Scott Uhlrich is the Director of Research in the Stanford Human Performance Lab. He is interested in understanding pathological human movement as well as peak human performance. He uses experimental techniques and computational modeling to develop tools for preventing injury, improving the efficacy of rehabilitation, and maximizing mobility for individuals with diseases like osteoarthritis. Dr. Uhlrich has designed and patented numerous rehabilitation tools and has investigated their efficacy in clinical trials. He also develops tools for measuring human movement with commodity sensors like a cell phone camera, facilitating clinically-actionable measurements to be made in the clinic, at home, or on the field.

Academic Appointments

Professional Education

  • PhD, Stanford University, Mechanical Engineering (2020)
  • MS, Stanford University, Mechanical Engineering (2016)
  • BS, Baylor University, Mechanical Engineering (2014)

Current Research and Scholarly Interests

Experimental biomechanical analysis of healthy and pathological human movement. Real-time biofeedback to modify motor control and kinematics.

Musculoskeletal modeling and simulation for estimating unmeasurable quantities during movement, like joint forces in individuals with osteoarthritis. Predictive musculoskeletal simulations to design rehabilitation interventions.

Computer vision, wearable sensing, and machine learning to develop tools that democratize biomechanical analysis and translate biomechanical interventions into clinical practice.

Quantitative MRI for analyzing the effect of non-surgical treatments for osteoarthritis on cartilage health. PET-MRI for analyzing relationships between the mechanical loading of tissue metabolic activity.

All Publications

  • OpenCap: Human movement dynamics from smartphone videos. PLoS computational biology Uhlrich, S. D., Falisse, A., Kidziński, Ł., Muccini, J., Ko, M., Chaudhari, A. S., Hicks, J. L., Delp, S. L. 2023; 19 (10): e1011462


    Measures of human movement dynamics can predict outcomes like injury risk or musculoskeletal disease progression. However, these measures are rarely quantified in large-scale research studies or clinical practice due to the prohibitive cost, time, and expertise required. Here we present and validate OpenCap, an open-source platform for computing both the kinematics (i.e., motion) and dynamics (i.e., forces) of human movement using videos captured from two or more smartphones. OpenCap leverages pose estimation algorithms to identify body landmarks from videos; deep learning and biomechanical models to estimate three-dimensional kinematics; and physics-based simulations to estimate muscle activations and musculoskeletal dynamics. OpenCap's web application enables users to collect synchronous videos and visualize movement data that is automatically processed in the cloud, thereby eliminating the need for specialized hardware, software, and expertise. We show that OpenCap accurately predicts dynamic measures, like muscle activations, joint loads, and joint moments, which can be used to screen for disease risk, evaluate intervention efficacy, assess between-group movement differences, and inform rehabilitation decisions. Additionally, we demonstrate OpenCap's practical utility through a 100-subject field study, where a clinician using OpenCap estimated musculoskeletal dynamics 25 times faster than a laboratory-based approach at less than 1% of the cost. By democratizing access to human movement analysis, OpenCap can accelerate the incorporation of biomechanical metrics into large-scale research studies, clinical trials, and clinical practice.

    View details for DOI 10.1371/journal.pcbi.1011462

    View details for PubMedID 37856442

    View details for PubMedCentralID PMC10586693

  • Muscle coordination retraining inspired by musculoskeletal simulations reduces knee contact force. Scientific reports Uhlrich, S. D., Jackson, R. W., Seth, A., Kolesar, J. A., Delp, S. L. 2022; 12 (1): 9842


    Humans typically coordinate their muscles to meet movement objectives like minimizing energy expenditure. In the presence of pathology, new objectives gain importance, like reducing loading in an osteoarthritic joint, but people often do not change their muscle coordination patterns to meet these new objectives. Here we use musculoskeletal simulations to identify simple changes in coordination that can be taught using electromyographic biofeedback, achieving the therapeutic goal of reducing joint loading. Our simulations predicted that changing the relative activation of two redundant ankle plantarflexor muscles-the gastrocnemius and soleus-could reduce knee contact force during walking, but it was unclear whether humans could re-coordinate redundant muscles during a complex task like walking. Our experiments showed that after a single session of walking with biofeedback of summary measures of plantarflexor muscle activation, healthy individuals reduced the ratio of gastrocnemius-to-soleus muscle activation by 25±15% (p=0.004, paired t test, n=10). Participants who walked with this "gastrocnemius avoidance" gait pattern reduced late-stance knee contact force by 12±12% (p=0.029, paired t test, n=8). Simulation-informed coordination retraining could be a promising treatment for knee osteoarthritis and a powerful tool for optimizing coordination for a variety of rehabilitation and performance applications.

