JournalArticle

MR Ebers, JP Williams, KM Steele, JN Kutz (2024) “Leveraging arbitrary mobile sensor trajectories with shallow recurrent decoder networks for full-state reconstruction,”

Katie Landwehr JournalArticle, Publications , ,

Journal Article in IEEE Access

Sensing is a fundamental task for the monitoring, forecasting, and control of complex systems. In many applications, a limited number of sensors are available and must move with the dynamics. Currently, optimal path planning, like Kalman filter estimation, is required to enable sparse mobile sensing for state estimation. However, we show that arbitrary mobile sensor trajectories can be used. By adapting the Shallow REcurrent Decoder (SHRED) network with mobile sensors, their time-history can be used to encode global information of the measured high-dimensional state space.

Summary figure of a shallow recurrent decoder network (SHRED) leveraging mobile sensors to reconstruct full state-space estimates from sparse dynamical trajectories. (Left) Sensor trajectory history encodes global information of the spatio-temporal dynamics of the sparsely measured system. In this work, we evaluate three challenging datasets, including forced isotropic turbulence, global sea-surface temperature, and human biomechanics. (Middle) The mobile SHRED architecture can (i) embed the multiscale physics of a system into a compact and low-dimensional latent space, and (ii) provide a mapping from the sparse mobile sensors to a full state estimate. (Right) The high-dimensional and complex system states can be reconstructed, provided training data for the dynamical trajectory of the sensor(s) is available.Aim: We leverage sparse mobile sensor trajectories for full-state estimation, agnostic to sensor path.

Methods: Using modern deep learning architectures, we show that a sequence-to-vector model, such as an LSTM (long, short-term memory) network, with a decoder network, dynamic trajectory information can be mapped to full state-space estimates.

Results: We demonstrate that by leveraging mobile sensor trajectories with shallow recurrent decoder networks, we can train the network (i) to accurately reconstruct the full state space using arbitrary dynamical trajectories of the sensors, (ii) the architecture reduces the variance of the mean-squared error of the reconstruction error in comparison with immobile sensors, and (iii) the architecture also allows for rapid generalization (parameterization of dynamics) for data outside the training set. Moreover, the path of the sensor can be chosen arbitrarily, provided training data for the spatial trajectory of the sensor is available.

Interpretation: The time-history of mobile sensors can be used to encode global information of the measured high-dimensional state space.

AA Portnova-Fahreeva, M Yamagami, A Robert-Gonzalez, J Mankoff, H Feldner, KM Steele (2024) “Accuracy of Video-Based Hand Tracking for People With Upper-Body Disabilities”

Katie Landwehr JournalArticle, News, Publications , ,

Journal Article in IEEE Transactions on Neural Systems and Rehabilitation Engineering

Utilization of hand-tracking cameras, such as Leap, for hand rehabilitation and functional assessments is an innovative approach to providing affordable alternatives for people with disabilities. However, prior to deploying these commercially-available tools, a thorough evaluation of their performance for disabled populations is necessary.

A graphic which shows two hands demonstrating hand gestures and a Leap hand tracking device. The graphic also says that "average accuracy for all hands 0.7-0.9".Aim: In this study, we provide an in-depth analysis of the accuracy of Leap’s hand-tracking feature for both individuals with and without upper-body disabilities for common dynamic tasks used in rehabilitation.

Methods: Leap is compared against motion capture with conventional techniques such as signal correlations, mean absolute errors, and digit segment length estimation. We also propose the use of dimensionality reduction techniques, such as Principal Component Analysis (PCA), to capture the complex, high-dimensional signal spaces of the hand.

Results: We found that Leap’s hand-tracking performance did not differ between individuals with and without disabilities, yielding average signal correlations between 0.7-0.9. Both low and high mean absolute errors (between 10-80mm) were observed across participants. Overall, Leap did well with general hand posture tracking, with the largest errors associated with the tracking of the index finger. Leap’s hand model was found to be most inaccurate in the proximal digit segment, underestimating digit lengths with errors as high as 18mm. Using PCA to quantify differences between the high-dimensional spaces of Leap and motion capture showed that high correlations between latent space projections were associated with high accuracy in the original signal space.

Interpretation: These results point to the potential of low-dimensional representations of complex hand movements to support hand rehabilitation and assessment.

EC Kuska, KM Steele (2024) “Does crouch alter the effects of neuromuscular impairments on gait? A simulation study”

Katie Landwehr JournalArticle, MotorControl, Publications , , , , , ,

Journal Article in Journal of Biomechanics

Cerebral palsy (CP) is a neurologic injury that impacts control of movement. Individuals with CP also often develop secondary impairments like weakness and contracture. Both altered motor control and secondary impairments influence how an individual walks after neurologic injury. However, understanding the complex interactions between and relative effects of these impairments makes analyzing and improving walking capacity in CP challenging.

A sagittal-plane musculoskeletal model and neuromuscular simulation framework that tracked average nondisabled (ND) kinematics and moderate and severe crouch gait. The model contains nine degrees-of-freedom (pelvic tilt and translation, and right and left hip, knee, and ankle flexion) actuated by eight Hill-type musculotendinous units per leg. The objective function minimized deviations from tracked kinematics and the sum of muscle activations squared (a2). We perturbed each gait simulation with multi-modal neuromuscular impairments—altered control, weakness, and contracture—of varying severities. Altered control was simulated by reducing the number of fixed synergies controlling each leg, and weakness and contracture were simulated by reducing a muscle’s maximum isometric force ( ) and tendon slack length ( ), respectively. A Bayesian Additive Regression Trees (BART) model then predicted resultant a2 from the simulated neuromuscular impairments for crouch and ND gait to evaluate the relative effects of each simulated neuromuscular impairment on the muscle activations required to maintain each gait pattern.Aim: The purpose of this study was to investigate the interactions between neuromuscular impairments and gait in CP.

