of hip, knees and ankles joints when dual task was compared to single task gait. These reductions were observed in specific gait events as toe off (for knees and ankles) and heel strike (for all joints). The reduction in lower limb RoM was positively correlated with the reduction in step length and gait speed. Conclusions: Lower limb joints kinematics were reduced during toe off and heel strike in dual task gait when compared to single gait. These findings might help physiotherapists to understand the influence of dual and single walking in lower limb RoM throughout the gait cycle in people with PD and FOG. [ABSTRACT FROM AUTHOR]

A Finite Element Analysis (FEA) was performed to evaluate the interaction between residual limb and socket when considering the dynamic loads of the gait cycle. Fourteen transfemoral amputees participated in this study, where their residual limbs (i.e., soft tissues and bone), and their sockets were reconstructed. The socket and the femur were defined as elastic materials, while the bulk soft tissues were defined as a hyperelastic material. Each model included the donning, standing, and gait cycle phase, with load and boundary conditions applied accordingly. The influence of adding the dynamic loads related to the gait cycle were compared against the modelling of the static load equivalent to the standing position resulting in changes of 23% ± 19% in the maximum values and in an increase in the size of the regions where they were located. Additionally, the possible correspondence between comfort and the location of peak loadbearing at the residual-limb/socket interface was explored. Consequently, the comfort perceived by the patient could be estimated based on the locations of the maximum stresses (i.e., if they coincide with the pressure tolerant or sensitive regions of the residual limb). [ABSTRACT FROM AUTHOR]

In this paper, an approach based on a liquid state machine (LSM) to compute the movement profiles to achieve a gait pattern subject to different variations in its trajectory is presented. At the same time, the position of the zero moment point (ZMP) to determine the stability of the six degrees-of-freedom (6DOF) bipedal robot in the sagittal plane during the gait cycle is calculated. The system is constructed as a supervised machine learning model. The time series of the oscillating foot trajectory obtained by direct kinematics with a multilayer perceptron neural network (MLP), to strengthen the kinematic model, is considered as input values for training. The target movement profiles are acquired of a human gait cycle analysis in three different scenarios: normal gait, climbing stairs, and descending stairs. In training, this model also gets the trajectories of the ZMP position during the gait cycle, as target time series. The LSM formed by spiking neurons, considered as third-generation neural networks, is compared in the accuracy of prediction, by the dynamic time warping (DTW) technique and correlation analysis, against the human gait analysis database. With this neuronal system, the joint positions to generate a trajectory of the oscillating foot and the ZMP position of the bipedal in the sagittal plane in different scenarios are obtained, proving the robustness of the LSM. [ABSTRACT FROM AUTHOR]

Introduction: Approximately 80% of patients are satisfied with the outcome of arthrodesis of the hallux metatarsophalangeal (MTP) joint. The hypothesis of this study was that MTP arthrodesis does not influence the walking cycle. The aim of this study was to evaluate the effect of MTP arthrodesis on gait cycle and to measure the functional outcome of MTP arthrodesis after a minimum of two year follow-up. Method: This was an observational prospective cohort study performed at a single centre that included 26 patients (32 ft) who underwent unilateral or bilateral MTP arthrodesis during the period 2004–2014. An X-ray assessment based on the American Orthopaedic Foot and Ankle Society score was performed pre-operatively and at the last follow-up (average follow-up duration 8.3 years). The walking cycle was analysed at the final follow-up using a GAITRite® treadmill test. Results: Twenty unilateral and six bilateral MTP arthrodeses were included in this study. The average age of the patients was 70 years. No significant difference was found in the walking cycle between the operated and non-operated sides for unilaterally MTP arthrodesis. However, we observed a non-significant increase in the percentage of contact time after MTP arthrodesis (65% on the operated side vs. 63% on the non-operated side). We also observed a significant decrease in the average walking rate, and a decrease in walking speed, in cases of bilateral MTP arthrodesis compared with normal walking cycle data from a laboratory study. Conclusions: MTP joint arthrodesis does not appear to have any effect on the walking cycle, but reduced patient pain and increased the walking distance. The patients reported satisfaction with the surgical outcomes and would recommend it to a relative with the same pathology. [ABSTRACT FROM AUTHOR]

