Gait Archives - Page 2 of 2 - Steele Lab - University of Washington

MC Rosenberg, BS Banjanin, SA Burden, KM Steele (2020) “Predicting walking response to ankle exoskeleton using data driven models”

Elijah JournalArticle, News October 20, 2020October 12, 2021Exoskeleton, Floquent theory, Gait, generalizable models, Modeling, Orthoses, Walking

Journal Article in The Royal Society:

This work highlights the potential of data-driven models grounded in dynamical systems theory to predict complex individualized responses to ankle exoskeletons., without requiring explicit knowledge of the individual’s physiology or motor control

Aim: Evaluate the ability of three classes of subject-specific phase-varying (PV) models to predict kinematic and myoelectric responses to ankle exoskeletons during walking, without requiring prior knowledge of specific user characteristics.

Method: Data from 12 unimpaired adults walking with bilateral passive ankle exoskeletons were captured. PV, linear PV (LPV), and nonlinear PV (NPV) models leveraged Floquet theory to kinematics and muscle activity in response to three exoskeleton torque conditions.

Results: The LPV model’s predictions were more accurate than the PV model when predicting less than 12.5% of a stride in the future and explained 49–70% of the variance in hip, knee and ankle kinematic responses to torque. The LPV model also predicted kinematic responses with similar accuracy to the more-complex NPV model. Myoelectric responses were challenging to predict with all models, explaining at most 10% of the variance in responses.

Interpretation: This work highlights the potential of data-driven PV models to predict complex subject-specific responses to ankle exoskeletons and inform device design and control.

NL Zaino, KM Steele, JM Donelan, MH Schwartz (2020) “Energy consumption does not change after selective dorsal rhizotomy in children with spastic cerebral palsy” Developmental Medicine & Child Neurology

Nicole JournalArticle, News, Publications April 23, 2020October 12, 2021Cerebral Palsy, energy consumption, Gait, selective dorsal rhizotomy, Spasticity

Journal Article in Developmental Medicine & Child Neurology:

This retrospective analysis demonstrated that energy consumption is not reduced after rhizotomy when compared to matched controls with cerebral palsy.

Aim: To determine whether energy consumption changes after selective dorsal rhizotomy (SDR) among children with cerebral palsy (CP).

Method: We retrospectively evaluated net nondimensional energy consumption during walking among 101 children with bilateral spastic CP who underwent SDR (59 males, 42 females; median age [5th centile, 95th centile] 5y 8mo [4y 2mo, 9y 4mo]) compared to a control group of children with CP who did not undergo SDR. The control group was matched by baseline age, spasticity, and energy consumption (56 males, 45 females; median age [5th centile, 95th centile] 5y 8mo [4y 1mo, 9y 6mo]). Outcomes were compared at baseline and follow‐up (SDR: mean [SD] 1y 7mo [6mo], control: 1y 8mo [8mo]).

Results: The SDR group had significantly greater decreases in spasticity compared to matched controls (–42% SDR vs –20% control, p<0.001). While both groups had a modest reduction in energy consumption between visits (–12% SDR, –7% control), there was no difference in change in energy consumption (p=0.11) or walking speed (p=0.56) between groups.

Interpretation: The SDR group did not exhibit greater reductions in energy consumption compared to controls. The SDR group had significantly greater spasticity reduction, suggesting that spasticity had minimal impact on energy consumption during walking in CP. These results support prior findings that spasticity and energy consumption decrease with age in CP. Identifying matched control groups is critical for outcomes research involving children with CP to account for developmental changes.

B Nguyen, N Baicoianu, D Howell, KM Peters, KM Steele (2020) “Accuracy and repeatability of smartphone sensors for measuring shank-to-vertical angle” Prosthetics & Orthotics International

Dr. Steele HuskySTEPS, JournalArticle, Orthoses, UbiquitousRehabilitation March 9, 2020October 12, 2021accuracy, AFO, app, Gait, Orthoses, Repeatability, wearable sensors

Journal Article in Prosthetics & Orthotics International

Example of how the smartphone app was used for this research. The top images show a black smartphone attached with a running arm band to the side or front of the shank - the two positions tested in this research. The middle figure shows the placement of the reflective markers for 3D motion analysis to evaluate the accuracy of the smartphone measurements. Markers were placed on the lateral epicondyle of the knee, lateral maleolus of the ankle, tibial tuberosity, and the distal tibia. Blacklight was used to mark the position of each marker and hide the position from the clinicians. The bottom panel shows screenshots from the app. The first screen is used to align the device and has arrows at the top and bottom that remind the clinician which anatomical landmarks should be used to align the device while displaying the shank-to-vertical angle in real time. The second screenshot shows an example of the calculated shank-to-vertical angle while someone was walking. The average is shown with a bold black line, with all other trials shown in blue and excluded trials (e.g., when someone was stopping or turning) that deviated more than one standard deviation from other trials are shown in red. There is also text below the graph that provides summary measures, like shank-to-vertical angle in mid stand and cadence (steps/min). The results can be exported as a picture or sent via e-mail using the app. — A) Smartphone positioning on the front or side of the shank. B) Reflective markers on the the tibial tuberosity (TT) – distal tibia (DT) and lateral epicondyle (LE) – lateral malleolus (LM) were used to compare the accuracy of the smartphone to traditional motion capture. UV markings were used to keep placement of these markers constant while blinding clinicians. C) Sample screenshots of the mobile application, including the set-up screen and results automatically produced after a walking trial.

