{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/162530"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/162530","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Biomechanical Golf Swing Analysis using Markerless Three-Dimensional Skeletal Tracking through Truncation-Robust Heatmaps","abstract":"The efficient generation and transfer of energy in the golf swing has long been a subject of biomechanical interest, with a particular focus on the concept of the kinematic sequence, which is the coordinated segmental rotation of the pelvis, torso, arms, and club. While previous studies have modeled aspects of this sequence using high-end laboratory setups or proprietary systems, few have provided open, quantifiable, and time-resolved measurements of angular kinematics across the full swing cycle. This thesis seeks to address this gap by implementing a markerless temporal skeletal tracking approach built on the open-source MeTRAbs computer vision framework to model and measure joint angles and angular velocities throughout the golf swing. Using two-dimensional video footage of right-handed golfers performing driver swings, the MeTRAbs pose estimation model and supplemental cross-frame temporal motion sequencing code were used to reconstruct three-dimensional joint trajectories and compute rotational kinematics of key body segments. This study demonstrates the feasibility of using markerless pose estimation to extract golf swing signatures and angular velocity profiles without requiring expensive or inaccessible motion capture equipment. Preliminary analysis suggests that joint coordination patterns and temporal characteristics of body segment angular velocities may reveal quantifiable insights into the kinematic sequence, laying the groundwork for further research and instructional applications. Ultimately, this thesis contributes a replicable and cost-effective framework for analyzing golf swing biomechanics using open-source tools and computer vision.","abstract_html":"The efficient generation and transfer of energy in the golf swing has long been a subject of biomechanical interest, with a particular focus on the concept of the kinematic sequence, which is the coordinated segmental rotation of the pelvis, torso, arms, and club. While previous studies have modeled aspects of this sequence using high-end laboratory setups or proprietary systems, few have provided open, quantifiable, and time-resolved measurements of angular kinematics across the full swing cycle. This thesis seeks to address this gap by implementing a markerless temporal skeletal tracking approach built on the open-source MeTRAbs computer vision framework to model and measure joint angles and angular velocities throughout the golf swing. Using two-dimensional video footage of right-handed golfers performing driver swings, the MeTRAbs pose estimation model and supplemental cross-frame temporal motion sequencing code were used to reconstruct three-dimensional joint trajectories and compute rotational kinematics of key body segments. This study demonstrates the feasibility of using markerless pose estimation to extract golf swing signatures and angular velocity profiles without requiring expensive or inaccessible motion capture equipment. Preliminary analysis suggests that joint coordination patterns and temporal characteristics of body segment angular velocities may reveal quantifiable insights into the kinematic sequence, laying the groundwork for further research and instructional applications. Ultimately, this thesis contributes a replicable and cost-effective framework for analyzing golf swing biomechanics using open-source tools and computer vision.","abstract_has_math":false,"creators":["Taylor, Benjamin F."],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"System Design and Management Program.","school":null,"contributors":[],"advisors":["Hosoi, Anette \"Peko\""],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-05","date_published":"2025-05","updated_at":"2026-07-22T22:22:10Z","subjects":[],"languages":[],"rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"rights_urls":["https://rightsstatements.org/page/InC-EDU/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/162530","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Hosoi, Anette \"Peko\""]},{"key":"dc:contributor.department","label":"Department","values":["System Design and Management Program."]},{"key":"dc:creator","label":"Author","values":["Taylor, Benjamin F."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-08-27T14:31:39Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-08-27T14:31:39Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-05"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master","Master of Science in Engineering and Management"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://rightsstatements.org/page/InC-EDU/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1721.1/162530"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The efficient generation and transfer of energy in the golf swing has long been a subject of biomechanical interest, with a particular focus on the concept of the kinematic sequence, which is the coordinated segmental rotation of the pelvis, torso, arms, and club. While previous studies have modeled aspects of this sequence using high-end laboratory setups or proprietary systems, few have provided open, quantifiable, and time-resolved measurements of angular kinematics across the full swing cycle. This thesis seeks to address this gap by implementing a markerless temporal skeletal tracking approach built on the open-source MeTRAbs computer vision framework to model and measure joint angles and angular velocities throughout the golf swing. Using two-dimensional video footage of right-handed golfers performing driver swings, the MeTRAbs pose estimation model and supplemental cross-frame temporal motion sequencing code were used to reconstruct three-dimensional joint trajectories and compute rotational kinematics of key body segments. This study demonstrates the feasibility of using markerless pose estimation to extract golf swing signatures and angular velocity profiles without requiring expensive or inaccessible motion capture equipment. Preliminary analysis suggests that joint coordination patterns and temporal characteristics of body segment angular velocities may reveal quantifiable insights into the kinematic sequence, laying the groundwork for further research and instructional applications. Ultimately, this thesis contributes a replicable and cost-effective framework for analyzing golf swing biomechanics using open-source tools and computer vision."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Biomechanical Golf Swing Analysis using Markerless Three-Dimensional Skeletal Tracking through Truncation-Robust Heatmaps"]}]}],"canonical_facts":{"dc:contributor.advisor":["Hosoi, Anette \"Peko\""],"dc:contributor.department":["System Design and Management Program."],"dc:creator":["Taylor, Benjamin F."],"dc:date.accessioned":["2025-08-27T14:31:39Z"],"dc:date.available":["2025-08-27T14:31:39Z"],"dc:date.issued":["2025-05"],"dc:description.abstract":["The efficient generation and transfer of energy in the golf swing has long been a subject of biomechanical interest, with a particular focus on the concept of the kinematic sequence, which is the coordinated segmental rotation of the pelvis, torso, arms, and club. While previous studies have modeled aspects of this sequence using high-end laboratory setups or proprietary systems, few have provided open, quantifiable, and time-resolved measurements of angular kinematics across the full swing cycle. This thesis seeks to address this gap by implementing a markerless temporal skeletal tracking approach built on the open-source MeTRAbs computer vision framework to model and measure joint angles and angular velocities throughout the golf swing. Using two-dimensional video footage of right-handed golfers performing driver swings, the MeTRAbs pose estimation model and supplemental cross-frame temporal motion sequencing code were used to reconstruct three-dimensional joint trajectories and compute rotational kinematics of key body segments. This study demonstrates the feasibility of using markerless pose estimation to extract golf swing signatures and angular velocity profiles without requiring expensive or inaccessible motion capture equipment. Preliminary analysis suggests that joint coordination patterns and temporal characteristics of body segment angular velocities may reveal quantifiable insights into the kinematic sequence, laying the groundwork for further research and instructional applications. Ultimately, this thesis contributes a replicable and cost-effective framework for analyzing golf swing biomechanics using open-source tools and computer vision."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/162530"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"dc:rights.uri":["https://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["Biomechanical Golf Swing Analysis using Markerless Three-Dimensional Skeletal Tracking through Truncation-Robust Heatmaps"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Science in Engineering and Management"]},"updated_at":"2026-07-22T22:22:10Z"}