• A novel method for extracting gait-cycles from acceleration signals is proposed. • Signals of interest are 3D-accelerations of the lower trunk and waist. • The algorithm combines well-known methods with a dynamic time warping strategy. • The result is a generalization of these methods, not relying on fixed thresholds. • Step detection and accuracy are tested on two open gait databases. Gait analysis is the systematic study of human walking. The analysis of gait signals from the lower trunk, acquired through accelerometers, begins with the proper identification of gait cycles. The goal of this work is to supplement gait-event based segmentation methods, tested for unimpaired and impaired populations, so that their need to calibrate or rely on pre-defined thresholds is overcome, and to implement strategies that reduce step-detection errors. A new system for the automatic extraction and analysis of gait cycles from acceleration signals of the lower trunk, combining knowledge from previous strategies with a dynamic time warping function, is presented. Performance was tested on gait signals from public databases. Sensitivities in step detection above 99.95% were achieved, with a positive predictive value of 100.00%. Step-correction strategies reduced the number of incorrect detections from 57 to 3 of 7056 steps. Bland-Altman plots and equivalence tests performed on cycle times by the proposed method and selected references showed good agreement, with mean differences below 0.003 s, and percent errors of 2%. This method may give place to a research tool for the automatic analysis of signals from subjects in a variety of cases. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the kinematics/kinetics of the ankle, knee, hip in the sagittal plane in adolescents with recurrent patellar dislocation in comparison to a healthy control. Methods: Case–control study. Eighty-eight knees (67 patients) with recurrent patellar dislocation (mean age 14.8 years ± 2.8 SD) were compared to 54 healthy knees (27 individuals, 14.9 years ± 2.4 SD). Kinematics/kinetics of ankle, knee, hip, and pelvis were captured using 3D-gait analysis (VICON, 12 cameras, 200 Hz, Plug-in-Gait, two force plates). One cycle (100%) consisted of 51 data-points. The mean of six trials was computed. Results: The loading-response increased by 0.02 s ± 0.01SE (10.8%) with dislocations (0.98% of total gait, P < 0.01). The mid-stance-phase decreased equally (P < 0.01). Dislocation decreased knee flexion during the entire gait cycle (P < 0.01), with the largest difference during mid-stance (9.0° ± 7.2 SD vs. 18.5° ± 6.7 SD). Dislocation increased plantar-flexion during loading response 4.1° ± 0.4 SE with (P < 0.01), afterward, the dorsal-extension decreased 3.2° ± 0.3 SE, (P < 0.01). Dislocation decreased hip flexion during all phases (P < 0.01). Maximal difference: 7.5° ± 0.5 SE during mid-stance. 80% of all patients developed this gait pattern. Internal moments of the ankle increased, of the knee and hip decreased during the first part of stance. Conclusion: Recurrent patellar dislocation decreases knee flexion during the loading-response and mid-stance phase. A decreased hip flexion and increased plantar-flexion, while adjusting internal moments, indicate a compensation mechanism. Level of evidence: III. [ABSTRACT FROM AUTHOR]

