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visual3d:tutorials:events:kinematic_event_detection [2025/06/02 20:33] – [Workflow Outline] wikisysopvisual3d:tutorials:events:kinematic_event_detection [2025/07/16 16:29] (current) – wikisysop
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 ===== Overview ===== ===== Overview =====
  
-This tutorial is a comprehensive walkthrough of a research investigation presented at the Ontario Biomechanics Conference (OBC) 2025.  +This tutorial is a comprehensive walkthrough of a research investigation presented at the Ontario Biomechanics Conference (OBC) 2025. The study, titled "Assessing Different Kinematic Methods of Structuring Gait", explores how gait events can be reliably detected using only kinematic data, without access to lab-based kinetic systems such as force plates or instrumented treadmills. 
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-The study, titled "Assessing Different Kinematic Methods of Structuring Gait", explores how gait events can be reliably detected using only kinematic data, without access to lab-based kinetic systems such as force plates or instrumented treadmills.  +
  
 **Research Question: Are kinematic event detection methods able to reliably structure biomechanical waveforms in the gait cycle?** **Research Question: Are kinematic event detection methods able to reliably structure biomechanical waveforms in the gait cycle?**
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 ===== Introduction ====== ===== Introduction ======
  
-In gait analysis, the ability to structure biomechanical waveforms into gait cycles is needed for analyzing different kinematic signals and calculating various gait measures. +In gait analysis, the ability to structure biomechanical waveforms into gait cycles is needed for analyzing different kinematic signals and calculating various gait measures. Traditionally, gait cycles are structured using kinetic event detection methods based on force thresholds, which provide an objective and reliable signal for detecting ON (HS) and OFF(TO). However, kinetic data acquisition is not always available and with more in-field data collection it is not feasible.
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-Traditionally, gait cycles are structured using kinetic event detection methods based on force thresholds, which provide an objective and reliable signal for detecting ON (HS) and OFF(TO). However, kinetic data acquisition is not always available and with more in-field data collection it is not feasible.+
  
 Given these limitations, researchers have developed a range of kinematic event detection algorithms that rely on marker trajectories or derived joint kinematics to infer gait events. While these methods are promising, their accuracy and robustness - especially under varying walking speeds and among diverse populations- needs validation. Given these limitations, researchers have developed a range of kinematic event detection algorithms that rely on marker trajectories or derived joint kinematics to infer gait events. While these methods are promising, their accuracy and robustness - especially under varying walking speeds and among diverse populations- needs validation.
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 ===== Sample Files ====== ===== Sample Files ======
  
-To facilitate learning and application, we provide a premade ZIP archive containing all required files.+To facilitate learning and application, we provide a premade ZIP archive containing all required files which can be downloaded [[https://has-motion.com/download/YouTubeTutorial/OBC_Sample_Data.zip|here.]]
   * Includes a Visual3D preprocessing pipeline (**Preprocessing_Pipeline**) that performs kinetic event detection and computes the necessary joint kinematics.   * Includes a Visual3D preprocessing pipeline (**Preprocessing_Pipeline**) that performs kinetic event detection and computes the necessary joint kinematics.
   * **PREPROCESSED_PARTICIPANTS**: Preprocessed CMZ files for all 42 participants with the preprocessing pipelines applied.   * **PREPROCESSED_PARTICIPANTS**: Preprocessed CMZ files for all 42 participants with the preprocessing pipelines applied.
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   * **AutoFormatted_Gait_Data_Final**: Excel sheet containing resultant exported data from processing - listing method, trial and cycle instance+duration. This format is used for more accessible manipulation during analysis in Python.   * **AutoFormatted_Gait_Data_Final**: Excel sheet containing resultant exported data from processing - listing method, trial and cycle instance+duration. This format is used for more accessible manipulation during analysis in Python.
  
-Copies of the literature for the various kinematic methods used are also included in the ZIP archive: +
-  * {{ :visual3d:tutorials:events:copy_of_zeni_richards_and_higginson_-_2008_-_two_simple_methods_for_determining_gait_events_during_treadmill_and_overground_walking_using_kinematic_data.pdf |Zeni et al. (2018) Method 1 and 2}} +
-  * {{ :visual3d:tutorials:events:copy_of_de_asha_robinson_and_barton_-_2012_-_a_marker_based_kinematic_method_of_identifying_initial_contact_during_gait_suitable_for_use_in_real-time_visual_feedback_applications.pdf |DeAsha et al. (2012)}} +
-  * {{ :visual3d:tutorials:events:copy_of_hreljac_and_marshall_-_2000_-_algorithms_to_determine_event_timing_during_normal_walking_using_kinematic_data.pdf |Hreljac & Marshall (2000)}} +
-  * {{ :visual3d:tutorials:events:copy_of_o_connor_et_al_-_2007_-_automatic_detection_of_gait_events_using_kinematic_data_1_.pdf |OConnor et al. (2007)}}+
  
 ===== Workflow Outline ====== ===== Workflow Outline ======
visual3d/tutorials/events/kinematic_event_detection.1748896401.txt.gz · Last modified: by wikisysop