Search Results (769)

Conventional ground reaction force (GRF) and load rate (LR) analyses may overlook temporal and waveform characteristics that reflect injury status and acuity. This study used an alternative GRF processing methodology to characterize GRF waveforms among runners with symptomatic medial tibial stress fractures (MTSS) and those recovering from tibial stress fractures (TSF; both unilateral [UL] and bilateral [BL]). This cross-sectional analysis of runners (n = 66) included four groups: symptomatic MTSS, recovering from UL or BL TSF, or uninjured case-matched controls. Participants ran at self-selected speed on an instrumented treadmill. Kinematics were collected with a 3D optical motion analysis system. Double-Gaussian models described the biphasic loading pattern of running gait (initial impact, active phases). Gaussian parameters described relative differences in the GRF waveform by injury condition. LR was calculated using the central difference numerical derivative of the raw normalized net force data. During the impact phase (0–20% of stance), controls and BL TSF produced higher GRF amplitudes than UL TSF and MTSS (p < 0.05). BL TSF and controls had greater maximal positive LR and minimum LR than UL TSF and MTSS. Peak medial GRF was 18–43% higher in the BL TSF group than in MTSS and UL TSF (p < 0.05). Correlations existed between tibial pain severity and early stance net GRF (r = 0.512; p = 0.016) and between pain severity and the duration since diagnosis for LR values during the impact phase (r values = 0.389–0.522; all p < 0.05). Collectively, these data suggest that this waveform modeling approach can differentiate injury status and pain acuity in runners. Early stance GRF and LR may offer novel insight into the management of running-related injuries. Full article

Optical sensor technologies are reshaping obesity detection by enabling non-invasive, dynamic analysis of biomechanical and morphological biomarkers. This review synthesizes recent advances in three key areas: optical gait analysis, vision-based pose estimation, and depth-sensing voxel modeling. Gait analysis leverages optical sensor arrays and video systems to identify obesity-specific deviations, such as reduced stride length and asymmetric movement patterns. Pose estimation algorithms—including markerless frameworks like OpenPose and MediaPipe—track kinematic patterns indicative of postural imbalance and altered locomotor control. Human voxel modeling reconstructs 3D body composition metrics, such as waist–hip ratio, through infrared-depth sensing, offering precise, contactless anthropometry. Despite their potential, challenges persist in sensor robustness under uncontrolled environments, algorithmic biases in diverse populations, and scalability for widespread deployment in existing health workflows. Emerging solutions such as federated learning and edge computing aim to address these limitations by enabling multimodal data harmonization and portable, real-time analytics. Future priorities involve standardizing validation protocols to ensure reproducibility, optimizing cost-efficacy for scalable deployment, and integrating optical systems with wearable technologies for holistic health monitoring. By shifting obesity diagnostics from static metrics to dynamic, multidimensional profiling, optical sensing paves the way for scalable public health interventions and personalized care strategies. Full article

Background: Hemiparetic gait is characterized by reduced limb shortening during swing, increasing the risk of tripping and leading to compensatory strategies. Despite 3D gait analysis being the gold standard for gait assessment, there is no consensus on relevant kinematic biomarkers for limb shortening and compensatory movements. Methods: Systematic review querying five databases (PubMed, Cochrane, Scopus, PEDro, and Web of Science). We included articles that described at least one kinematic biomarker of the lower limb in the sagittal plane and at least one biomarker of the lower limb or pelvis in the transversal or frontal plane, or pelvis in the sagittal plane. Then, we collected kinematic biomarkers from these studies and identified those that seemed relevant to describe limb shortening and compensatory movements during the swing phase. Results: We included 40 studies and collected 385 biomarkers. Among them, 15 described limb shortening, 22 compensations, and 3 toe clearance. Analysis of 12 interventional studies showed that some biomarkers of shortening and compensation were more sensitive to change than others. Conclusions: This review highlights the lack of standardized description for limb shortening and compensatory movements in hemiparetic gait. A set of 13 relevant biomarkers is proposed to improve the interpretation of gait analysis and support consistent evaluation of therapeutic interventions. Full article