The 1/f-like gait cycle variability, characterized by temporal changes in stride-time intervals during steady-state human walking, is a well-documented gait characteristic. Such gait fractality is apparent in healthy young adults, but tends to disappear in the elderly and patients with neurological diseases. However, mechanisms that give rise to gait fractality have yet to be fully clarified. We aimed to provide novel insights into neuro-mechanical mechanisms of gait fractality, based on a numerical simulation model of biped walking. A previously developed heel-toe footed, seven-rigid-link biped model with human-like body parameters in the sagittal plane was implemented and expanded. It has been shown that the gait model, stabilized rigidly by means of impedance control with large values of proportional (P) and derivative (D) gains for a linear feedback controller, is destabilized only in a low-dimensional eigenspace, as P and D decrease below and even far below critical values. Such low-dimensional linear instability can be compensated by impulsive, phase-dependent actions of nonlinear controllers (phase resetting and intermittent controllers), leading to the flexible walking with joint impedance in the model being as small as that in humans. Here, we added white noise to the model to examine P-value-dependent stochastic dynamics of the model for small D-values. The simulation results demonstrated that introduction of the nonlinear controllers in the model determined the fractal features of gait for a wide range of the P-values, provided that the model operates near the edge of stability. In other words, neither the model stabilized only by pure impedance control even at the edge of linear stability, nor the model stabilized by specific nonlinear controllers, but with P-values far inside the stability region, could induce gait fractality. Although only limited types of controllers were examined, we suggest that the impulsive nonlinear controllers and criticality could be major mechanisms for the genesis of gait fractality. [ABSTRACT FROM AUTHOR]

In this paper we present some theoretical considerations and experimental biomechanical analysis of gait cycle. The theoretical aspects of the gait cycle, parameters and limits defining the gait cycle but also an analysis of gait typologies developed by a healthy subject are presented in the first part of the paper. The principles and methodology for investigating structure of gait cycle vs. morphological modifications of plantar surface, using a pressure plate type RSScan and also some experimental aspects highlighted during the developed analysis are presented in the second part of the paper. In the third part of the paper are presented the results of these analysis and correlation strategies. In the final part of the paper, conclusions of the investigations are set by records analyses. Also are presented the development of biomechanical investigations for comparative evaluations and future directions of the studies. [ABSTRACT FROM AUTHOR]

Objective measurement of walking speed and gait deficits are an important clinical tool in chronic illness management. We previously reported in Parkinson's disease that different types of gait tests can now be implemented and administered in the clinic or at home using Ambulosono smartphone-sensor technology, whereby movement sensing protocols can be standardized under voice instruction. However, a common challenge that remains for such wearable sensor systems is how meaningful data can be extracted from seemingly "noisy" raw sensor data, and do so with a high level of accuracy and efficiency. Here, we describe a novel pattern recognition algorithm for the automated detection of gait-cycle breakdown and freezing episodes. Ambulosono-gait-cycle-breakdown-and-freezing-detection (Free-D) integrates a nonlinear m-dimensional phase-space data extraction method with machine learning and Monte Carlo analysis for model building and pattern generalization. We first trained Free-D using a small number of data samples obtained from thirty participants during freezing of gait tests. We then tested the accuracy of Free-D via Monte Carlo cross-validation. We found Free-D to be remarkably effective at detecting gait-cycle breakdown, with mode error rates of 0% and mean error rates < 5%. We also demonstrate the utility of Free-D by applying it to continuous holdout traces not used for either training or testing, and found it was able to identify gait-cycle breakdown and freezing events of varying duration. These results suggest that advanced artificial intelligence and automation tools can be developed to enhance the quality, efficiency, and the expansion of wearable sensor data processing capabilities to meet market and industry demand. [ABSTRACT FROM AUTHOR]

