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.
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.
OpenSense: An open-source toolbox for inertial-measurement-unit-based measurement of lower extremity kinematics over long durations.
Journal of neuroengineering and rehabilitation
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
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
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
SOC NUCLEAR MEDICINE INC. 2020
View details for Web of Science ID 000568290500163
Rapid volumetric gagCEST imaging of knee articular cartilage at 3 T: evaluation of improved dynamic range and an osteoarthritic population.
NMR in biomedicine
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
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
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
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