Background

Assessments of human movement are clinically important. However, accurate measurements are often unavailable due to the need for expensive equipment or intensive processing. For orthotists and therapists, shank-to-vertical angle (SVA) is one critical measure used to assess gait and guide prescriptions. Smartphone-based sensors may provide a widely-available platform to expand access to quantitative assessments.

Objectives

Assess accuracy and repeatability of smartphone-based measurement of SVA compared to marker-based 3D motion analysis.

Method

Four licensed clinicians (two physical therapists and two orthotists) measured SVA during gait with a smartphone attached to the anterior or lateral shank surface of unimpaired adults. We compared SVA calculated from the smartphone’s inertial measurement unit to marker-based measurements. Each clinician completed three sessions/day on two days with each participant to assess repeatability.

Results

Average absolute differences in SVA measured with a smartphone versus marker-based 3D motion analysis during gait were 0.67 ± 0.25° and 4.89 ± 0.72°, with anterior or lateral smartphone positions, respectively. The inter- and intra-day repeatability of SVA were within 2° for both smartphone positions.

Conclusions

Smartphone sensors can be used to measure SVA with high accuracy and repeatability during unimpaired gait, providing a widely-available tool for quantitative gait assessments.

Try it out!

The app for monitoring shank-to-vertical angle is available for you to download and use on either Android or iOS smartphone. Please complete THIS SURVEY which will then send you an e-mail with instructions for installation and use. This app is not an FDA approved medical device and should be used appropriately.

BR Shuman, M Goudriaan, K Desloovere, MH Schwartz, KM Steele (2019) “Muscle synergies demonstrate only minimal changes after treatment in cerebral palsy.” Journal of NeuroEngineering and Rehabilitation

Nicole JournalArticle, MotorControl, Projects, Publications March 29, 2019October 12, 2021CP (cerebral palsy), Electromyography, Gait, Motor Control, Motor disorders, Muscle synergy, Neurological rehabilitation, Synergy plasticity

Journal Article in Journal of NeuroEngineering and Rehabilitation:

In collaboration with University Hospital Pellenberg we examined whether muscle synergies change following common treatments in CP.

Background: Children with cerebral palsy (CP) have altered synergies compared to typically-developing peers, reflecting different neuromuscular control strategies used to move. While these children receive a variety of treatments to improve gait, whether synergies change after treatment, or are associated with treatment outcomes, remains unknown.

Methods: We evaluated synergies for 147 children with CP before and after three common treatments: botulinum toxin type-A injection (n = 52), selective dorsal rhizotomy (n = 38), and multi-level orthopaedic surgery (n = 57). Changes in synergy complexity were measured by the number of synergies required to explain > 90% of the total variance in electromyography data and total variance accounted for by one synergy. Synergy weights and activations before and after treatment were compared using the cosine similarity relative to average synergies of 31 typically-developing (TD) peers.

Results: There were minimal changes in synergies after treatment despite changes in walking patterns. Number of synergies did not change significantly for any treatment group. Total variance accounted for by one synergy increased (i.e., moved further from TD peers) after botulinum toxin type-A injection (1.3%) and selective dorsal rhizotomy (1.9%), but the change was small. Synergy weights did not change for any treatment group (average 0.001 ± 0.10), but synergy activations after selective dorsal rhizotomy did change and were less similar to TD peers (− 0.03 ± 0.07). Only changes in synergy activations were associated with changes in gait kinematics or walking speed after treatment. Children with synergy activations more similar to TD peers after treatment had greater improvements in gait.

Conclusions: While many of these children received significant surgical procedures and prolonged rehabilitation, the minimal changes in synergies after treatment highlight the challenges in altering neuromuscular control in CP. Development of treatment strategies that directly target impaired control or are optimized to an individual’s unique control may be required to improve walking function.

BR Shuman, M Goudriaan, K Desloovere, MH Schwartz, KM Steele (2018) “Associations Between Muscle Synergies and Treatment Outcomes in Cerebral Palsy Are Robust Across Clinical Centers.” Archives of Physical Medicine and Rehabilitation

Nicole JournalArticle, MotorControl, Projects, Publications November 1, 2018October 12, 2021Cerebral Palsy, Electromyography, Gait, Motor disorders, Rehabilitation, Walking speed

Journal article in Archives of Physical Medicine and Rehabilitation:

In collaboration with Gillette Children’s Hospital and University Hospital Pellenberg we examined whether associations between treatment outcomes and muscles synergies are robust between clinical centers.

Objective: To determine whether patient-specific differences in motor control quantified using muscle synergy analysis were associated with changes in gait after treatment of cerebral palsy (CP) across 2 clinical centers with different treatments and clinical protocols.

Design: Retrospective cohort study.

Setting: Clinical medical center.

Participants: Center 1: children with CP (n=473) and typically developing (TD) children (n=84). Center 2: children with CP (n=163) and TD children (n=12).

Interventions: Standard clinical care at each center.

Main outcome measures: The Dynamic Motor Control Index During Walking (walk-DMC) was computed from electromyographic data during gait using muscle synergy analysis. Regression analysis was used to evaluate whether pretreatment walking speed or kinematics, muscle synergies, treatment group, prior treatment, or age were associated with posttreatment changes in gait at both clinical centers.

Results: Walk-DMC was significantly associated with changes in speed and kinematics after treatment with similar regression models at both centers. Children with less impaired motor control were more likely to have improvements in walking speed and gait kinematics after treatment, independent of treatment group.

Conclusions: Dynamic motor control evaluated with synergy analysis was associated with changes in gait after treatment at both centers, despite differences in treatments and clinical protocols. This study further supports the finding that walk-DMC provides additional information, not captured in traditional gait analysis, that may be useful for treatment planning.