SYNGAP1-related disorder is a rare neurodevelopmental disorder characterized by intellectual and motor disabilities, including disordered gait control. Currently, there have been few studies that have assessed the gait of individuals with SYNGAP1-related disorder using technology-based collection techniques. The purpose of this investigation was to characterize the kinematic gait pattern of these individuals using camera-based motion capture technology during treadmill walking. Both linear and non-linear analysis techniques were used to analyze bilateral lower-limb joint motion and compare the results to age-matched neurotypical individuals. Results indicate that joint range of motion and velocity were decreased in the patient population relative to the neurotypical participants with the non-linear measures of angle–angle and phase portrait areas reflecting similar outcomes. The combination of linear and non-linear measures provide complementary information that, when used in combination, can provide deeper insights into the coordination and control of gait than if either of the measurement techniques are used in isolation. Such information can be useful to clinicians and therapists to develop targeted interventions designed to improve the gait of individuals with SYNGAP1-related disorder. Full article

Gait analysis is a valuable tool for aiding in the diagnosis of neurological diseases, providing objective measurements of human gait kinematics and kinetics. These data enable the quantitative estimation of movement abnormalities, which helps to diagnose disorders and assess their severity. In this regard, machine learning techniques and explainability methods offer an opportunity to enhance anomaly detection in gait measurements and support a more objective assessment of neurodegenerative disease, providing insights into the most relevant gait parameters used for disease identification. This study employs several classifiers and explainability methods to analyze gait data from a public dataset composed of patients affected by degenerative neurological diseases and healthy controls. The work investigates the relevance of spatial, temporal, and kinematic gait parameters in distinguishing such diseases. The findings are consistent among the classifiers employed and in agreement with known clinical findings about the major gait impairments for each disease. This work promotes the use of data-driven assessments in clinical settings, helping reduce subjectivity in gait evaluation and enabling broader deployment in healthcare environments. Full article

The urgent need for complex terrain adaptability in industrial automation and disaster relief has highlighted the great potential of octopedal wheel-legged robots. However, their design complexity and motion control challenges must be addressed. In this study, an innovative design approach is employed to construct a highly adaptive robot architecture capable of intelligently adjusting the wheel-leg configuration to cope with changing environments. An advanced kinematic analysis and simulation techniques are combined with inverse kinematic algorithms and dynamic planning to achieve a typical ‘Step-Wise Octopedal Dynamic Coordination Gait’ and different gait planning and optimization. The effectiveness of the design and control strategy is verified through the construction of an experimental platform and field tests, significantly improving the robot’s adaptability and mobility in complex terrain. Additionally, an optional integrated quadrotor module with a compact folding mechanism is incorporated, enabling the robot to overcome otherwise impassable obstacles via short-distance flight when ground locomotion is impaired. This achievement not only enriches the theory and methodology of the multi-legged robot design but also establishes a solid foundation for its widespread application in disaster rescue, exploration, and industrial automation. Full article

Exercise is an important component in the treatment and improvement of function in populations with or at risk of lower limb injury. Cycling is the most common exercise modality used by these populations. However, reduced lower limb joint excursion and/or range of motion (ROM) during cycling might limit the optimization of functional improvements. Increased hip flexion gait (HFgait) is a new exercise modality that might result in larger lower limb joint excursions compared to cycling. The purpose of this study was to compare lower limb kinematics between HFgait and cycling. Twelve healthy individuals participated in the study. Each participant performed cycling and HFgait. Hip, knee, and ankle kinematics in the sagittal, frontal, and transverse planes were analyzed with and without phase offset reduction (POR). Discrete and continuous analyses were performed. Discrete analysis indicated differences for at least one of the variables analyzed (maximum, minimum, and ROM) for the hip (p ≤ 0.041), knee (p ≤ 0.008), and ankle (p ≤ 0.040) across all planes. For the continuous analysis, differences between HFgait and cycling kinematics were observed during the cycles for the hip, knee, and ankle sagittal (hip: original: 85%; with POR: 77%; knee: original: 93%; with POR: 76%; ankle: original: 14%; with POR: 14%), frontal (hip: original: 93%; with POR: 98%; knee: original: 41%; with POR: 12%; ankle: original: 4%; with POR: 5%), and transverse (hip: original: 66%; with POR: 0%; knee: original: 14%; with POR: 0%; ankle: original: 3%; with POR: 0%) planes. HFgait resulted in larger hip (+60.2°) and knee (+38.2°) sagittal plane ROM while maintaining the hip in a more neutral position in the frontal plane compared with cycling. These findings can support the development of rehabilitation strategies with the goal of improving function and joint range of motion while also receiving the health benefits of exercise. Full article