• We have proposed a new representation from gait video frames, stereo silhouettes maps. • Each gait cycle is broken into a few gait cycle segments (GCS) derived from human gait biomechanics. • Spatio-temporal features are extracted for learning intra GCS relationship using pre-trained 3-D CNN. • Over the intra GCS features, LSTM is used to learn long and short term inter GCS relationship. • The gait metric is learned by training in a Siamese framework using triplet loss function, with dynamic adaptive margin. Gait recognition is a non-invasive biometric technology that can be used to identify humans in surveillance systems. It is based on the style or manner in which a person walk and can be realized with minimal amount of individual cooperation for its acquisition. However, it may causes many challenges in the form of varying viewpoints, carrying conditions and clothing variations. To tackle such limitations, we present a view-invariant gait recognition network that divide the gait cycle into five segments (GCS). The intra gait-cycle-segment (GCS) convolutional spatio-temporal relationships has been obtained by employing a 3D-CNN via. transfer learning mechanism. Later, a stacked LSTM has been trained over spatio-temporal features to learn the long and short relationship between inter gait-cycle-segment. The first step in our work is data pre-processing, in which we create silhouette stereo map (SSM) from the binary silhouettes of the gait video frame and sampled each video into a fixed 80 frames. These 80 frames SSM have been divided into 5 gait-cycle-segments (GCS) of 16 frames each. From each of these GCS, we extract spatio-temporal features using a pre-trained 3-D CNN. These features have been concatenated temporally, and an LSTM cell is used to learn the long-term dependencies between each GCS. Finally, the required class scores are computed by averaging (to handle noise) the output generated by LSTM. The network is trained in an end-to-end fashion using triplet loss function so as to learn the gait metric well using only the hard triplets. All the experiments are carried out on publicly available CASIA-B and OU-ISIR gait dataset. From the experimental results, it has been indicated that the proposed network performs better than the current state-of-the-art gait recognition systems. [ABSTRACT FROM AUTHOR]

BACKGROUND: Human beings regularly walk over even and uneven surfaces during their daily activities. A human being with lower limb disability needs an exoskeleton to walk independently. However, walking surface irregularities increase the risk of falling of exoskeleton users. This falling tendency can be minimized by balancing the exoskeleton on irregular surface profiles against the gait cycle variation. Gait variation is studied using quality EMG signals obtained from the gastrocnemius and hamstring muscle activity during uneven surface walking. OBJECTIVE: The present study compares the activity of hamstring and gastrocnemius muscles during walking on a treadmill, utilizing both even and uneven planes. METHODS: Integrated electromyography signals from eight healthy male subjects are collected while walking on a treadmill, even and uneven planes. Muscle activity variation on these planes is studied using two-way ANOVA with replications. RESULTS: The results show that hamstring muscle activity registers a sound variation in swing phase but has no variation in stance phase over all three planes, whereas gastrocnemius muscle activity changes between swing and stance phases over even and uneven planes during forward walking. CONCLUSIONS: The results illustrate that the gait cycle variation depends on surface irregularities which indicates the importance of surface consideration. [ABSTRACT FROM AUTHOR]

Abstract Gait as a biometric property for person identification plays a key role in video surveillance and security applications. In gait recognition, normally, gait feature such as Gait Energy Image (GEI) is extracted from one full gait cycle. However in many circumstances, such a full gait cycle might not be available due to occlusion. Thus, the GEI is not complete giving rise to a degrading in gait-based person identification rate. In this paper, we address this issue by proposing a novel method to identify individuals from gait feature when a few (or even single) frame(s) is available. To do so, we propose a deep learning-based approach to transform incomplete GEI to the corresponding complete GEI obtained from a full gait cycle. More precisely, this transformation is done gradually by training several auto encoders independently and then combining these as a uniform model. Experimental results on two public gait datasets, namely OULP and Casia-B demonstrate the validity of the proposed method in dealing with very incomplete gait cycles. [ABSTRACT FROM AUTHOR]

One commonly used criterion in evaluating a patients' response to knee surgery or rehabilitation is bilateral symmetry. However, the natural symmetry in uninjured healthy adult knee kinematics remains relatively unknown, making it challenging to determine if clinical treatment has adequately restored bilateral symmetry. The primary purpose of this study was to determine the typical side‐to‐side differences in 6 degree of freedom (DOF) knee kinematics over the entire gait cycle in healthy adults using biplane radiography. Six DOF tibiofemoral kinematics were measured during treadmill walking in 19 participants using a validated volumetric model‐based tracking process that matched subject‐specific bone models to biplane radiographs collected at 100 images/s. Average absolute side‐to‐side differences in knee kinematics at foot strike were 1.3 mm or less in translation and 3.8° or less in rotation. Peak side‐to‐side differences in knee kinematics occurred during the swing phase and were up to 2.2 mm in translation and 7.1° in rotation. Dominant versus non‐dominant leg differences were 0.8 mm and 2.8° or less at foot strike and reached maximum values of 0.8 mm and 7.2° over the full gait cycle. Statement of Clinical Significance: This study quantifies the inherent asymmetry of knee kinematics in healthy individuals over the entire gait cycle. The values of asymmetry presented here may serve as a guide for evaluating functional outcomes and restoration of so‐called "normal" kinematics after injury and clinical intervention. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res [ABSTRACT FROM AUTHOR]

