{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/117796"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/117796","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Development and validation of lower- and upper-extremity robotic medical education task trainers for neurologic exams","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms","abstract_has_math":false,"creators":["Pei, Yinan"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Mechanical Engineering","degree_department":null,"school":null,"contributors":["Hsiao-Wecksler, Elizabeth T.","Kersh, Mariana E.","Ramos, João","Hernandez, Manuel E.","Zallek, Christopher M."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-12","date_published":"2022-12","updated_at":"2026-07-22T22:24:56Z","subjects":["Medical Training Simulators","Task Trainers","Medical Robotics","Series Elastic Actuators","Force Control","Medical Education","Haptics"],"languages":["en","eng"],"rights":["Copyright 2022 Yinan Pei"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/117796","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hsiao-Wecksler, Elizabeth T.","Kersh, Mariana E.","Ramos, João","Hernandez, Manuel E.","Zallek, Christopher M."]},{"key":"dc:creator","label":"Author","values":["Pei, Yinan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-12","2022-11-30"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Medical Training Simulators","Task Trainers","Medical Robotics","Series Elastic Actuators","Force Control","Medical Education","Haptics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2022 Yinan Pei"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/117796"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms","The student, Yinan Pei, accepted the attached license on 2022-11-29 at 11:57.","The student, Yinan Pei, submitted this Dissertation for approval on 2022-11-29 at 12:06.","This Dissertation was approved for publication on 2022-11-30 at 12:44.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18667 on 2023-04-12 at 07:34:41","During neurologic exams, clinicians perform manual assessments of various joints and rely on haptic experiential knowledge to diagnose underlying neurologic conditions. It is imperative to afford clinical learners more exposure to the haptic feeling of common abnormal behaviors. Traditionally, training is carried out on practice patients or even classmates, but outcomes are not always consistent and reliable. Alternatively, medical education training simulators could render accessible, safe, consistent, and scalable training environments. Although simulators have been widely adopted for surgical and anatomical procedures, there are no commercial task trainers for practicing neurologic examination techniques. Task trainers that can simulate multiple behaviors at various severity levels should integrate high-fidelity force control capability into human-size limb mannequins. Considering the device shares many similar technical challenges to powered prosthetics and exoskeletons, we refer to this category of device as robotic task trainers. A few research prototypes have been proposed previously but none have been adopted publicly, possibly due to cost, maintenance, portability, or mechanical complexity issues. In this dissertation research, we used a series elastic actuator (SEA) design strategy to develop robotic task trainers that achieve a balance across cost, size, and performance. Two prototype task trainers were developed. The lower-extremity trainer mimics ankle clonus and deep tendon reflex. The upper-extremity trainer replicates upper-arm spasticity, lead-pipe rigidity, and cogwheel rigidity. We discussed their design, sensing, modeling, and control aspects. Validation tests (benchtop performance and clinical expert assessments) highlight that these devices can be viable training solutions for learners in healthcare professions."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Development and validation of lower- and upper-extremity robotic medical education task trainers for neurologic exams"]}]}],"canonical_facts":{"dc:contributor":["Hsiao-Wecksler, Elizabeth T.","Kersh, Mariana E.","Ramos, João","Hernandez, Manuel E.","Zallek, Christopher M."],"dc:creator":["Pei, Yinan"],"dc:date":["2022-12","2022-11-30"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms","The student, Yinan Pei, accepted the attached license on 2022-11-29 at 11:57.","The student, Yinan Pei, submitted this Dissertation for approval on 2022-11-29 at 12:06.","This Dissertation was approved for publication on 2022-11-30 at 12:44.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18667 on 2023-04-12 at 07:34:41","During neurologic exams, clinicians perform manual assessments of various joints and rely on haptic experiential knowledge to diagnose underlying neurologic conditions. It is imperative to afford clinical learners more exposure to the haptic feeling of common abnormal behaviors. Traditionally, training is carried out on practice patients or even classmates, but outcomes are not always consistent and reliable. Alternatively, medical education training simulators could render accessible, safe, consistent, and scalable training environments. Although simulators have been widely adopted for surgical and anatomical procedures, there are no commercial task trainers for practicing neurologic examination techniques. Task trainers that can simulate multiple behaviors at various severity levels should integrate high-fidelity force control capability into human-size limb mannequins. Considering the device shares many similar technical challenges to powered prosthetics and exoskeletons, we refer to this category of device as robotic task trainers. A few research prototypes have been proposed previously but none have been adopted publicly, possibly due to cost, maintenance, portability, or mechanical complexity issues. In this dissertation research, we used a series elastic actuator (SEA) design strategy to develop robotic task trainers that achieve a balance across cost, size, and performance. Two prototype task trainers were developed. The lower-extremity trainer mimics ankle clonus and deep tendon reflex. The upper-extremity trainer replicates upper-arm spasticity, lead-pipe rigidity, and cogwheel rigidity. We discussed their design, sensing, modeling, and control aspects. Validation tests (benchtop performance and clinical expert assessments) highlight that these devices can be viable training solutions for learners in healthcare professions."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/117796"],"dc:language":["en","eng"],"dc:rights":["Copyright 2022 Yinan Pei"],"dc:subject":["Medical Training Simulators","Task Trainers","Medical Robotics","Series Elastic Actuators","Force Control","Medical Education","Haptics"],"dc:title":["Development and validation of lower- and upper-extremity robotic medical education task trainers for neurologic exams"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:56Z"}