JournalArticle

KA Ingraham, HA Feldner, KM Steele (2024) “An Instrumented ‘Explorer Mini’ for Quantitative Analysis of Toddlers Using Powered Mobility for Exploratory, Mobile, and Digital Play”

Katie Landwehr JournalArticle, News, Presentation, Publications , , , ,

Journal Article in the 10th IEEE RAS EMBS Intl. Conference on Biomedical Robotics and Biomechatronics (BioRob).

For toddlers with disabilities, assistive technologies can enable developmentally appropriate exploration, play, and participation, but little is known about how children interact with accessible interfaces, such as joysticks.

The instrumented explorer mini measures joystick position, wheel rotations, and bodyweight loading at 100 Hz. Representative raw data collected from the device are shown here for 100 seconds.Aim: The Permobil Explorer Mini is currently the only commercially available, FDA-cleared pediatric powered mobility device in the United States designed for children ages 12–36 months. In this paper, we present an instrumented Explorer Mini that enables us to quantitatively analyze how young children with disabilities learn to use and interact with joystick-based technology.

Methods: We discuss preliminary results from two studies conducted with two toddlers with motor disabilities using the instrumented Explorer Mini in different contexts: 1) during exploratory mobile play (i.e., driving) and 2) during interactive digital play (i.e., playing a simple computer game).

Results: In the first study, we found that, for a given 15–20 minute play session, participants drove between 11.3 and 65.6 m, and engaged with the joystick between 53 and 165 times. In the second study, we found that children could use the joystick to play a simple cause-and-effect computer game, but that they disproportionately used the ‘forward’ direction of the joystick, regardless of the direction of the displayed target.

Interpretation: The novel experimental platform, research framework, and preliminary data presented in this paper lay the foundation to study how children with disabilities learn to use and interact with joystick-based assistive technologies. This knowledge is critical to inform the design and advancement of developmentally appropriate technologies that equitably support toddlers in exploration, mobility, and play.

NL Zaino, KA Ingraham, ME Hoffman, HA Feldner, KM Steele (2024) “Quantifying toddler exploration in different postures with powered mobility”

Katie Landwehr JournalArticle, News, Publications , , , ,

Journal Article in Assistive Technology

Access to powered mobility can support play and development for toddlers with disabilities. Using powered mobility in a standing posture has been theorized to support development of muscle coordination, balance, head and trunk stability, and transition to ambulation.

3 graphs showing the number of joystick activations, longest joystick activation, and loading through the base over the 13% bodyweight threshold in each play session for each participant for both SIT (left, open) and STAND (right, filled).

Aim: The purpose of this study was to quantify and characterize joystick control, bodyweight support, and muscle activity while using the Permobil Explorer Mini in seated and supported standing postures.

Methods: Nine children with mobility disabilities participated in four visits where they completed two, 15–20 minute play sessions, one in each posture, with a break between.

Results: We found that all toddlers engaged with the joystick in both postures, with individual differences in favored directions and control patterns. Participants had similar loading through their feet in both postures, but had slightly higher muscle activity in standing, especially while driving.

Interpretation: These results demonstrate that young children with disabilities quickly engage with joystick-based powered mobility in seated and standing postures, with important individual differences that can inform future design of devices and interventions to support play and development.

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.