Weakness, spasticity, and muscle shortening are common in children with cerebral palsy (CP), leading to deficits in gross motor, gait, and selective motor functions. While traditional assessments, such as the Gross Motor Function Measure (GMFM-66), instrumented gait analysis, and the Selective Control Assessment of the Lower Extremity (SCALE), are widely used, they are often limited by the resource-intensive nature of hospital-based evaluations. We employed cyclogram-based analysis, utilizing simple hip and knee joint kinematics to assess clinical measures, including GMFM-66, normalized gait speed, the gait deviation index (GDI), and the gait profile score (GPS). Principal component analysis was used to quantify the cyclogram shape characteristics. A total of 144 children with ambulatory spastic CP were included in the study. All the cyclogram parameters were significantly correlated with GMFM-66, gait speed, the GDI, and the sagittal plane subscore of the GPS for the hip and knee, with the swing phase area showing the strongest correlation. Regression models based on the swing phase area were used to estimate the GMFM-66 (R² = 0.301) and gait speed (R² = 0.484). The PC1/PC2 ratio showed a moderate correlation with selective motor control, as measured by the SCALE (R² = 0.320). These findings highlight the potential of hip–knee cyclogram parameters to be used as accessible digital biomarkers for evaluating motor control and gait function in children with bilateral spastic CP. Further prospective studies using wearable sensors, such as inertial measurement units, are warranted to validate and build upon these results. Full article

Background/Objectives: The projected rise in limb amputations highlights the need for advancements in prosthetic technology. Current transtibial prosthetic designs primarily focus on sagittal plane kinematics but often neglect both the ankle kinematics and kinetics in the coronal plane, and the metatarsophalangeal joint, which play critical roles in gait stability and efficiency. This study aims to evaluate the combined effects of compliance in the coronal plane and a flexible toe joint on prosthetic gait using non-amputated participants as a model. Methods: We conducted gait trials on ten non-amputated individuals in the presence and absence of compliance in the coronal plane and toe compliance, using a previously developed three-degree-of-freedom (DOF) prosthetic foot with a prosthetic simulator. We recorded and analyzed sagittal and coronal kinematic data, ground reaction forces, and electromyographic signals from muscles involved in the control of gait. Results: The addition of compliance in the coronal plane and toe compliance had significant kinematic and muscular effects. Notably, this compliance combination reduced peak pelvis obliquity by 27%, preserved the swing stance/ratio, and decreased gluteus medius’ activation by 34% on the non-prosthetic side, compared to the laterally rigid version of the prosthesis without toe compliance. Conclusions: The results underscore the importance of integrating compliance in the coronal plane and toe compliance in prosthetic feet designs as they show potential in improving gait metrics related to mediolateral movements and balance, while also decreasing muscle activation. Still, these findings remain to be validated in people with transtibial amputations. Full article