    View details for DOI 10.1038/s41598-022-13386-9

    View details for PubMedID 35798755

  • Osteoarthritis year in review 2023: biomechanics. Osteoarthritis and cartilage Diamond, L. E., Grant, T., Uhlrich, S. D. 2023


    Biomechanics plays a significant yet complex role in osteoarthritis (OA) onset and progression. Identifying alterations in biomechanical factors and their complex interactions is critical for gaining new insights into OA pathophysiology and identification of clearly defined and modifiable mechanical treatment targets. This review synthesized biomechanics studies from March 2022 to April 2023, from which three themes relating to human gait emerged: (1) new insights into the pathogenesis of OA using computational modelling and machine learning, (2) technology-enhanced biomechanical interventions for OA, and (3) out-of-lab biomechanical assessments of OA. We further highlighted future-focused areas which may continue to advance the field of biomechanics in OA, with a particular emphasis on exploiting technology to understand and treat biomechanical mechanisms of OA outside the laboratory. The breadth of studies included in this review highlights the complex role of biomechanics in OA and showcase numerous innovative and outstanding contributions to the field. Exciting cross-disciplinary efforts integrating computational modelling, mobile sensors, and machine learning methods show great promise for streamlining in vivo multi-scale biomechanics workflows and are expected to underpin future breakthroughs in the understanding and treatment of biomechanics in OA.

    View details for DOI 10.1016/j.joca.2023.11.015

    View details for PubMedID 38043858

  • Simulating Muscle-Level Energetic Cost Savings When Humans Run with a Passive Assistive Device. IEEE robotics and automation letters Stingel, J. P., Hicks, J. L., Uhlrich, S. D., Delp, S. L. 2023; 8 (10): 6267-6274


    Connecting the legs with a spring attached to the shoelaces, called an exotendon, can reduce the energetic cost of running, but how the exotendon reduces the energetic burden of individual muscles remains unknown. We generated muscle-driven simulations of seven individuals running with and without the exotendon to discern whether savings occurred during the stance phase or the swing phase, and to identify which muscles contributed to energy savings. We computed differences in muscle-level energy consumption, muscle activations, and changes in muscle-fiber velocity and force between running with and without the exotendon. The seven of nine participants who reduced energy cost when running with the exotendon reduced their measured energy expenditure rate by 0.9 W/kg (8.3%). Simulations predicted a 1.4 W/kg (12.0%) reduction in the average rate of energy expenditure and correctly identified that the exotendon reduced rates of energy expenditure for all seven individuals. Simulations showed most of the savings occurred during stance (1.5 W/kg), though the rate of energy expenditure was also reduced during swing (0.3 W/kg). The energetic savings were distributed across the quadriceps, hip flexor, hip abductor, hamstring, hip adductor, and hip extensor muscle groups, whereas no changes were observed in the plantarflexor or dorsiflexor muscles. Energetic savings were facilitated by reductions in the rate of mechanical work performed by muscles and their estimated rate of heat production. By modeling muscle-level energetics, this simulation framework accurately captured measured changes in whole-body energetics when using an assistive device. This is a useful first step towards using simulation to accelerate device design by predicting how humans will interact with assistive devices that have yet to be built.

    View details for DOI 10.1109/lra.2023.3303094

    View details for PubMedID 37745177

    View details for PubMedCentralID PMC10512759

  • Ten steps to becoming a musculoskeletal simulation expert: A half-century of progress and outlook for the future. Journal of biomechanics Uhlrich, S. D., Uchida, T. K., Lee, M. R., Delp, S. L. 2023; 154: 111623


    Over the past half-century, musculoskeletal simulations have deepened our knowledge of human and animal movement. This article outlines ten steps to becoming a musculoskeletal simulation expert so you can contribute to the next half-century of technical innovation and scientific discovery. We advocate looking to the past, present, and future to harness the power of simulations that seek to understand and improve mobility. Instead of presenting a comprehensive literature review, we articulate a set of ideas intended to help researchers use simulations effectively and responsibly by understanding the work on which today's musculoskeletal simulations are built, following established modeling and simulation principles, and branching out in new directions.

