[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84882-en":3,"doc-seo-84882-105":29,"detail-sidebar-cat-0-en-105":83},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},84882,8796095461610,"Oliver","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Designing Computerized Gait Analysis for Pediatric Care: Clinician Perspectives on Sensing, Workflow, and Care Environments","Computerized gait analysis (CGA) functions as an essential diagnostic capability for children with neuromuscular, musculoskeletal, and neurological disorders, supporting early and objective assessment across conditions such as cerebral palsy and muscular dystrophy. A qualitative study with 12 pediatric clinicians and one system designer examines pediatric-specific requirements driven by ongoing development. Clinicians highlight sensory sensitivities to wearables, sensor placement and calibration challenges shaped by body proportions, and the need to sustain engagement during data capture. The work proposes pediatric-centered CGA design recommendations for both sensory-appropriate sensing and data collection in diverse, naturalistic care environments.","Designing Computerized Gait Analysis for Pediatric Care: Clinician Perspectives on Sensing, Workflow, and Care  \nEnvironments  \nElizabeth Hong∗ Computer Science Stanford University USA  \nAndrea Green∗ Civil and Environmental Engineering Stanford University USA  \nGe Wang  \nSiebel School of Computing and Data Science University of Illinois Urbana-Champaign USA  \nYiwen Dong  \nIndustrial & Enterprise Systems Engineering University of Illinois Urbana-Champaign USA  \narXiv :2607 .06076v2 [ cs .HC] 8 Jul 2026  \nAbstract  \nComputerized gait analysis (CGA) serves as an essential diagnostic tool for evaluating neuromuscular, musculoskeletal, and neurological disorders in children, from cerebral palsy to muscular dystrophy. By enabling objective and comprehensive gait analysis, CGA supports timely clinical interventions that can significantly improve pediatric mobility outcomes and quality of life. Yet pediatric gait analysis introduces unique design considerations often underexplored in existing CGA research, as children’s ongoing development shapes assessment requirements. To understand how CGA technologies can be designed for pediatric care, we conducted a qualitative study with 12 pediatric clinicians and one system designer who routinely work with CGA. Participants identified child-specific challenges including managing heightened sensory sensitivities to wearable devices, accommodating body proportions in sensor placement and calibration, and maintaining patient engagement during data collection. Clinicians also articulated needs for workflow adaptations and expressed interest in extending gait analysis beyond controlled laboratory settings into naturalistic environments such as playgrounds and schools, where children’s authentic movement patterns emerge. Drawing from these clinician perspectives, we present design recommendations for pediatric-centered CGA that address sensing modalities suitable for sensory-sensitive children and approaches for capturing gait data across diverse care environments. Our findings contribute to the broader challenge of adapting clinical technologies to meet the distinct needs of pediatric populations.  \nKeywords  \nUser-centered Design, Computerized Gait Analysis, Sensing  \n1 Introduction  \nGait analysis is a cornerstone of clinical evaluation across neurological, musculoskeletal, and cardiovascular medicine, playing a critical role in managing conditions ranging from cognitive disorders to pediatric neuromuscular and neurological conditions such as muscular dystrophy and cerebral palsy [3, 13, 14, 23, 31, 37] . A  \n∗ These authors contributed equally to this work.  \nperson’s gait reflects underlying neuromuscular function, joint mechanics, and disease progression, providing clinicians with valuable diagnostic and prognostic insights.  \nHistorically, gait analysis relied on visual observation by trained clinicians [22, 39]. While instrumented approaches using sensors offered more comprehensive data capture [34], modern computerized gait analysis (CGA)—the use of computer-based technologies to collect, process, analyze, and visualize gait data—has dramatically expanded clinical capabilities. CGA utilizes vision-based systems, ambient sensors, and wearable devices to enable three-dimensional measurements, objective neuromuscular profiling, and longitudinal tracking that exceed what visual observation alone can provide[31] . These computerized methods are particularly crucial for pediatric patients, where comprehensive gait analysis and timely intervention can substantially improve long-term mobility and quality of life[15, 34] .  \nDespite its clinical value, significant barriers hinder the integration of CGA into routine clinical workflows. Clinicians face challenges related to the complexity of CGA systems, including lengthy setup times, specialized technical expertise requirements, and difficulties interpreting large volumes of data [20] . These barriers are further compounded when working with pediat","cbCaipdECkjFeZ6K","https://ap.wps.com/l/cbCaipdECkjFeZ6K","pdf",9804522,1,17,"English","en",105,"# Abstract\n# Introduction\n## Research gap and motivation\n## Study design and participants\n## Research questions and contributions","[{\"question\":\"How does the study structure clinician input to derive design recommendations?\",\"answer\":\"The study interviews 12 pediatric clinicians and one system designer, then categorizes clinicians by role: medical experts who coordinate technical procedures and patient interactions, and physicians who interpret results for diagnoses and treatment plans. Insights from these perspectives inform pediatric-centered sensing and workflow recommendations, including approaches for naturalistic environments.\"}]",1784198993,43,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":78,"head_meta":80,"extra_data":82,"updated_unix":27},"designing-computerized-gait-analysis-for-pediatric-care-clinician-perspectives-on-sensing-workflow-and-care-environments","",{"@graph":35,"@context":77},[36,53,68],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/designing-computerized-gait-analysis-for-pediatric-care-clinician-perspectives-on-sensing-workflow-and-care-environments/84882/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-17","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71],{"name":72,"@type":73,"acceptedAnswer":74},"How does the study structure clinician input to derive design recommendations?","Question",{"text":75,"@type":76},"The study interviews 12 pediatric clinicians and one system designer, then categorizes clinicians by role: medical experts who coordinate technical procedures and patient interactions, and physicians who interpret results for diagnoses and treatment plans. 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