Spatiotemporal Gait Parameters Research Articles

Musculoskeletal System and Gait Characteristics in Patients with Osteogenesis imperfecta.

The aim of the study was to assess the muscoloskeletal system and spatiotemporal gait parameters of patients in three types of osteogenesis imperfecta. Retrospective observational study. The Department of Rehabilitation, Children's Memorial Health Institute in Warsaw, Poland. This study investigated individuals with various types of osteogenesis imperfecta: 33 with osteogenesis imperfecta I (aged 13.9), 16 with osteogenesis imperfecta III (aged 10.4), and 14 with osteogenesis imperfecta IV (aged, 15.8), as well as a reference group of 400 healthy individuals. The musculoskeletal assessment included: medical record review, clinical evaluation, functional tests, long bone deformity assessment via clinical and X-ray examination, and objective gait analysis with the Vicon Motion Systems (Ltd, Oxford, UK). The study revealed notable differences in clinical presentation, deformities within the musculoskeletal system, gait parameters across the various types of osteogenesis imperfecta (p < 0.001). The most affected gait parameters were: cadence, gait speed and step length. The greatest deformities of lower limbs and spine were presented in patients with osteogenesis imperfecta type III. These findings are significant for understanding gait abnormalities in osteogenesis imperfecta patients and designing customized physiotherapy programs to help them participate fully in daily life. Improvement of muscle strength is one of the key for easier engagement in activities like walking or stair-climbing.

Effects of sedentary behaviour and long-term regular Tai Chi exercise on dynamic stability control during gait initiation in older women

Background: Sedentary behaviour has been associated with an increased risk of falls among older adults. Although gait initiation (GI) is a promising tool used to assess fall risk, it has yet to be quantitatively evaluated for dynamic stability in sedentary populations. Tai Chi exercise is believed to be effective in preventing falls in older adults, but its effect on GI stability has not been quantified. This study aims to compare the stability of GI in sedentary older individuals versus those who are long-term Tai Chi exercisers by using a quantitative approach.Methods: This study included 17 sedentary older women without exercise habits (age: 65.59 ± 3.66 years, average daily sitting time: 8.735 ± 1.847 h/day) and 19 older women who regularly engage in Tai Chi exercise (age: 65.58 ± 3.63 years, years of exercise: 9.84 ± 3.48 years). Every participant underwent five trials of self-paced GI walking tests. Eight cameras and four force plates were used to obtain kinematic and kinetic parameters. The trajectory of the centre of mass (CoM) and the position of the foot placement were recorded. The anterior–posterior (A-P) and medio–lateral (M-L) dynamic stability at the onset and end moments of the single-legged support was calculated using CoM and gait spatiotemporal parameters. The stepping dynamic stability and foot placement positions of both groups were compared.Results: The Tai Chi group had greater stability in the M-L directions at the swing leg’s toe-off moment and in the M-L and A-P directions at the heel-strike moment, as well as significantly larger step length, step width and step speed during locomotion than sedentary older women. However, the stability in the A-P directions at the swing leg’s toe-off moment and the foot inclination angle was not statistically different between the two groups.Conclusion: Long-term regular Tai Chi exercise can enhance the dynamic stability of GI in older women, and effectively improve their foot placement strategy during GI. The findings further confirm the negative effect of sedentary on the stability control of older women and the positive role of Tai Chi in enhancing their gait stability and reducing the risk of falls.

The effects of L-DOPA on gait abnormalities in a unilateral 6-OHDA rat model of Parkinson's disease

