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Human Gait Analysis: A Case Study in Clinical Applications
H. K. Banga, P. Kalra, R.M. Belokar, R.. Kumar, Somya Saxena, D. K. Mahapatra
Abstract: The aim of this research paper is to enhance the human gait analysis of foot drop patients with 3D-printed ankle foot orthosis by using a clinical gait analysis lab. According to the World Health Organization (WHO), there are approximately 0.2 billion orthotics patients (which is about 10% of the world's orthotics patients’ population) who require AFO as a supportive device to lead their day-to-day life. The cost of currently available AFOs in the market varies according to the features such as conformability and flexibility. As the affordability of low-income group patients is a concern, they need to compromise comfort and usability levels to fit their budget. Currently, no study is available on the manufacturing and designing process of AFOs. For the above experiment, a standard gait laboratory setup and experimental protocol will be used. The subject's selection for research work depends upon the availability of foot deformity patients in the region i.e., Foot drops, Neurological Disorders, Cerebral Palsy, Stroke Patients, and some accidental cases. Current research to attain a short and clean identity of human movement to be used in enhancing the Gait pattern of foot deformities subjects, consisting of bodily rehabilitation areas. Current GAIT Analysis technology allows for single-step identification of complex objects with embedded electronics and is currently being implemented in all major fields of medicine. Combined with non-invasive 3D scanning techniques it allows clinical assessment and treatment in a telemedicine context regardless of geographical borders. By using 3D printed orthosis, it enhances the 75% human gait of foot drop patients that's the result shown in the clinical gait analysis report.
Series on Biomechanics, Vol.36 No.4 (2022), 66-75
DOI:10.7546/SB.08.04.2022
Keywords: Ankle Foot Orthosis (AFO), clinical applications; foot deformities; gait phases; human motion analysis
Date published: 2022-11-07
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