    View details for DOI 10.1016/j.jbiomech.2023.111623

    View details for PubMedID 37210923

  • Can static optimization detect changes in peak medial knee contact forces induced by gait modifications? Journal of biomechanics Kaneda, J. M., Seagers, K. A., Uhlrich, S. D., Kolesar, J. A., Thomas, K. A., Delp, S. L. 2023; 152: 111569


    Medial knee contact force (MCF) is related to the pathomechanics of medial knee osteoarthritis. However, MCF cannot be directly measured in the native knee, making it difficult for therapeutic gait modifications to target this metric. Static optimization, a musculoskeletal simulation technique, can estimate MCF, but there has been little work validating its ability to detect changes in MCF induced by gait modifications. In this study, we quantified the error in MCF estimates from static optimization compared to measurements from instrumented knee replacements during normal walking and seven different gait modifications. We then identified minimum magnitudes of simulated MCF changes for which static optimization correctly identified the direction of change (i.e., whether MCF increased or decreased) at least 70% of the time. A full-body musculoskeletal model with a multi-compartment knee and static optimization was used to estimate MCF. Simulations were evaluated using experimental data from three subjects with instrumented knee replacements who walked with various gait modifications for a total of 115 steps. Static optimization underpredicted the first peak (mean absolute error = 0.16 bodyweights) and overpredicted the second peak (mean absolute error = 0.31 bodyweights) of MCF. Average root mean square error in MCF over stance phase was 0.32 bodyweights. Static optimization detected the direction of change with at least 70% accuracy for early-stance reductions, late-stance reductions, and early-stance increases in peak MCF of at least 0.10 bodyweights. These results suggest that a static optimization approach accurately detects the direction of change in early-stance medial knee loading, potentially making it a valuable tool for evaluating the biomechanical efficacy of gait modifications for knee osteoarthritis.

    View details for DOI 10.1016/j.jbiomech.2023.111569

    View details for PubMedID 37058768

  • A scoping review of portable sensing for out-of-lab anterior cruciate ligament injury prevention and rehabilitation. NPJ digital medicine Tan, T., Gatti, A. A., Fan, B., Shea, K. G., Sherman, S. L., Uhlrich, S. D., Hicks, J. L., Delp, S. L., Shull, P. B., Chaudhari, A. S. 2023; 6 (1): 46


    Anterior cruciate ligament (ACL) injury and ACL reconstruction (ACLR) surgery are common. Laboratory-based biomechanical assessment can evaluate ACL injury risk and rehabilitation progress after ACLR; however, lab-based measurements are expensive and inaccessible to most people. Portable sensors such as wearables and cameras can be deployed during sporting activities, in clinics, and in patient homes. Although many portable sensing approaches have demonstrated promising results during various assessments related to ACL injury, they have not yet been widely adopted as tools for out-of-lab assessment. The purpose of this review is to summarize research on out-of-lab portable sensing applied to ACL and ACLR and offer our perspectives on new opportunities for future research and development. We identified 49 original research articles on out-of-lab ACL-related assessment; the most common sensing modalities were inertial measurement units, depth cameras, and RGB cameras. The studies combined portable sensors with direct feature extraction, physics-based modeling, or machine learning to estimate a range of biomechanical parameters (e.g., knee kinematics and kinetics) during jump-landing tasks, cutting, squats, and gait. Many of the reviewed studies depict proof-of-concept methods for potential future clinical applications including ACL injury risk screening, injury prevention training, and rehabilitation assessment. By synthesizing these results, we describe important opportunities that exist for clinical validation of existing approaches, using sophisticated modeling techniques, standardization of data collection, and creation of large benchmark datasets. If successful, these advances will enable widespread use of portable-sensing approaches to identify ACL injury risk factors, mitigate high-risk movements prior to injury, and optimize rehabilitation paradigms.