Parkinson's Disease (PD) is a neurodegenerative movement disorder characterized by dopamine (DA) cell loss in the substantia nigra pars compacta (SNc). As PD progresses, patients display disruptions in gait such as changes in posture, bradykinesia, and shortened stride. DA replacement via L-DOPA alleviates many PD symptoms, though its effects on gait are not well demonstrated. This study aimed to assess the relationship between DA lesion, gait, and deficit-induced reversal with L-DOPA. To do so, Sprague–Dawley rats (N = 25, 14 males, 11 females) received unilateral medial forebrain bundle (MFB) DA lesions with 6-hydroxydopamine (6-OHDA). An automated gait analysis system assessed spatiotemporal gait parameters pre- and post-lesion, and after various doses of L-DOPA (0, 3, or 6 mg/kg; s.c.). The forepaw adjusting steps (FAS) test was implemented to evaluate lesion efficacy while the abnormal involuntary movements (AIMs) scale monitored the emergence of L-DOPA-induced dyskinesia (LID). High performance liquid chromatography (HPLC) assessed changes in brain monoamines on account of lesion and treatment. Results revealed lesion-induced impairments in gait, inclusive of max-contact area and step-sequence alterations that were not reversible with L-DOPA. However, the emergence of AIMs were observed at higher doses. Post-mortem, 6-OHDA lesions induced a loss of striatal DA and norepinephrine (NE), while prefrontal cortex (PFC) displayed noticeable reduction in NE but not DA. Our findings indicate that hemiparkinsonian rats display measurable gait disturbances similar to PD patients that are not rescued by DA replacement. Furthermore, non-DA mechanisms such as attention-related NE in PFC may contribute to altered gait and may constitute a novel target for its treatment.

Stroke walking and balance characteristics via principal component analysis

Balance impairment is associated gait dysfunction with several quantitative spatiotemporal gait parameters in patients with stroke. However, the link between balance impairments and joint kinematics during walking remains unclear. Clinical assessments and gait measurements using motion analysis system was conducted in 44 stroke patients. This study utilised principal component analysis to identify key joint kinematics characteristics of patients with stroke during walking using average joint angles of pelvis and bilateral lower limbs in every gait-cycle percentile related to balance impairments. Reconstructed kinematics showed the differences in joint kinematics in both paretic and nonparetic lower limbs that can be distinguished by balance impairment, particularly in the sagittal planes during swing phase. The impaired balance group exhibited greater joint variability in both the paretic and nonparetic limbs in the sagittal plane during entire gait phase and during terminal swing phase respectively compared with those with high balance scores. This study provides a more comprehensive understanding of stroke hemiparesis gait patterns and suggests considering both nonparetic and paretic limb function, as well as bilateral coordination in clinical practice. Principal component analysis can be a useful assessment tool to distinguish differences in balance impairment and dynamic symmetry during gait in patients with stroke.

Shoe sole impedes leg muscle activation and impairs dynamic balance responding to a standing-slip

The shoe sole is identified as a fall risk factor since it may impede the afferent information about the outside world collected by the plantar sensory units. However, no study has directly quantified how the shoe sole compromises body balance and increases fall risk. This study aimed to inspect how the sole affects human balance after an unexpected standing-slip. It was hypothesized that individuals wearing the sole, relative to their barefoot counterparts, would exhibit 1) more impaired stability and 2) disrupted lower limb muscle activation following a standing-slip. Twenty young adults were evenly randomized into two groups: soled and barefoot. The soled group wore a pair of customized 10-mm thick soles, while the other group was bare-footed. Full-body kinematics and leg muscle electromyography (EMG) were collected during a standardized and unexpected standing-slip. The EMG electrodes were placed on the tibialis anterior, gastrocnemius, rectus femoris, and biceps femoris bilaterally. Dynamic stability, spatiotemporal gait parameters, and the EMG latency of the leg muscles were compared between groups. The sole impeded the initiation of the recovery step possibly because it interfered with the accurate detection of the external perturbation and subsequently activated the leg muscles later in the soled group than in the barefoot group. As a result, individuals in the soled group experienced a longer slip distance and were more unstable than the barefoot group at the recovery foot liftoff. The findings of this study could augment our understanding of how the shoe sole impairs body balance and increases the fall risk.

Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study.

Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies. The aim of this study was to validate gait sequence (GS) detection algorithms developed for the wrist position against reference data acquired in a real-world context. In addition, this study aimed to compare the performance of algorithms applied to the wrist position to those applied to lower back-worn inertial sensors. Participants with Parkinson disease, multiple sclerosis, proximal femoral fracture (hip fracture recovery), chronic obstructive pulmonary disease, and congestive heart failure and healthy older adults (N=83) were monitored for 2.5 hours in the real-world using inertial sensors on the wrist, lower back, and feet including pressure insoles and infrared distance sensors as reference. In total, 10 algorithms for wrist-based gait detection were validated against a multisensor reference system and compared to gait detection performance using lower back-worn inertial sensors. The best-performing GS detection algorithm for the wrist showed a mean (per disease group) sensitivity ranging between 0.55 (SD 0.29) and 0.81 (SD 0.09) and a mean (per disease group) specificity ranging between 0.95 (SD 0.06) and 0.98 (SD 0.02). The mean relative absolute error of estimated walking time ranged between 8.9% (SD 7.1%) and 32.7% (SD 19.2%) per disease group for this algorithm as compared to the reference system. Gait detection performance from the best algorithm applied to the wrist inertial sensors was lower than for the best algorithms applied to the lower back, which yielded mean sensitivity between 0.71 (SD 0.12) and 0.91 (SD 0.04), mean specificity between 0.96 (SD 0.03) and 0.99 (SD 0.01), and a mean relative absolute error of estimated walking time between 6.3% (SD 5.4%) and 23.5% (SD 13%). Performance was lower in disease groups with major gait impairments (eg, patients recovering from hip fracture) and for patients using bilateral walking aids. Algorithms applied to the wrist position can detect GSs with high performance in real-world environments. Those periods of interest in real-world recordings can facilitate gait parameter extraction and allow the quantification of gait duration distribution in everyday life. Our findings allow taking informed decisions on alternative positions for gait recording in clinical studies and public health. ISRCTN Registry 12246987; https://www.isrctn.com/ISRCTN12246987. RR2-10.1136/bmjopen-2021-050785.

Computer Vision System Based on the Analysis of Gait Features for Fall Risk Assessment in Elderly People

Up to 30% of people over the age of 60 are at high risk of falling, which can cause injury, aggravation of pre-existing conditions, or even death, with up to 684,000 fatal falls reported annually. This is due to the difficult task of establishing a preventive system for the care of the elderly, both in the hospital environment and at home. Therefore, this work proposes the development of an intelligent vision system that uses a novel methodology to infer fall risk from the analysis of kinetic and spatiotemporal gait parameters. In general, each patient is assessed using the Tinetti scale. Then, the computer vision system estimates the biomechanics of walking and obtains gait features, such as stride length, cadence, period, and range of motion. Subsequently, this information serves as input to an artificial neural network that diagnoses the risk of falling. Ninety-six participants took part in the study. The system’s performance was 99.1% accuracy, 94.4% precision, 96.9% recall, 99.4% specificity, and 95.5% F1-Score. Thus, the proposed system can evaluate the fall risk assessment, which could benefit clinics, hospitals, and even homes by allowing them to assess in real time whether a person is at high risk of falling to provide timely assistance.

Brain Networks Modulation during Simple and Complex Gait: A "Mobile Brain/Body Imaging" Study.

Walking encompasses a complex interplay of neuromuscular coordination and cognitive processes. Disruptions in gait can impact personal independence and quality of life, especially among the elderly and neurodegenerative patients. While traditional biomechanical analyses and neuroimaging techniques have contributed to understanding gait control, they often lack the temporal resolution needed for rapid neural dynamics. This study employs a mobile brain/body imaging (MoBI) platform with high-density electroencephalography (hd-EEG) to explore event-related desynchronization and synchronization (ERD/ERS) during overground walking. Simultaneous to hdEEG, we recorded gait spatiotemporal parameters. Participants were asked to walk under usual walking and dual-task walking conditions. For data analysis, we extracted ERD/ERS in α, β, and γ bands from 17 selected regions of interest encompassing not only the sensorimotor cerebral network but also the cognitive and affective networks. A correlation analysis was performed between gait parameters and ERD/ERS intensities in different networks in the different phases of gait. Results showed that ERD/ERS modulations across gait phases in the α and β bands extended beyond the sensorimotor network, over the cognitive and limbic networks, and were more prominent in all networks during dual tasks with respect to usual walking. Correlation analyses showed that a stronger α ERS in the initial double-support phases correlates with shorter step length, emphasizing the role of attention in motor control. Additionally, β ERD/ERS in affective and cognitive networks during dual-task walking correlated with dual-task gait performance, suggesting compensatory mechanisms in complex tasks. This study advances our understanding of neural dynamics during overground walking, emphasizing the multidimensional nature of gait control involving cognitive and affective networks.

