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Gait parameters determination by 2D optical motion analyzer system
Mahyuddin A.I.a, Mihradi S.a, Dirgantara T.b, Maulido P.N.a
a Mechanical Design Research Group, Mechanical Engineering Department, Indonesia
b Aeronautics and Astronautics Department, Lightweight Structures Research Group, Institut Teknologi Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]In the present work, an optical motion-capture system combined with software for 2D clinical gait analysis is utilized to determine spatiotemporal gait parameters such as stride-length, cadence, cycle-time, and speed as well as joint angles. The developed system consists of a video camera with a maximum speed of 90 fps, LED markers, PC and technical computing software, which are developed for tracking markers attached to human body during motion and to calculate kinematics and kinetics parameters of human gait. Gait data of 60 subjects within the age group between 18 to 49 years are measured as part of an effort to develop normal walking database of Indonesian people. In the experiments, the subject is instructed to walk in a specially-arranged measurement area, which is calibrated using the Direct Linear Transformation (DLT) method. Before the measurement, the body posture of each subject is evaluated to ensure normalcy. To validate the system, the obtained gait data is compared to the available normal walking database, and the results obtained by the system show good compatibility. © (2011) Trans Tech Publications, Switzerland.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Age groups,Analyzer system,Body postures,Direct linear transformation,Gait parameters,Good compatibility,Human bodies,Human gait,Joint angle,Kinetics parameter,Maximum speed,Motion analyzer system,Motion capture,Normal walking,Optical motion,Technical computing[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Gait analysis,Gait parameters,Motion analyzer system[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.4028/www.scientific.net/AMM.83.123[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]