    View details for DOI 10.1038/s41746-023-00782-2

    View details for PubMedID 36934194

  • Smartphone videos of the sit-to-stand test predict osteoarthritis and health outcomes in a nationwide study. NPJ digital medicine Boswell, M. A., Kidziński, Ł., Hicks, J. L., Uhlrich, S. D., Falisse, A., Delp, S. L. 2023; 6 (1): 32


    Physical function decline due to aging or disease can be assessed with quantitative motion analysis, but this currently requires expensive laboratory equipment. We introduce a self-guided quantitative motion analysis of the widely used five-repetition sit-to-stand test using a smartphone. Across 35 US states, 405 participants recorded a video performing the test in their homes. We found that the quantitative movement parameters extracted from the smartphone videos were related to a diagnosis of osteoarthritis, physical and mental health, body mass index, age, and ethnicity and race. Our findings demonstrate that at-home movement analysis goes beyond established clinical metrics to provide objective and inexpensive digital outcome metrics for nationwide studies.

    View details for DOI 10.1038/s41746-023-00775-1

    View details for PubMedID 36871119

    View details for PubMedCentralID 5009047

  • Peak knee joint moments accurately predict medial and lateral knee contact forces in patients with valgus malalignment. Scientific reports Holder, J., van Drongelen, S., Uhlrich, S. D., Herrmann, E., Meurer, A., Stief, F. 2023; 13 (1): 2870


    Compressive knee joint contact force during walking is thought to be related to initiation and progression of knee osteoarthritis. However, joint loading is often evaluated with surrogate measures, like the external knee adduction moment, due to the complexity of computing joint contact forces. Statistical models have shown promising correlations between medial knee joint contact forces and knee adduction moments in particularly in individuals with knee osteoarthritis or after total knee replacements (R2=0.44-0.60). The purpose of this study was to evaluate how accurately model-based predictions of peak medial and lateral knee joint contact forces during walking could be estimated by linear mixed-effects models including joint moments for children and adolescents with and without valgus malalignment. Peak knee joint moments were strongly correlated (R2>0.85, p<0.001) with both peak medial and lateral knee joint contact forces. The knee flexion and adduction moments were significant covariates in the models, strengthening the understanding of the statistical relationship between both moments and medial and lateral knee joint contact forces. In the future, these models could be used to evaluate peak knee joint contact forces from musculoskeletal simulations using peak joint moments from motion capture software, obviating the need for time-consuming musculoskeletal simulations.

    View details for DOI 10.1038/s41598-023-30058-4

    View details for PubMedID 36806297

  • Personalization improves the biomechanical efficacy of foot progression angle modifications in individuals with medial knee osteoarthritis. Journal of biomechanics Uhlrich, S. D., Kolesar, J. A., Kidzinski, L., Boswell, M. A., Silder, A., Gold, G. E., Delp, S. L., Beaupre, G. S. 2022; 144: 111312


    Modifying the foot progression angle during walking can reduce the knee adduction moment, a surrogate measure of medial knee loading. However, not all individuals reduce their knee adduction moment with the same modification. This study evaluates whether a personalized approach to prescribing foot progression angle modifications increases the proportion of individuals with medial knee osteoarthritis who reduce their knee adduction moment, compared to a non-personalized approach. Individuals with medial knee osteoarthritis (N=107) walked with biofeedback instructing them to toe-in and toe-out by 5° and 10° relative to their self-selected angle. We selected individuals' personalized foot progression angle as the modification that maximally reduced their larger knee adduction moment peak. Additionally, we used lasso regression to identify which secondary kinematic changes made a 10° toe-in gait modification more effective at reducing the first knee adduction moment peak. Seventy percent of individuals reduced their larger knee adduction moment peak by at least 5% with a personalized foot progression angle modification, which was more than (p≤0.002) the 23-57% of individuals who reduced it with a uniformly assigned 5° or 10° toe-in or toe-out modification. When toeing-in, greater reductions in the first knee adduction moment peak were related to an increased frontal-plane tibia angle (knee more medial than ankle), a more valgus knee abduction angle, reduced contralateral pelvic drop, and a more medialized center of pressure in the foot reference frame. In summary, personalization increases the proportion of individuals with medial knee osteoarthritis who may benefit from a foot progression angle modification.