Unveiling the Unpredictable in Parkinson’s Disease: Sensor-Based Monitoring of Dyskinesias and Freezing of Gait in Daily Life

Background: Dyskinesias and freezing of gait are episodic disorders in Parkinson’s disease, characterized by a fluctuating and unpredictable nature. This cross-sectional study aims to objectively monitor Parkinsonian patients experiencing dyskinesias and/or freezing of gait during activities of daily living and assess possible changes in spatiotemporal gait parameters. Methods: Seventy-one patients with Parkinson’s disease (40 with dyskinesias and 33 with freezing of gait) were continuously monitored at home for a minimum of 5 days using a single wearable sensor. Dedicated machine-learning algorithms were used to categorize patients based on the occurrence of dyskinesias and freezing of gait. Additionally, specific spatiotemporal gait parameters were compared among patients with and without dyskinesias and/or freezing of gait. Results: The wearable sensor algorithms accurately classified patients with and without dyskinesias as well as those with and without freezing of gait based on the recorded dyskinesias and freezing of gait episodes. Standard spatiotemporal gait parameters did not differ significantly between patients with and without dyskinesias or freezing of gait. Both the time spent with dyskinesias and the number of freezing of gait episodes positively correlated with the disease severity and medication dosage. Conclusions: A single inertial wearable sensor shows promise in monitoring complex, episodic movement patterns, such as dyskinesias and freezing of gait, during daily activities. This approach may help implement targeted therapeutic and preventive strategies for Parkinson’s disease.

The Effect of a Cognitive Dual Task on Gait Parameters among Healthy Young Adults with Good and Poor Sleep Quality: A Cross-Sectional Analysis.

Background: Sleep quality is known to affect automatic and executive brain functions such as gait control and cognitive processing. This study aimed to investigate the effect of dual tasks on gait spatiotemporal parameters among young adults with good and poor sleep quality. Methods: In total, 65 young adults with a mean age of 21.1 ± 2.5 were assessed for gait analysis during single-task and dual-task conditions. The participants' sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) and gait was assessed using the BTS Gaitlab System. The participants were asked to walk at natural speed as a single-task condition, followed by walking while performing a cognitive task as a dual-task condition. The parameters assessed included the gait velocity (m/s), cadence (steps/min), step width (m), and stride length (m). The dual-task cost (DTC) on each gait parameter was calculated. The Mann-Whitney U test was used to compare the differences in the DTC on gait variables between the good and poor sleep quality groups and the Spearman correlation test was used to assess the correlation between total PSQI scores and the DTC. Results: At a significance level of p < 0.05, a significant difference in cadence between the two sleep quality groups was observed, in addition to a positive correlation between sleep quality and the DTC effect on gait mean velocity, cadence, and stride length. Our findings also revealed a greater DTC in participants with poorer sleep quality. Conclusions: These findings contribute to our perception of the significance of sleep quality in gait performance while multitasking in younger populations.

Movement strategies during obstacle crossing in people with Parkinson disease: A systematic review with meta-analysis.

Navigating obstacles involves adjusting walking patterns, particularly when stepping over them. This task may be particularly challenging for people with Parkinson disease (PD) for several reasons.This review aims to compare the spatiotemporal gait parameters of people with and without PD while stepping over obstacles. A systematic literature search was conducted in six databases (PubMed, Scopus, Web of Science, EBSCO, Embase, and SciELO) from inception to September 2023. Studies were selected that evaluated gait parameters of people with and without PD while walking over obstacles. Two independent researchers evaluated the eligibility and extracted gait parameters during obstacle crossing. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Heterogeneity was assessed using I2-tests. Random effects models were determined for effect sizes as standardized mean differences (SMD). Twenty-five studies were included in the review and 17 in the meta-analysis. Most of the studies (58%) showed a low risk of bias. People with PD exhibit a shorter step when landing after crossing an obstacle (SMD = -0.50 [-0.69 to -0.31]). Compared to people without PD, people with PD also widen their support base (SMD = 0.27 [0.07-0.47]) and reduce gait velocity (SMD = -0.60 [-0.80 to -0.39]) when crossing the obstacle. People with PD adopt a more conservative motor behavior during obstacle crossing than those without PD, with a shorter step length when landing after crossing an obstacle, greater step width and lower crossing speed.

