[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT07616167":3,"trial-entities:NCT07616167":96,"trial-summary:NCT07616167":99},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":7,"overall_status":8,"completion_date":9,"status_verified_date":10,"last_update_date":11,"start_date":12,"sponsor_name":13,"lead_sponsor_class":14,"has_dmc":15,"brief_summary":16,"detailed_description":15,"conditions":17,"keywords":19,"study_type":20,"primary_purpose":21,"phases":22,"enrollment_info":24,"interventions":27,"primary_outcomes":39,"secondary_outcomes":47,"sex":58,"minimum_age":59,"maximum_age":60,"healthy_volunteers":61,"eligibility_criteria":62,"std_ages":79,"locations":82,"central_contacts":92,"overall_officials":93,"references":94,"see_also_links":95},"NCT07616167","HUM00287262","This Study Evaluates the Use of a Data-driven Lower Limb Exoskeleton Controller for Stroke Rehabilitation.","From Stroke Rehabilitation to Independence: An Impairment-Aware Control Framework for Adaptive Exoskeleton Assistance","NOT_YET_RECRUITING","2027-12-31","2026-05","2026-06-01","2026-10-01","University of Michigan","OTHER",null,"The goal of this clinical trial is to test a new, impairment-aware robotic control software framework to see if its smart adaptation can improve walking recovery in healthy adults and chronic stroke survivors. .\n\nThe main questions it aims to answer are:\n\nCan the new control software safely use sensors and machine learning to predict and instantly adapt to a user's specific walking needs?\n\nDoes training with a robotic device driven by this new adaptive control framework improve walking speed and overall mobility in stroke survivors?\n\nResearchers will compare a lower-limb orthosis operating under the new \"smart\" control software (which adapts to the user's impairment) to the same device operating under a standard, non-adaptive controller (which uses rigid or fixed assistance) to see if the new control approach leads to greater improvements in walking ability.\n\nParticipants will:\n\nWalk on treadmills, flat walkways, or stairs while wearing a robotic leg orthosis driven by the different control software systems being tested.\n\nWear small tracking tools (like reflective motion-capture markers and muscle activity sensors) so researchers can precisely measure how their movements interact with each control program.\n\nComplete standard walking tests to measure their walking speed and overall mobility under each software condition.",[18],"Stroke",[],"INTERVENTIONAL","TREATMENT",[23],"NA",{"count":25,"type":26},20,"ESTIMATED",[28,34],{"type":29,"name":30,"description":31,"armGroupLabels":32},"DEVICE","Unified Control Framework for Lower-Limb Powered Orthosis","An AI-driven, machine learning-based control software integrated into a wearable lower-limb powered orthosis. The system utilizes a Bayesian Neural Network (BNN) to analyze a user's pathological walking patterns (kinematics) in real-time via onboard sensors. Based on this real-time performance, the device dynamically modulates its physical assistance along a seamless continuum. It automatically transitions between stiff corrective guidance (position-based gait training) when the user struggles, and compliant, volitional torque support (torque-based assistance) as the user's independent walking ability improves.",[33],"Experimental Arm",{"type":29,"name":35,"description":36,"armGroupLabels":37},"Conventional Robotic Controller","A standard control paradigm for lower-limb powered orthoses that provides non-adaptive physical assistance during gait training. Depending on the trial block, the device operates in one of two static modalities: either rigid position-based gait training (GT) that physically guides the patient's limbs through a fixed, predetermined trajectory regardless of effort, or torque-based volitional augmentation (VA) that proportionally amplifies existing muscle output or ground reaction forces. Unlike the experimental intervention, this controller cannot interpret kinematics in real-time or dynamically modulate assistance along a continuous spectrum based on the user's instantaneous performance.",[38],"Active Comparator Arm",[40,44],{"measure":41,"description":42,"timeFrame":43},"Walking Speed","A standardized clinical assessment used to determine short-distance walking speed over a 10-meter course. This metric evaluates the preliminary clinical efficacy of the unified control framework compared to the conventional controller in chronic stroke survivors.","Baseline (Week 0), Post-Intervention Phase 1 (Week 4), Post-Washout \u002F Pre-Intervention Phase 2 (Week 8), and Post-Intervention Phase 2 (Week 12).",{"measure":45,"description":46,"timeFrame":43},"Functional Mobility and Balance","A clinical performance-based measure used to