    View details for DOI 10.1016/j.jbiomech.2022.111312

    View details for PubMedID 36191434

  • [18F]Sodium Fluoride PET-MRI Detects Increased Metabolic Bone Response to Whole-Joint Loading Stress in Osteoarthritic Knees. Osteoarthritis and cartilage Watkins, L. E., Haddock, B., MacKay, J. W., Baker, J., Uhlrich, S. D., Mazzoli, V., Gold, G. E., Kogan, F. 2022


    OBJECTIVE: Altered joint function is a hallmark of osteoarthritis (OA). Imaging techniques for joint function are limited, but [18F]sodium fluoride (NaF) PET-MRI may assess the acute joint response to loading stresses. [18F]NaF PET-MRI was used to study the acute joint response to exercise in OA knees, and compare relationships between regions of increased uptake after loading and structural OA progression two years later.METHODS: In this prospective study, 10 participants with knee OA (59 ± 8 years; 8 female) were scanned twice consecutively using a PET-MR system and performed a one-legged squat exercise between scans. Changes in tracer uptake measures in 9 bone regions were compared between knees that did and did not exercise with a mixed-effects model. Areas of focally large changes in uptake between scans (ROIfocal, Delta SUVmax > 3) were identified and the presence of structural MRI features was noted. Five participants returned two years later to assess structural change on MRI.RESULTS: There was a significant increase in [18F]NaF uptake in OA exercised knees (SUV p < 0.001, Ki p = 0.002, K1 p < 0.001) that differed by bone region.CONCLUSION: There were regional differences in the acute bone metabolic response to exercise and areas of focally large changes in the metabolic bone response that might be representative of whole-joint dysfunction.

    View details for DOI 10.1016/j.joca.2022.08.004

    View details for PubMedID 36031138

  • Changes in foot progression angle during gait reduce the knee adduction moment and do not increase hip moments in individuals with knee osteoarthritis. Journal of biomechanics Seagers, K., Uhlrich, S. D., Kolesar, J. A., Berkson, M., Kaneda, J. M., Beaupre, G. S., Delp, S. L. 2022; 141: 111204


    People with knee osteoarthritis who adopt a modified foot progression angle (FPA) during gait often benefit from a reduction in the knee adduction moment. It is unknown, however, whether changes in the FPA increase hip moments, a surrogate measure of hip loading, which will increase the mechanical demand on the joint. This study examined how altering the FPA affects hip moments. Individuals with knee osteoarthritis walked on an instrumented treadmill with their baseline gait, 10° toe-in gait, and 10° toe-out gait. A musculoskeletal modeling package was used to compute joint moments from the experimental data. Fifty participants were selected from a larger study who reduced their peak knee adduction moment with a modified FPA. In this group, participants reduced the first peak of the knee adduction moment by 7.6% with 10° toe-in gait and reduced the second peak by 11.0% with 10° toe-out gait. Modifying the FPA reduced the early-stance hip abduction moment, at the time of peak hip contact force, by 4.3% ± 1.3% for 10° toe-in gait (p = 0.005, d = 0.49) and by 4.6% ± 1.1% for 10° toe-out gait (p < 0.001, d = 0.59) without increasing the flexion and internal rotation moments (p > 0.15). Additionally, 74% of individuals reduced their total hip moment at time of peak hip contact force with a modified FPA. In summary, when adopting a FPA modification that reduced the knee adduction moment, participants, on average, did not increase surrogate measures of hip loading.

    View details for DOI 10.1016/j.jbiomech.2022.111204

    View details for PubMedID 35772243

  • OpenSense: An open-source toolbox for inertial-measurement-unit-based measurement of lower extremity kinematics over long durations. Journal of neuroengineering and rehabilitation Al Borno, M., O'Day, J., Ibarra, V., Dunne, J., Seth, A., Habib, A., Ong, C., Hicks, J., Uhlrich, S., Delp, S. 2022; 19 (1): 22


    BACKGROUND: The ability to measure joint kinematics in natural environments over long durations using inertial measurement units (IMUs) could enable at-home monitoring and personalized treatment of neurological and musculoskeletal disorders. However, drift, or the accumulation of error over time, inhibits the accurate measurement of movement over long durations. We sought to develop an open-source workflow to estimate lower extremity joint kinematics from IMU data that was accurate and capable of assessing and mitigating drift.METHODS: We computed IMU-based estimates of kinematics using sensor fusion and an inverse kinematics approach with a constrained biomechanical model. We measured kinematics for 11 subjects as they performed two 10-min trials: walking and a repeated sequence of varied lower-extremity movements. To validate the approach, we compared the joint angles computed with IMU orientations to the joint angles computed from optical motion capture using root mean square (RMS) difference and Pearson correlations, and estimated drift using a linear regression on each subject's RMS differences over time.RESULTS: IMU-based kinematic estimates agreed with optical motion capture; median RMS differences over all subjects and all minutes were between 3 and 6 degrees for all joint angles except hip rotation and correlation coefficients were moderate to strong (r=0.60-0.87). We observed minimal drift in the RMS differences over 10min; the average slopes of the linear fits to these data were near zero (- 0.14-0.17deg/min).CONCLUSIONS: Our workflow produced joint kinematics consistent with those estimated by optical motion capture, and could mitigate kinematic drift even in the trials of continuous walking without rest, which may obviate the need for explicit sensor recalibration (e.g. sitting or standing still for a few seconds or zero-velocity updates) used in current drift-mitigation approaches when studying similar activities. This could enable long-duration measurements, bringing the field one step closer to estimating kinematics in natural environments.