Ubiquitous Gait Analysis through Footstep-Induced Floor Vibrations.

Quantitative analysis of human gait is critical for the early discovery, progressive tracking, and rehabilitation of neurological and musculoskeletal disorders, such as Parkinson's disease, stroke, and cerebral palsy. Gait analysis typically involves estimating gait characteristics, such as spatiotemporal gait parameters and gait health indicators (e.g., step time, length, symmetry, and balance). Traditional methods of gait analysis involve the use of cameras, wearables, and force plates but are limited in operational requirements when applied in daily life, such as direct line-of-sight, carrying devices, and dense deployment. This paper introduces a novel approach for gait analysis by passively sensing floor vibrations generated by human footsteps using vibration sensors mounted on the floor surface. Our approach is low-cost, non-intrusive, and perceived as privacy-friendly, making it suitable for continuous gait health monitoring in daily life. Our algorithm estimates various gait parameters that are used as standard metrics in medical practices, including temporal parameters (step time, stride time, stance time, swing time, double-support time, and single-support time), spatial parameters (step length, width, angle, and stride length), and extracts gait health indicators (cadence/walking speed, left-right symmetry, gait balance, and initial contact types). The main challenge we addressed in this paper is the effect of different floor types on the resultant vibrations. We develop floor-adaptive algorithms to extract features that are generalizable to various practical settings, including homes, hospitals, and eldercare facilities. We evaluate our approach through real-world walking experiments with 20 adults with 12,231 labeled gait cycles across concrete and wooden floors. Our results show 90.5% (RMSE 0.08s), 71.3% (RMSE 0.38m), and 92.3% (RMSPE 7.7%) accuracy in estimating temporal, spatial parameters, and gait health indicators, respectively.

Square-stepping exercise in older inpatients in early geriatric rehabilitation. A randomized controlled pilot study

BackgroundPreservation of mobility and fall prevention have a high priority in geriatric rehabilitation. Square-Stepping Exercise (SSE) as an evaluated and standardized program has been proven to be an effective training for older people in the community setting to reduce falls and improve subjectively perceived health status. This randomized controlled trial (RCT), for the first time, examines SSE in the context of inpatient early geriatric rehabilitation compared to conventional physiotherapy (cPT).MethodsData were collected in a general hospital in the department of acute geriatric care at admission and discharge. Fifty-eight inpatients were randomized to control (CG, n = 29) or intervention groups (IG, n = 29). CG received usual care with cPT five days per week during their hospital stay. For the IG SSE replaced cPT for at least six sessions, alternating with cPT. Physical function was measured with the Short Physical Performance Battery (SPPB) and Timed “Up & Go” (TUG). Gait speed was measured over a distance of 10 m. In a subgroup (n = 17) spatiotemporal gait parameters were analyzed via a GAITRite® system.ResultsBoth the SPPB total score improved significantly (p = < 0.001) from baseline to discharge in both groups, as did the TUG (p < 0.001). In the SPPB Chair Rise both groups improved with a significant group difference in favor of the IG (p = 0.031). For both groups gait characteristics improved: Gait speed (p = < 0.001), walk ratio (p = 0.011), step length (p = < 0.001), stride length (p = < 0.001) and double support (p = 0.009). For step length at maximum gait speed (p = 0.054) and stride length at maximum gait speed (p = 0.060) a trend in favor of the IG was visible.ConclusionsSSE in combination with a reduced number of sessions of cPT is as effective as cPT for inpatients in early geriatric rehabilitation to increase physical function and gait characteristics. In the Chair Rise test SSE appears to be superior. These results highlight that SSE is effective, and may serve as an additional component for cPT for older adults requiring geriatric acute care.Trial RegistrationDRKS00026191.

The effects of an upper limb exoskeleton on gait performance and stability

Upper limb exoskeletons (ULEs) are emerging as workplace tools to alleviate workload and prevent work-related musculoskeletal disorders during lifting tasks. However, their introduction raises concerns about potential instability and increased fall risk for workers. This study investigates gait performance and stability parameters implications of ULE use. Fifteen participants performed a carrying task with different loads (0, 5, 10, 15 kg), both with and without the use of an ULE. Spatiotemporal gait parameters, Required Coefficient of Friction (RCoF), Minimum Foot Clearance (MFC), and Margin of Stability (MoS) were analysed. The findings indicate that while the ULE does not significantly alter most gait parameters or slip risk, it may negatively impact trip risk. Furthermore, while mediolateral stability remains unaffected, anteroposterior stability is compromised by ULE usage. These insights are critical for ensuring the safe implementation of ULEs in occupational settings.