assess dynamic balance, turning agility, and functional mobility. The test measures the time (in seconds) taken for a participant to rise from a chair, walk 3 meters, turn around, walk back, and sit down.",[48,52,55],{"measure":49,"description":50,"timeFrame":51},"Acute Within-Session Changes in Spatial Gait Symmetry","Gait symmetry evaluated using the step length symmetry index (SI), calculated from lower-limb kinematics recorded by the exoskeleton's onboard joint encoders and\u002For motion capture data. This metric evaluates the immediate corrective effects on walking patterns. An SI of 0% represents perfect symmetry.","Baseline (Week 0) and weekly during the 12 training sessions across each 4-week intervention period.",{"measure":53,"description":54,"timeFrame":51},"Acute Within-Session Changes in Ground Reaction Force Symmetry","Force symmetry evaluated using the peak vertical ground reaction force ratio between the paretic and non-paretic limbs, measured via the exoskeleton's instrumented insoles and\u002For force plates. This evaluates the immediate impact of the control framework on weight-bearing symmetry. Data are expressed as a dimensionless ratio, where a value of 1.0 indicates perfect symmetry between limbs. Force is measured in units of Newtons.",{"measure":56,"description":57,"timeFrame":51},"Acute Within-Session Changes in Joint Range of Motion","Measurement of the peak angular displacement of the knee, hip and ankle joints (in degrees) during the sagittal plane gait cycle, captured by the exoskeleton's onboard joint encoders and\u002For a motion capture system.","ALL","18 Years","80 Years",true,{"inclusion":63,"exclusion":72,"raw_text":78},[64,65,66,67,68,69,70,71],"Cohort 1: Able-Bodied Participants (Initial Validation)","Healthy young adults.","No history of neurological, orthopedic, or cardiovascular impairments affecting gait or balance.","Able to walk independently without assistive devices.","Individuals with a documented history of chronic stroke.","Persistent unilateral lower-limb motor impairment resulting in a pathological gait pattern (heterogeneous gait deficits).","Stable medical condition allowing for participation in intensive physical rehabilitation tasks.","Able to provide informed consent.",[73,74,75,76,77],"Severe cognitive or communication impairments that prevent the participant from following safety instructions or reporting discomfort.","Co-existing neurological conditions (other than stroke) that independently impair locomotion (e.g., Parkinson's disease, Multiple Sclerosis).","Severe lower-limb joint contractures or orthopedic conditions that mechanically restrict the safe range of motion of the robotic orthosis.","Skin breakdowns, open wounds, or severe unhealed lesions at the contact points where the powered orthosis interfaces with the lower limbs.","Any medical contraindication to intensive walking exercise or treadmill training (e.g., unstable angina, severe unmanaged cardiovascular disease).","Inclusion Criteria:\n\n* Cohort 1: Able-Bodied Participants (Initial Validation)\n* Healthy young adults.\n* No history of neurological, orthopedic, or cardiovascular impairments affecting gait or balance.\n* Able to walk independently without assistive devices.\n\nCohort 2: Stroke Survivors (Clinical Efficacy Pilot)\n\n* Individuals with a documented history of chronic stroke.\n* Persistent unilateral lower-limb motor impairment resulting in a pathological gait pattern (heterogeneous gait deficits).\n* Stable medical condition allowing for participation in intensive physical rehabilitation tasks.\n* Able to provide informed consent.\n\nExclusion Criteria:\n\n* Severe cognitive or communication impairments that prevent the participant from following safety instructions or reporting discomfort.\n* Co-existing neurological conditions (other than stroke) that independently impair locomotion (e.g., Parkinson's disease, Multiple Sclerosis).\n* Severe lower-limb joint contractures or orthopedic conditions that mechanically restrict the safe range of motion of the robotic orthosis.\n* Skin breakdowns, open wounds, or severe unhealed lesions at the contact points where the powered orthosis interfaces with the lower limbs.\n* Any medical contraindication to intensive walking exercise or treadmill training (e.g., unstable angina, severe unmanaged cardiovascular disease).",[80,81],"ADULT","OLDER_ADULT",[83],{"facility":84,"city":85,"state":86,"zip":87,"country":88,"geoPoint":89},"Rehabilitation Laboratory in the Ford Robotics Building on the University of Michigan North Campus","Ann Arbor","Michigan","48109","United States",{"lat":90,"lon":91},42.27756,-83.74088,[],[],[],[],{"nct_id":4,"conditions":97,"biomarkers":98},[18],[],{"nct_id":4,"found":100,"summary":15,"prompt_version":15},false]