    View details for DOI 10.1186/s12984-022-01001-x

    View details for PubMedID 35184727

  • Assessment of Quantitative [18F]Sodium Fluoride PET Measures of Knee Subchondral Bone Perfusion and Mineralization in Osteoarthritic and Healthy Subjects. Osteoarthritis and cartilage Watkins, L., MacKay, J., Haddock, B., Mazzoli, V., Uhlrich, S., Gold, G., Kogan, F. 2021


    OBJECTIVE: Molecular information derived from dynamic [18F]sodium fluoride ([18F]NaF) PET imaging holds promise as a quantitative marker of bone metabolism. The objective of this work was to evaluate physiological mechanisms of [18F]NaF uptake in subchondral bone of individuals with and without knee osteoarthritis (OA).METHODS: Eleven healthy volunteers and twenty OA subjects were included. Both knees of all subjects were scanned simultaneously using a 3T hybrid PET/MRI system. MRI MOAKS assessment was performed to score the presence and size of osteophytes, bone marrow lesions, and cartilage lesions. Subchondral bone kinetic parameters of bone perfusion (K1), tracer extraction fraction, and total tracer uptake into bone (Ki) were evaluated using the Hawkins 3-compartment model. Measures were compared between structurally normal-appearing bone regions and those with structural findings.RESULTS: Mean and maximum SUV and kinetic parameters Ki, K1, and extraction fraction were significantly different between Healthy subjects and subjects with OA. Between-group differences in metabolic parameters were observed both in regions where the OA group had degenerative changes as well as in regions that appeared structurally normal.CONCLUSIONS: Results suggest that bone metabolism is altered in OA subjects, including bone regions with and without structural findings, compared to healthy subjects. Kinetic parameters of [18F]NaF uptake in subchondral bone show potential to quantitatively evaluate the role of bone physiology in OA initiation and progression. Objective measures of bone metabolism from [18F]NaF PET imaging can complement assessments of structural abnormalities observed on MRI.

    View details for DOI 10.1016/j.joca.2021.02.563

    View details for PubMedID 33639259

  • A neural network to predict the knee adduction moment in patients with osteoarthritis using anatomical landmarks obtainable from 2D video analysis. Osteoarthritis and cartilage Boswell, M. A., Uhlrich, S. D., Kidzinski, L., Thomas, K., Kolesar, J. A., Gold, G. E., Beaupre, G. S., Delp, S. L. 2021


    OBJECTIVE: The knee adduction moment (KAM) can inform treatment of medial knee osteoarthritis; however, measuring the KAM requires an expensive gait analysis laboratory. We evaluated the feasibility of predicting the peak KAM during natural and modified walking patterns using the positions of anatomical landmarks that could be identified from video analysis.METHOD: Using inverse dynamics, we calculated the KAM for 86 individuals (64 with knee osteoarthritis, 22 without) walking naturally and with foot progression angle modifications. We trained a neural network to predict the peak KAM using the 3-dimensional positions of 13 anatomical landmarks measured with motion capture (3D neural network). We also trained models to predict the peak KAM using 2-dimensional subsets of the dataset to simulate 2-dimensional video analysis (frontal and sagittal plane neural networks). Model performance was evaluated on a held-out, 8-person test set that included steps from all trials.RESULTS: The 3D neural network predicted the peak KAM for all test steps with r2=0.78. This model predicted individuals' average peak KAM during natural walking with r2=0.86 and classified which 15° foot progression angle modifications reduced the peak KAM with accuracy=0.85. The frontal plane neural network predicted peak KAM with similar accuracy (r2=0.85) to the 3D neural network, but the sagittal plane neural network did not (r2=0.14).CONCLUSION: Using the positions of anatomical landmarks from motion capture, a neural network accurately predicted the peak KAM during natural and modified walking. This study demonstrates the feasibility of measuring the peak KAM using positions obtainable from 2D video analysis.

