Friction in hip bearings under continuous normal walking conditions: Influence of swing phase load and patient weight
Robert SonntagLoay Al-SalehiSteffen BraunTherese BormannSebastian JaegerStefan SchroederDaniel HeitzmannJan Philippe Kretzer
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Friction torque
Gait cycle
Objective:To find the walking feature of the hemiplegia by the quantitative analysis of phases and cycle in hemiplegic gait after stroke.Methods: To compare the difference of the gait cycle between 30 hemiplegic patients and 30 healthy people by using Wall and Ryuichi's gait analyses methods. Results: The period of support of affected side in experiment group was significantly shorter than that of unaffected side (P0.01). Meanwhile, the sway period of affected side was remarkably longer than that of unaffected side (P0.01). There were also notable differences in the phase of double support and gait cycle between experiment group and control group(P0.01). Conclusion: The study indicates that the shorter single support time during the gait cycle in patients is responsible for the abnormal walking velocity , awful gait and decreased ability of walking. It suggests that increasing single support training is an effective way for improving the patients'gait.
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In this paper we will show that using Principle Component Analysis (PCA) on accelerometer based gait data will give a large improvement on the performance. On a dataset of 720 gait samples (60 volunteers and 12 gait samples per volunteer) we achieved an EER of 1.6% while the best result so far, using the Average Cycle Method (ACM), gave a result of nearly 6%. This tremendous increase makes gait recognition a viable method in commercial applications in the near future.
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Ground reaction force
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Gait Disturbance
Etiology
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In gait recognition, which has been recently regarded as a biometric recognition tool, proposed approaches assume that an individual is observed for at least one gait cycle. However, in reality, there might be available only a few frames of full gait cycle of a subject due to occlusion. Therefore, gait recognition systems would fail in these scenarios. In this paper, we propose a method to tackle this problem by proposing a gait recognition algorithm from an incomplete gait cycle information. We achieve this by 1) creating an incomplete Energy Image (GEI) from a few available silhouettes of a subject and 2) reconstructing the complete GEI from incomplete GEI using a deep auto-encoder. The experimental results on a public gait dataset demonstrate the validity of the proposed method.
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In the advanced stage of Parkinson's disease (PD), motor fluctuation is a frequent and a disabling problem. Despite its importance, motor fluctuation has received little scientific analysis probably due to limitation in objective assessment. Here, we focused on gait disorders to estimate motor fluctuation in daily activities.Using a new device, the portable gait rhythmogram, we recorded gait rhythm continuously over 24 hours in 22 patients with PD and in 11 normal controls, for quantitative evaluation of motor fluctuation. The duration of one gait cycle was measured.Continuous 24-hour recording identified changes in gait rhythm, which correlated with fluctuation of PD symptoms. Different motor fluctuations were observed; a shift to a faster gait cycle was noted in patients with short-step walking, festination or freezing of gait, whereas a shift to a slower gait cycle was observed in patients with bradykinesia or instability.Characterization of motor fluctuation using this device could help in the selection of appropriate anti-PD medications.
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Aim: To explore one of the temporal characteristic of running gait (Gait Cycle Duration) in children and determine its relationship with the selected body characteristics
Methodology: Twenty school going children of 5 years age consisting of both genders were selected for the study. To obtain the required data, an experimental setup was designed consisting of caliberated running path and a cannon camcorder Legria SF10 operating at shutter speed of 1/2000 and frame rate of 50 Hz. The obtained video data was analyzed using Silicocoach7 motion analysis software. The statistical analysis was done by SPSSv 17.0 to determine the relationship of gait cycle duration with the selected body characteristics.
Results: No significant relationship was found between the gait cycle duration and body characteristics, however a striking feature got extracted that the gait cycle duration of 5 years old children was shorter than that of adults.
Conclusion: The results concluded from the study could be of great use to clinicians to assess the gait maturation or abnormality in the gait of children. Further, the changes in the gait cycle duration could reflect improvement in gait over time..
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