Central pattern generators (CPGs) have been extensively researched and validated as a well-established methodology for bionic control, particularly within the field of legged robotics. However, investigations concerning octopod robots remain relatively sparse. This study presents the design of an octopod robotic system inspired by the biological characteristics of lobsters. The machine lobster utilizes remote sensing technology to execute designated tasks in subterranean and mining environments, with its motion regulated by CPGs, accompanied by a comprehensive simulation analysis. The research commenced with the modeling of a biomimetic lobster robot, which features a three-degree-of-freedom leg structure and torso, interconnected by shape memory alloys (SMAs) that serve as muscle actuators. Mathematically, both forward and inverse kinematics were formulated for the robot’s legs, and a 24-degree-of-freedom (DOF) gait pattern was designed and validated through MATLAB 2020a simulations. Subsequently, a multi-layer mesh CPG neural network model was developed utilizing the Kuramoto model, which incorporated frustration effects as the rhythm generator. The control model was constructed and evaluated in Simulink, while dynamic simulations were conducted using Adams 2022 software. The findings demonstrate the feasibility, robustness, and efficiency of the proposed CPG network in facilitating the forward locomotion of the lobster robot, thereby broadening the range of control methodologies applicable to octopod biomimetic robots. Full article

Background: Marker-based motion capture is the current gold standard for three-dimensional (3D) gait analysis. This is a highly technical analysis that is time-consuming, and marker application can trigger anxiety in children. One potential solution is to use markerless camera systems instead. The objective of this study was to compare 3D lower limb gait kinematics in children using both marker-based and markerless motion capture methods. Methods: Ten typically developing children (age 6–13 yrs) completed five barefoot walks at a self-selected speed. A 10-camera marker-based system (Oqus, Qualisys) and a 7-camera markerless system (Miqus, Qualisys) captured synchronised gait data at 85 Hz. Generalised Additive Mixed Models were fitted to the data to identify the random effects of measurement systems, age, and time across the gait cycle. The root-mean-square difference (RMSD) was used to compare the differences between systems. Results: Significant interactions and differences were observed between the marker-based and markerless systems for most joint angles and planes of motion, particularly with regard to time and age. Conclusions: Despite differences across all kinematic profiles, the RMSD in this study was comparable to previously published results. Alternative model definitions and kinematic crosstalk in both systems likely explain the differences. Age differences were not consistent across joint levels, suggesting a larger sample size is required to determine how maturation may affect markerless tracking. Further investigation is required to understand the deviations and differences between systems before implementing markerless technology in a clinical setting. Full article

Hallux valgus (HV) is described as a lateral deviation of the great toe at the first metatarsophalangeal joint (MTP), which is a very common foot deformity in the clinic. This deformity extends beyond localized foot mechanics to affect the entire lower extremity kinetic chain, potentially increasing dynamic instability during locomotion. This study aimed to characterize the kinematics of ankle and knee joints during walking in HV patients compared to controls. In total, 23 patients with bilateral HV and matched healthy controls were recruited. The 6-DOF kinematics data of ankles and knees were collected using a joint motion function analysis system while level walking at adaptive speed. HV patients demonstrated significant kinematic alterations in the ankle joint at IC, including decreased varus by 2.87° (p < 0.001), decreased internal rotation by 1.77° (p = 0.035), and decreased plantarflexion by 4.39° (p < 0.001) compared with healthy subjects. Concurrent compensatory changes in the knee joint included increased varus rotation by 1.41° (p = 0.023), reduced anterior translation by 0.84 mm (p < 0.001), and increased lateral translation by 0.26 mm (p = 0.036). HV patients showed increased ankle dorsiflexion of 3.61° (p = 0.06) and decreased ankle internal rotation of 2.69° (p = 0.043), with concurrent increased knee internal rotation of 2.59° (p = 0.009) at SPF. The ripple effect during walking in the HV population may elevate the risk of knee pathologies. These findings may inform both conservative management strategies and post-surgical rehabilitation regimens. Full article