    View details for DOI 10.1016/j.joca.2020.12.017

    View details for PubMedID 33422707

  • Evaluating the Relationship between Dynamic Na[F-18]F-Uptake Parameters and MRI Knee Osteoarthritic Findings Watkins, L., MacKay, J., Haddock, B., Mazzoli, V., Uhlrich, S., Gold, G., Kogan, F. SOC NUCLEAR MEDICINE INC. 2020
  • Rapid volumetric gagCEST imaging of knee articular cartilage at 3 T: evaluation of improved dynamic range and an osteoarthritic population. NMR in biomedicine Watkins, L. E., Rubin, E. B., Mazzoli, V. n., Uhlrich, S. D., Desai, A. D., Black, M. n., Ho, G. K., Delp, S. L., Levenston, M. E., Beaupré, G. S., Gold, G. E., Kogan, F. n. 2020: e4310


    Chemical exchange saturation transfer of glycosaminoglycans, gagCEST, is a quantitative MR technique that has potential for assessing cartilage proteoglycan content at field strengths of 7 T and higher. However, its utility at 3 T remains unclear. The objective of this work was to implement a rapid volumetric gagCEST sequence with higher gagCEST asymmetry at 3 T to evaluate its sensitivity to osteoarthritic changes in knee articular cartilage and in comparison with T2 and T1ρ measures. We hypothesize that gagCEST asymmetry at 3 T decreases with increasing severity of osteoarthritis (OA). Forty-two human volunteers, including 10 healthy subjects and 32 subjects with medial OA, were included in the study. Knee Injury and Osteoarthritis Outcome Scores (KOOS) were assessed for all subjects, and Kellgren-Lawrence grading was performed for OA volunteers. Healthy subjects were scanned consecutively at 3 T to assess the repeatability of the volumetric gagCEST sequence at 3 T. For healthy and OA subjects, gagCEST asymmetry and T2 and T1ρ relaxation times were calculated for the femoral articular cartilage to assess sensitivity to OA severity. Volumetric gagCEST imaging had higher gagCEST asymmetry than single-slice acquisitions (p = 0.015). The average scan-rescan coefficient of variation was 6.8%. There were no significant differences in average gagCEST asymmetry between younger and older healthy controls (p = 0.655) or between healthy controls and OA subjects (p = 0.310). T2 and T1ρ relaxation times were elevated in OA subjects (p < 0.001 for both) compared with healthy controls and both were moderately correlated with total KOOS scores (rho = -0.181 and rho = -0.332 respectively). The gagCEST technique developed here, with volumetric scan times under 10 min and high gagCEST asymmetry at 3 T, did not vary significantly between healthy subjects and those with mild-moderate OA. This further supports a limited utility for gagCEST imaging at 3 T for assessment of early changes in cartilage composition in OA.

    View details for DOI 10.1002/nbm.4310

    View details for PubMedID 32445515

  • Connecting the legs with a spring improves human running economy. The Journal of experimental biology Simpson, C. S., Welker, C. G., Uhlrich, S. D., Sketch, S. M., Jackson, R. W., Delp, S. L., Collins, S. H., Selinger, J. C., Hawkes, E. W. 2019


    Human running is inefficient. For every ten calories burned, less than one is needed to maintain a constant forward velocity-the remaining energy is, in a sense, wasted. The majority of this wasted energy is expended to support the bodyweight and redirect the center of mass during the stance phase of gait. An order of magnitude less energy is expended to brake and accelerate the swinging leg. Accordingly, most devices designed to increase running efficiency have targeted the costlier stance phase of gait. An alternative approach is seen in nature: spring-like tissues in some animals and humans are believed to assist leg swing. While it has been assumed that such a spring simply offloads the muscles that swing the legs, thus saving energy, this mechanism has not been experimentally investigated. Here we show that a spring, or 'exotendon', connecting the legs of a human reduces the energy required for running by 6.4±2.8%, and does so through a complex mechanism that produces savings beyond those associated with leg swing. The exotendon applies assistive forces to the swinging legs, increasing the energy optimal stride frequency. Runners then adopt this frequency, taking faster and shorter strides, and reduce the joint mechanical work to redirect their center of mass. Our study shows how a simple spring improves running economy through a complex interaction between the changing dynamics of the body and the adaptive strategies of the runner, highlighting the importance of considering each when designing systems that couple human and machine.