Exploration and demonstration of explainable machine learning models in prosthetic rehabilitation-based gait analysis.

Quantitative gait analysis is important for understanding the non-typical walking patterns associated with mobility impairments. Conventional linear statistical methods and machine learning (ML) models are commonly used to assess gait performance and related changes in the gait parameters. Nonetheless, explainable machine learning provides an alternative technique for distinguishing the significant and influential gait changes stemming from a given intervention. The goal of this work was to demonstrate the use of explainable ML models in gait analysis for prosthetic rehabilitation in both population- and sample-based interpretability analyses. Models were developed to classify amputee gait with two types of prosthetic knee joints. Sagittal plane gait patterns of 21 individuals with unilateral transfemoral amputations were video-recorded and 19 spatiotemporal and kinematic gait parameters were extracted and included in the models. Four ML models-logistic regression, support vector machine, random forest, and LightGBM-were assessed and tested for accuracy and precision. The Shapley Additive exPlanations (SHAP) framework was applied to examine global and local interpretability. Random Forest yielded the highest classification accuracy (98.3%). The SHAP framework quantified the level of influence of each gait parameter in the models where knee flexion-related parameters were found the most influential factors in yielding the outcomes of the models. The sample-based explainable ML provided additional insights over the population-based analyses, including an understanding of the effect of the knee type on the walking style of a specific sample, and whether or not it agreed with global interpretations. It was concluded that explainable ML models can be powerful tools for the assessment of gait-related clinical interventions, revealing important parameters that may be overlooked using conventional statistical methods.

The Combined Influence of Infant Carrying Method and Motherhood on Gait Mechanics.

Postpartum mothers are susceptible to lumbopelvic pain which may be exacerbated by loading, like carrying their infant in arms and with baby carriers. Nulliparous women carrying infant mannequins may biomechanically mimic mother-infant dyad, but this has not been studied. The purpose of our study was to investigate biomechanical differences of 10 mothers carrying their infants and 10 nulliparous women carrying infant mannequins under 3 gait conditions: carrying nothing, carrying in arms, and carrying in a baby carrier (babywearing). Spatiotemporal gait parameters, peak ground reaction forces and impulses, and lower extremity and trunk kinematics were collected using motion capture and force plates and compared using a mixed 2 × 3 (parity × condition) analysis of variance (α ≤ .05). The largest differences occurred between carrying conditions: carrying in arms or babywearing increased vertical and anteroposterior ground reaction forces, trunk extension, ankle dorsiflexion, and hip and knee flexion. Kinematic differences were identified between arms and babywearing conditions. Together this suggests alterations in joint loading for both groups. Our study also contributes a novel understanding of postpartum health by demonstrating alterations in step time, anterior forces, and ankle and knee mechanics, suggesting that during gait, mothers carrying their own infants choose different propulsive strategies than nulliparous women carrying mannequins.

Comparison of Spatiotemporal Gait Parameters in Indoor and Outdoor Walking Among Older Adults

Comparison of Spatiotemporal Gait Parameters in Indoor and Outdoor Walking Among Older Adults

The Effect of a New Generation of Ankle Foot Orthoses on Sloped Walking in Children with Hemiplegia Using the Gait Real Time Analysis Interactive Lab (GRAIL).