Methods: We used a sagittal-plane musculoskeletal model and neuromuscular control framework to simulate crouch and nondisabled gait. We perturbed each simulation by varying the number of synergies controlling each leg (altered control), and imposed weakness and contracture. A Bayesian Additive Regression Trees (BART) model was also used to parse the relative effects of each impairment on the muscle activations required for each gait pattern.

Results: By using these simulations to evaluate gait-pattern specific effects of neuromuscular impairments, we identified some advantages of crouch gait. For example, crouch tolerated 13 % and 22 % more plantarflexor weakness than nondisabled gait without and with altered control, respectively. Furthermore, BART demonstrated that plantarflexor weakness had twice the effect on total muscle activity required during nondisabled gait than crouch gait. However, crouch gait was also disadvantageous in the presence of vasti weakness: crouch gait increased the effects of vasti weakness on gait without and with altered control.

Interpretation: These simulations highlight gait-pattern specific effects and interactions between neuromuscular impairments. Utilizing computational techniques to understand these effects can elicit advantages of gait deviations, providing insight into why individuals may select their gait pattern and possible interventions to improve energetics.

NL Zaino, Z McKee, CD Caskey, KM Steele, HA Feldner (2024) “Perceptions and experiences of first mobility aid provision for young children with cerebral palsy in the United States: a mixed-methods study”

Katie Landwehr JournalArticle, News, Publications , , , ,

Journal Article in Disability and Rehabilitation: Assistive Technology 

This research provides insights into the lived experiences of clinicians and caregivers of young children with CP regarding the prescription, provision, use and impact of first mobility aids, specifically ankle foot orthoses and walkers/gait trainers.

Caregiver views of impact of first orthoses (n = 8) and walkers (n = 4). Proportional bar graph depicting caregiver perceptions on the impacts of their child’s ankle foot orthoses and/or walkers on various activities.Aim: The purpose of this study was to establish and understand the provision process and impacts of first mobility aids for children with cerebral palsy (CP) in the United States – specifically orthoses, walkers and gait-trainers.

Methods: We performed a mixed-methods study including surveys and semi-structured interviews of caregivers of young children with CP (n = 10) and clinicians who work with young children with CP (n = 29). We used content analysis for the surveys and inductive coding for the interviews.

Results: Four themes emerged: (1) first mobility aids have mixed impacts and use patterns, (2) there is varied caregiver education and understanding about mobility aids, (3) clinician knowledge, consistency and connection impact care and (4) numerous access barriers exist for families, and there are still opportunities for improvement across all domains.

Interpretation: This study not only provides researchers and clinicians with an understanding of the current status of the prescription and provision process in the United States, but also offers suggestions for improvements of the process and mobility aids themselves. These results have implications for future research, mobility aid, design and the provision process of first mobility aids.

MC Rosenberg, JL Proctor, KM Steele (2024) “Quantifying changes in individual-specific template-based representations of center-of-mass dynamics during walking with ankle exoskeletons using Hybrid-SINDy”

Katie Landwehr JournalArticle, News, Publications , , ,

Journal Article in Scientific Reports

Ankle exoskeletons alter whole-body walking mechanics, energetics, and stability by altering center-of-mass (CoM) motion. Controlling the dynamics governing CoM motion is, therefore, critical for maintaining efficient and stable gait. However, how CoM dynamics change with ankle exoskeletons is unknown, and how to optimally model individual-specific CoM dynamics, especially in individuals with neurological injuries, remains a challenge.

Depictions of walking conditions, phase variables, and example template state variables. (A) Two-dimensional depictions of template model applied to human walking without and with ankle exoskeletons (left). The phase portrait (right) defined a phase variable, , used to cluster kinematically similar measurements for model fitting. Colors denote gait phases corresponding to first and second double-limb support, single-limb support, and swing of the right leg. (B) Stride-averaged global CoM position, velocity, and acceleration for an exemplary unimpaired adult in the anterior–posterior, vertical, and mediolateral directions. The three exoskeleton conditions are shown in panels (B) and (C): shoes-only (solid lines), zero-stiffness exoskeletons (K0; dashed lines), and stiff exoskeletons (KH; dotted lines). (C) Template position and velocity states used to fit the template signatures were defined by sagittal- and frontal-plane leg angles, and leg length.Aim: Evaluate individual-specific changes in CoM dynamics in unimpaired adults and one individual with post-stroke hemiparesis while walking in shoes-only and with zero-stiffness and high-stiffness passive ankle exoskeletons.

Methods: To identify optimal sets of physically interpretable mechanisms describing CoM dynamics, termed template signatures, we leveraged hybrid sparse identification of nonlinear dynamics (Hybrid-SINDy), an equation-free data-driven method for inferring sparse hybrid dynamics from a library of candidate functional forms.

Results: In unimpaired adults, Hybrid-SINDy automatically identified spring-loaded inverted pendulum-like template signatures, which did not change with exoskeletons (p > 0.16), except for small changes in leg resting length (p < 0.001). Conversely, post-stroke paretic-leg rotary stiffness mechanisms increased by 37–50% with zero-stiffness exoskeletons.

Interpretation: While unimpaired CoM dynamics appear robust to passive ankle exoskeletons, how neurological injuries alter exoskeleton impacts on CoM dynamics merits further investigation. Our findings support Hybrid-SINDy’s potential to discover mechanisms describing individual-specific CoM dynamics with assistive devices.