    View details for DOI 10.1242/jeb.202895

    View details for PubMedID 31395676

  • Assessment of acute bone loading in humans using [18F]NaF PET/MRI. European journal of nuclear medicine and molecular imaging Haddock, B., Fan, A. P., Uhlrich, S. D., Jorgensen, N. R., Suetta, C., Gold, G. E., Kogan, F. 2019


    PURPOSE: The acute effect of loading on bone tissue and physiology can offer important information with regard to joint function in diseases such as osteoarthritis. Imaging studies using [18F]-sodium fluoride ([18F]NaF) have found changes in tracer kinetics in animals after subjecting bones to strain, indicating an acute physiological response. The aim of this study is to measure acute changes in NaF uptake in human bone due to exercise-induced loading.METHODS: Twelve healthy subjects underwent two consecutive 50-min [18F]NaF PET/MRI examinations of the knees, one baseline followed by one post-exercise scan. Quantification of tracer kinetics was performed using an image-derived input function from the popliteal artery. For both scans, kinetic parameters of KiNLR, K1, k2, k3, and blood volume were mapped parametrically using nonlinear regression with the Hawkins model. The kinetic parameters along with mean SUV and SUVmax were compared between the pre- and post-exercise examinations. Differences in response to exercise were analysed between bone tissue types (subchondral, cortical, and trabecular bone) and between regional subsections of knee subchondral bone.RESULTS: Exercise induced a significant (p<<0.001) increase in [18F]NaF uptake in all bone tissues in both knees, with mean SUV increases ranging from 47% in trabecular bone tissue to 131% in subchondral bone tissue. Kinetic parameters involving vascularization (K1 and blood volume) increased, whereas the NaF extraction fraction [k3/(k2+k3)] was reduced.CONCLUSIONS: Bone loading induces an acute response in bone physiology as quantified by [18F]NaF PET kinetics. Dynamic imaging after bone loading using [18F]NaF PET is a promising diagnostic tool in bone physiology and imaging of biomechanics.

    View details for DOI 10.1007/s00259-019-04424-2

    View details for PubMedID 31385012

  • Subject-specific toe-in or toe-out gait modifications reduce the larger knee adduction moment peak more than a non-personalized approach JOURNAL OF BIOMECHANICS Uhlrich, S. D., Slider, A., Beaupre, G. S., Shull, P. B., Delp, S. L. 2018; 66: 103–10


    The knee adduction moment (KAM) is a surrogate measure for medial compartment knee loading and is related to the progression of knee osteoarthritis. Toe-in and toe-out gait modifications typically reduce the first and second KAM peaks, respectively. We investigated whether assigning a subject-specific foot progression angle (FPA) modification reduces the peak KAM by more than assigning the same modification to everyone. To explore the effects of motor learning on muscle coordination and kinetics, we also evaluated the peak knee flexion moment and quadriceps-hamstring co-contraction during normal walking, when subjects first learned their subject-specific FPA, and following 20 min of training. Using vibrotactile feedback, we trained 20 healthy adults to toe-in and toe-out by 5° and 10° relative to their natural FPA, then identified the subject-specific FPA as the angle where each subject maximally reduced their larger KAM peak. When walking at their subject-specific FPA, 18 subjects significantly reduced their larger KAM peak; 8 by toeing-in and 10 by toeing-out. On average, subjects reduced their larger KAM peak by 18.6 ± 16.2% when walking at their subject-specific FPA, which was more than the reductions achieved when all subjects toed-in by 10° (10.0 ± 17.1%, p = .013) or toed-out by 10° (11.0 ± 18.3%, p = .002). Quadriceps-hamstring co-contraction and the peak knee flexion moment increased when subjects first learned their subject-specific FPA, but only co-contraction returned to baseline levels following training. These findings demonstrate that subject-specific gait modifications reduce the peak KAM more than uniformly assigned modifications and have the potential to slow the progression of medial compartment knee osteoarthritis.

    View details for PubMedID 29174534

    View details for PubMedCentralID PMC5859947