Cerebral palsy poses challenges in walking, necessitating ankle foot orthoses (AFOs) for stability. Gait analysis, particularly on slopes, is crucial for effective AFO assessment. The study aimed to compare the performance of commercially available AFOs with a new sports-specific AFO in children with hemiplegic cerebral palsy and to assess the effects of varying slopes on gait. Eighteen participants, aged 6-11, with hemiplegia, underwent gait analysis using GRAIL technology. Two AFO types were tested on slopes (uphill +10 deg, downhill -5 deg, level-ground). Kinematic, kinetic, and spatiotemporal parameters were analyzed. The new AFO contributed to significant changes in ankle dorsi-plantar-flexion, foot progression, and trunk and hip rotation during downhill walking. Additionally, the new AFO had varied effects on spatiotemporal gait parameters, with an increased stride length during downhill walking. Slope variations significantly influenced the kinematics and kinetics. This study provides valuable insights into AFO effectiveness and the impact of slopes on gait in hemiplegic cerebral palsy. The findings underscore the need for personalized interventions, considering environmental factors, and enhancing clinical and research approaches for improving mobility in cerebral palsy.

Motion acquisition of gait characteristics one week after total hip arthroplasty: a factor analysis

IntroductionClinical gait analysis can be used to evaluate the recovery process of patients undergoing total hip arthroplasty (THA). The postoperative walking patterns of these patients can be significantly influenced by the choice of surgical approach, as each procedure alters distinct anatomical structures. The aim of this study is twofold. The first objective is to develop a gait model to describe the change in ambulation one week after THA. The secondary goal is to describe the differences associated with the surgical approach.Materials and methodsThirty-six patients undergoing THA with lateral (n = 9), anterior (n = 15), and posterior (n = 12) approaches were included in the study. Walking before and 7 days after surgery was recorded using a markerless motion capture system. Exploratory Factor Analysis (EFA), a data reduction technique, condensed 21 spatiotemporal gait parameters to a smaller set of dominant variables. The EFA-derived gait domains were utilized to study post-surgical gait variations and to compare the post-surgical gait among the three groups.ResultsFour distinct gait domains were identified. The most pronounced variation one week after surgery is in the Rhythm (gait cycle time: +32.9%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$+32.9\\mathrm{\\%}$$\\end{document}), followed by Postural control (step width: +27.0%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$+27.0\\mathrm{\\%}$$\\end{document}), Phases (stance time: +11.0%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$+11.0\\%$$\\end{document}), and Pace (stride length: − 9.3%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$9.3\\%$$\\end{document}). In postsurgical walking, Phases is statistically significantly different in patients operated with the posterior approach compared to lateral (p-value = 0.017) and anterior (p-value = 0.002) approaches. Furthermore, stance time in the posterior approach group is significantly lower than in healthy individuals (p-value < 0.001).ConclusionsThis study identified a four-component gait model specific to THA patients. The results showed that patients after THA have longer stride time but shorter stride length, wider base of support, and longer stance time, although the posterior group had a statistically significant shorter stance time than the others. The findings of this research have the potential to simplify the reporting of gait outcomes, reduce redundancy, and inform targeted interventions in regards to specific gait domains.

Effect of levodopa on pathological gait in Dravet syndrome: A randomized crossover trial using three-dimensional gait analysis.

Individuals with Dravet syndrome (DS) exhibit progressive gait disturbance. No quantitative studies have been conducted to evaluate the effectiveness of medication for gait disturbance. Therefore, the aim of this study was to evaluate the effectiveness of levodopa for pathological gait in people with DS using three-dimensional gait analysis (3DGA). Nine individuals with DS, ages 6-20 years, participated in a crossover study of levodopa and were randomly assigned to the levodopa precedence or no levodopa precedence group. Levodopa/carbidopa hydrate was prescribed at a dose of 5 mg/kg/day (body weight <60 kg) or 300 mg/day (body weight ≥60 kg). The medication was taken for 4-6 weeks (4-week washout period). 3DGA was performed three times before the study, with and without levodopa. A mixed-effects model was used to evaluate the effectiveness of levodopa. The primary outcome was the change in the Gait Deviation Index (GDI). In addition, spatiotemporal gait parameters, 6-minute walking distance (6MD), and balance were evaluated. The correlation between the effectiveness of levodopa and age or gait performance before starting levodopa was analyzed. Levodopa improved the GDI by 4.2 points, (p = .029), 6MD by 52 m (p = .002), and balance test result by 4.1 mm (p = .011) in participants with DS. No severe adverse events were observed, with the exception of one participant, who exhibited fever and consequently stopped taking levodopa. Levodopa was more effective in younger participants with a higher baseline gait performance. Our randomized crossover trial showed that levodopa has the potential to improve gait disturbance in people with DS.