Do Three Different Passive Assessments of Quadriceps Spasticity Relate to the Functional Activity of Walking for Children Diagnosed with Cerebral Palsy?

A stiff-knee gait pattern is frequently associated with several impairments including quadriceps spasticity in children diagnosed with cerebral palsy (CP). The relationship of clinical measures of quadriceps spasticity and the stiff-knee gait pattern in children diagnosed with CP has not been well established. Therefore, the purpose of this study was to determine the ability of clinical measures of quadriceps spasticity (modified Ashworth scale [MAS], Ely tests, and pendulum test) to categorize a stiff-knee gait pattern in children with CP. Children were categorized as having a stiff-knee gait pattern based on kinematic and EMG gait data. Results of a logistic regression model revealed that the only significant measure was A1 of the pendulum test. Discriminant analysis functions were used to predict group membership (stiff-knee, not stiff-knee gait pattern) for each measure. The A1 of the pendulum test demonstrated the highest classification accuracy and the highest sensitivity compared to the other measures. Therefore, a negative pendulum test (indicated by an A1 value of 45 degrees or more) is more useful for ruling out a stiff-knee gait pattern compared to the other clinical measures

Automatic Gait Pattern Selection for Legged Robots

An important issue when synthesizing legged locomotion plans is the combinatorial complexity that arises from gait pattern selection. Though it can be defined manually, the gait pattern plays an important role in the feasibility and optimality of a motion with respect to a task. Replacing human intuition with an automatic and efficient approach for gait pattern selection would allow for more autonomous robots, responsive to task and environment changes. To this end, we propose the idea of building a map from task to gait pattern selection for given environment and performance objective. Indeed, we show that for a 2D half-cheetah model and a quadruped robot, a direct mapping between a given task and an optimal gait pattern can be established. We use supervised learning to capture the structure of this map in a form of gait regions. Furthermore, we propose to construct a warm-starting trajectory for each gait region. We empirically show that these warm-starting trajectories improve the convergence speed of our trajectory optimization problem up to 60 times when compared with random initial guesses. Finally, we conduct experimental trials on the ANYmal robot to validate our method.</p

Original investigation correlated joint fluctuations can influence the selection of steady state gait patterns in the elderly

This investigation utilized a Markov model to investigate the relationship of correlated lower extremity joint fluctuations and the selection of a steady state gait pattern in the young and elderly. Our model simulated the neuromuscular system by predicting the behavior of the joints for the next gait cycle based on the behavior exhibited in the preceding gait cycles. Such dependencies in the joint fluctuations have been noted previously in the literature. We speculated that compared to the young model, the characteristics of the correlated fluctuations in the elderly model would result in the selection of a different steady state gait pattern. The results of our simulation support the notion that correlated fluctuations in the joint kinematics influence the selection of a steady state gait pattern. The steady state gait pattern for the elderly model was dependent the ankle and hip. Conversely, the steady state gait pattern for the young control model was dependent on the behavior of the knee and hip. Based on our model, we suggested that the altered steady state gait patterns observed in the elderly may be due to an altered neuromuscular memory of prior joint behaviors

Gait characteristics of subjects with chronic fatigue syndrome and controls at self-selected and matched velocities

Background: Gait abnormalities have been reported in individuals with Chronic Fatigue Syndrome (CFS) however no studies exist to date investigating the kinematics of individuals with CFS in over-ground gait. The aim of this study was to compare the over-ground gait pattern (sagittal kinematics and temporal and spatial) of individuals with CFS and control subjects at their self-selected and at matched velocities. Methods: Twelve individuals with CFS and 12 matched controls participated in the study. Each subject walked along a 7.2 m walkway three times at each of three velocities: self-selected, relatively slow (0.45 ms-1) and a relatively fast (1.34 ms-1). A motion analysis system was used to investigate the sagittal plane joint kinematics and temporal spatial parameters of gait. Results: At self-selected velocity there were significant differences between the two groups for all the temporal and spatial parameters measured, including gait velocity (P = 0.002). For the kinematic variables the significant differences were related to both ankles during swing and the right ankle during stance. At the relatively slower velocity the kinematic differences were replicated. However, the step distances decreased in the CFS population for the temporal and spatial parameters. When the gait pattern of the individuals with CFS at the relatively fast walking velocity (1.30 ± 0.24 ms-1) was compared to the control subjects at their self-selected velocity (1.32 ± 0.15 ms-1) the gait pattern of the two groups was very similar, with the exception of both ankles during swing. Conclusion: The self-selected gait velocity and/or pattern of individuals with CFS may be used to monitor the disease process or evaluate therapeutic intervention. These differences may be a reflection of the relatively low self-selected gait velocity of individuals with CFS rather than a manifestation of the condition itself