The spinal cord contains the neural circuitry needed to generate rhythmic walking motions, and afferent sensory feedbacks are involved in the control of locomotion. In this study, we examined the influence of periodic electrical stimulation on the change in gait cycle period during treadmill walking. 40 subjects walked on a treadmill while receiving periodic bursts of electrical stimulation at various perturbation periods (-20, -40, -60, +20, +40 milliseconds from their initial gait cycle periods). Eleven subjects received electrical stimulation to the hamstring, and 29 received electrical stimulation to the calf. Each subject completed four trials; two trials were conducted using high amplitude stimulation causing a slight degree of joint motion, and the other two trials were conducted using reduced amplitude stimulation which did not cause observable motion. Through the trials, we sought to answer the following questions: 1) does the amplitude of electrical stimulation have an effect on the level of entrainment? 2) does the stimulation site effect the level of entrainment? Entrainment refers to the synchronization of gait cycle period to the period of electrical stimulation. The results showed that entrainment was observed when the perturbation periods were induced relatively close to the subject’s initial gait cycle period. For both stimulation sites, entrainment was shown in 59% of subjects at +/- 20 milliseconds from the initial gait cycle period. With reduced amplitude, entrainment was still observed (51% all stimulation site groups at +/- 20 milliseconds). In addition, after-effects following electrical perturbation were present as seen by changes in the mean gait cycle period. Our results suggest that human locomotor control is organized with a semi-autonomous peripheral oscillator influenced by afferent information, and that electrical stimulation has the potential to be a simpler, and cost-effective tool for locomotion rehabilitation. [ABSTRACT FROM AUTHOR]

Background: Gait disturbances have emerged as some of the main therapeutic concerns in late-stage Parkinson's disease (PD) treated with dopaminergic therapy and deep brain stimulation (DBS). External cues may help to overcome freezing of gait (FOG) and improve some of the gait parameters. Aim: To evaluate the effect of 3D visual cues and STN-DBS on gait in PD group. Methods: We enrolled 35 PD patients treated with DBS of nucleus subthalamicus (STN-DBS). Twenty-five patients (5 females; mean age 58.9 ±6.3) and 25 sex- and age-matched controls completed the gait examination. The gait in 10 patients deteriorated in OFF state. The severity of PD was evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS) and Hoehn and Yahr (HY). The PD group filled the Falls Efficacy Scale-International (FES) and Freezing of Gait Questionnaire (FOGQ). Gait was examined using the GaitRite Analysis System, placed in the middle of the 10m marked path. The PD group was tested without dopaminergic medication with and without visual cueing together with the DBS switched ON and OFF. The setting of DBS was double-blind and performed in random order. Results: The UPDRS was 21.9 ±9.5 in DBS ON state and 41.3 ±13.7 in DBS OFF state. HY was 2.5 ±0.6, FES 12.4 ±4.1 and FOGQ 9.4 ±5.7. In the DBS OFF state, PD group walked more slowly with shorter steps, had greater step length variability and longer duration of the double support phase compared to healthy controls. The walking speed and step length increased in the DBS ON state. The double support phase was reduced with 3D visual cueing and DBS; the combination of both cueing and DBS was even more effective. Conclusion: Cueing with 3D visual stimuli shortens the double support phase in PD patients treated with DBS-STN. The DBS is more effective in prolonging step length and increasing gait speed. We conclude that 3D visual cueing can improve walking in patients with DBS. [ABSTRACT FROM AUTHOR]