The use of gait analysis to differentiate among paediatric populations with neurological and developmental conditions such as idiopathic toe walking (ITW), cerebral palsy (CP), and hereditary spastic paraplegia (HSP) remains challenging due to the insufficient precision of current diagnostic approaches, leading in some cases to misdiagnosis. Existing methods often isolate the analysis of gait variables, overlooking the whole complexity of biomechanical patterns and variations in motor control strategies. While previous studies have explored the use of statistical physics principles for the analysis of impaired gait patterns, gaps remain in integrating both kinematic and kinetic information or benchmarking these approaches against Deep Learning models. This study evaluates the robustness of statistical physics metrics in differentiating between normal and abnormal gait patterns and quantifies how the data source affects model performance. The analysis was conducted using gait data sets from two research institutions in Madrid and Dublin, with a total of 81 children with ITW, 300 with CP, 20 with HSP, and 127 typically developing children as controls. From each kinematic and kinetic time series, Shannon’s entropy, permutation entropy, weighted permutation entropy, and time irreversibility metrics were derived and used with Random Forest models. The classification accuracy of these features was compared to a ResNet Deep Learning model. Further analyses explored the effects of inter-laboratory comparisons and the spatiotemporal resolution of time series on classification performance and evaluated the impact of age and walking speed with linear mixed models. The results revealed that statistical physics metrics were able to differentiate among impaired gait patterns, achieving classification scores comparable to ResNet. The effects of walking speed and age on gait predictability and temporal organisation were observed as disease-specific patterns. However, performance differences across laboratories limit the generalisation of the trained models. These findings highlight the value of statistical physics metrics in the classification of children with different toe walking conditions and point towards the need of multimetric integration to improve diagnostic accuracy and gain a more comprehensive understanding of gait disorders. Full article

Neuromuscular gait deficits in children with autism spectrum disorder (ASD) are often overlooked. High-intensity training protocols may improve running performance, but their efficacy in pediatric populations is underexplored. This study evaluates the impact of a high-intensity running protocol on locomotor performance in neurotypical and neurodivergent children (children with ASD). Spatiotemporal gait characteristics (speed, stride frequency, stride length, and duty factor), gait symmetry (symmetry ratio), and kinematics were assessed for ten neurodivergent children (10–15 years old) during a 15 m sprint. Locomotor costs (cost of locomotion, transport, and locomotion per stride) were analyzed in six neurodivergent participants (11–14 years old) via open-flow respirometry during treadmill running. Participants completed a 5–12 week, twice-weekly program; neurotypical participants served as a control group. Neurodivergent and neurotypical children exhibited baseline differences in spatiotemporal variables. Following training, neurodivergent participants demonstrated statistically significant improvements in spatiotemporal metrics and locomotor costs. Differences in symmetry between the two groups were not present pre- or post-program. These findings highlight the efficacy of high-intensity running programs in improving sensorimotor function and coordination in children with ASD. This program provides valuable insights into gross motor rehabilitation for neurodivergent children, supporting its potential as an effective intervention. Full article

Background/Objectives: This study focuses on the motion planning and control of an active ankle–foot orthosis (AFO) that leverages biomechanical insights to mitigate footdrop, a deficit that prevents safe toe clearance during walking. Methods: To adapt the motion of the device to the user’s walking speed, a geometric model was used, together with real-time measurement of the user’s gait cycle. A geometric speed-adaptive model also scales a trapezoidal ankle-velocity profile in real time using the detected gait cycle. The algorithm was tested at three different walking speeds, with a prototype of the AFO worn by a test subject. Results: At walking speeds of 0.44 and 0.61 m/s, reduced tibialis anterior (TA) muscle activity was confirmed by electromyography (EMG) signal measurement during the stance phase of assisted gait. When the AFO was in assistance mode after toe-off (initial and mid-swing phase), it provided an average of 48% of the estimated required power to make up for the deliberate inactivity of the TA muscle. Conclusions: Kinematic analysis of the motion capture data showed that sufficient foot clearance was achieved at all three speeds of the test. No adverse effects or discomfort were reported during the experiment. Future studies should examine the device in populations with footdrop and include a comprehensive evaluation of safety. Full article