Towards dynamically consistent real-time gait pattern generation for full-size humanoid robots

We propose a two-stage gait pattern generation scheme for the full-scale humanoid robots, that considers the dynamics of the system throughout the process. The fist stage is responsible for generating semi-dynamically consistent step position and step time information, while the second stage incorporated with multi-body dynamics system is responsible for generation of gait pattern that is feasible and stable on the full-scale multi-degree-of-freedom humanoid robot. The approach allows for very rapid gait pattern regeneration during the swing phase of motion and includes information about present dynamic state when regenerating the new pattern. The paper contains description of a developed method, as well as experimental results proving its effectiveness

Feature extraction from ear-worn sensor data for gait analysis

Gait analysis has a significant role in assessing human's walking pattern. It is generally used in sports science for understanding body mechanics, and it is also used to monitor patients' neuro-disorder related gait abnormalities. Traditional marker-based systems are well known for tracking gait parameters for gait analysis, however, it requires long set up time therefore very difficult to be applied in everyday realtime monitoring. Nowadays, there is ever growing of interest in developing portable devices and their supporting software with novel algorithms for gait pattern analysis. The aim of this research is to investigate the possibilities of novel gait pattern detection algorithms for accelerometer-based sensors. In particular, we have used e-AR sensor, an ear-worn sensor which registers body motion via its embedded 3-D accelerom-eter. Gait data was given semantic annotation using pressure mat as well as real-time video recording. Important time stamps within a gait cycle, which are essential for extracting meaningful gait parameters, were identified. Furthermore, advanced signal processing algorithm was applied to perform automatic feature extraction by signal decomposition and reconstruction. Analysis on real-word data has demonstrated the potential for an accelerometer-based sensor system and its ability to extract of meaningful gait parameters

Quantitative Effects of Repeated Muscle Vibrations on Gait Pattern in a 5-Year-Old Child with Cerebral Palsy

Objective. To investigate quantitatively and objectively the effects of repeated muscle vibration (rMV) of triceps surae on the gait pattern in a 5-year-old patient with Cerebral Palsy with equinus foot deformity due to calf spasticity. Methods. The patient was assessed before and one month after the rMV treatment using Gait Analysis. Results. rMV had positive effects on the patient's gait pattern, as for spatio-temporal parameters (the stance duration and the step length increased their values after the treatment) and kinematics. The pelvic tilt reduced its anteversion and the hip reduced the high flexion evidenced at baseline; the knee and the ankle gained a more physiological pattern bilaterally. The Gillette Gait Index showed a significant reduction of its value bilaterally, representing a global improvement of the child's gait pattern. Conclusions. The rMV technique seems to be an effective option for the gait pattern improvement in CP, which can be used also in very young patient. Significant improvements were displayed in terms of kinematics at all lower limb joints, not only at the joint directly involved by the treatment (i.e., ankle and knee joints) but also at proximal joints (i.e., pelvis and hip joint)

Hubungan Antara Perubahan Postur Tipe Fleksi Dengan Pola Jalan Pada Lanjut Usia

Background: The prevalence of changes posture in elderly patients is 20% to 40% that can be caused by a decrease in bone density due to the aging process, which indirectly alters the shape of the spinal curve. Posture changes resulted in disruption of activities especially on gait pattern. Gait disorders in the elderly with age above 65 years may reach 20-40% and in the elderly with age above 85 years may experience interference gait pattern of 40-50%. So the elderly with type flexed posture changes significantly changing the physical size and gait. Objective: Knowing the relationship between posture changes the type of flexion with the gait pattern (stride length, step speed, cadence and mobility and balance runs) in elderly patients. Methods: An observational study with cross sectional design to examine the relationship between posture changes the type of flexion with the gait pattern in the elderly, with a sample size of 72 people. Using a univariate data analysis techniques with frequency distribution table and bivariate test by using chi - square. Results: The relationship between changes in posture type flexion with the stride length (P-value = 0.001) correlation between changes in posture with the step speed (P-value = 0.127) correlation between changes in posture with cadence (P-value = 0.000) correlation between changes in posture with mobility and balance runs (P-value = 0.001) Conclusion: There is a relationship between changes in the type flexed posture with stride length, there is no relationship between the type of flexion posture changes with step speed there is a relationship between changes in the type flexed posture with cadence and there is a relationship between changes in posture type of flexion with mobility and balance to walk. Keywords: Posture, Gait pattern, Elderl