Exoskeleton Archives - Page 3 of 5 - Neuromechanics & Mobility Lab

MR Ebers, MC Rosenberg, JN Kutz, KM Steele (2023) “A machine learning approach to quantify individual gait responses to ankle exoskeletons”

Yusuke Maruo JournalArticle, News, Publications August 9, 2023December 15, 2023Exoskeleton, Gait, Modeling

Journal Article in Journal of Biomechanics:

Physiological and biomechanical responses to mechanical assistance from wearable technology are highly variable, especially for clinical populations; tools to predict how users respond to different types of exoskeleton assistance may optimize the prescription process and uncover underlying mechanisms driving locomotor changes in the context of personalized wearable/assistive technology.

Aim: The purpose of this study was to determine if a discrepancy modeling framework could quantify individual-specific gait responses to ankle exoskeletons.

Method: We employ a machine learning technique — neural network based discrepancy modeling — on gait data from 12 non-disabled adults to capture within-participant differences in walking dynamics without vs. with a bilateral passive elastic ankle exoskeletons applying 5 N-m/deg of torque. We fit three models: Nominal gait (no exo), Exo, and Discrepancy. Then, post-fitting, we extend the Nominal by the Discrepancy Model (Augmented). We hypothesize that if Augmented (Nom+Discrep) can capture similar amount of variability as the Exo model, then it can be inferred that the discrepancy model accurately captures how a user will respond to an exoskeleton — without direct information about that user’s physiology or motor coordination.

Results:While joint kinematics during Exo gait were well predicted using the Nominal model (median 𝑅2 = 0.863 − 0.939), the Augmented model significantly increased variance accounted for (𝑝 < 0.042, median 𝑅2 = 0.928 − 0.963). For EMG, the Augmented model (median 𝑅2 = 0.665 −
0.788) accounted for significantly more variance than the Nominal model (median 𝑅2 = 0.516 − 0.664). Minimal kinematic variance was left unexplained by the Exo model (median 𝑅2 = 0.954 − 0.978), but only accounted for 72.4%–81.5% of the median variance in EMG during Exo gait across all individuals.

Interpretation:Discrepancy modeling successfully quantified individuals’ exoskeleton responses without requiring knowledge about physiological structure or motor control. However, additional measurement modalities and/or improved resolution are needed to characterize Exo gait, as the discrepancy may not comprehensively capture response due to unexplained variance in Exo gait.

BC Conner, AM Spomer, KM Steele, ZF Lerner (2022) “Factors influencing neuromuscular responses to gait training with a robotic ankle exoskeleton in cerebral palsy”

Yusuke Maruo JournalArticle, Publications February 7, 2023August 9, 2023AFO, Cerebral Palsy, Exoskeleton

Journal Article in Assistive Technology:

Our findings underscored the importance of monitoring how users change their gait kinematics when walking with the resistive device, with a specific emphasis on stance-phase lower limb extension. We also highlight the necessity of considering an individual’s functional status and amount of practice with the device, as well as more obvious factors, like device parameters. BART can be used early in the development of robotic gait training interventions to better understand complex and multifactorial user-device interactions.

Aim: Although ankle exoskeletons offer a promising means of augmenting gait training and enhancing independent mobility among individuals with neuromuscular disorders, response to existing paradigms is highly heterogeneous. In this study we aimed to identify factors which may affect how individuals with cerebral palsy (CP) interact with a resistive ankle exoskeleton during multi-day training to inform future device design and individualized tuning.

Method:We evaluated the gait mechanics (kinematics and muscle activity) of eight individuals with CP as they walked with bilateral ankle exoskeletons – designed to promote increased plantar flexor recruitment – during a seven-day training paradigm. These data along with pertinent device and participant parameters were input into a Bayesian Additive Regression Trees (BART) machine learning model to identify factors which were most associated with increased plantar flexor recruitment.

Results: Four themes emerged: 1) AFO provision is a confusing and lengthy process, 2) participants want more information during AFO provision, 3) AFOs are uncomfortable and difficult to use, and 4) AFOs can benefit mobility and independence. Caregivers and individuals with CP recommended ideas such as 3D printing orthoses and education for caregivers on design choices to improve AFO design and provision.

Interpretation: Individuals with CP and their caregivers found the AFO provision process frustrating but highlight that AFOs support mobility and participation. Further opportunities exist to support function and participation of people with CP by streamlining AFO provision processes, creating educational materials, and improving AFO design for comfort and ease of use.

BC Conner, AM Spomer, SSPA Bishe, KM Steele, ZF Lerner (2022) “Soleus H-reflex modulation in cerebral palsy and its relationship with neural control complexity: a pilot study”

Katie Landwehr JournalArticle, MotorControl, News, Publications June 25, 2022June 11, 2024Cerebral Palsy, Exoskeleton, H-reflex, Muscle synergy

Journal Article in Experimental Brain Research

Individuals with cerebral palsy (CP) display motor control patterns that suggest decreased supraspinal input, but it remains unknown if they are able to modulate lower-limb reflexes in response to more complex tasks, or whether global motor control patterns relate to reflex modulation capacity in this population.

Aim: To further elucidate the multifaceted effects of CP on inhibitory and faciliatory supraspinal pathways and global measures of motor control, providing novel information for improving targeted neuromuscular interventions in this patient population.

Methods: Eight ambulatory individuals with CP (12–18 years old) were recruited to complete a task complexity protocol, where soleus H-reflex excitability was compared between bilateral (baseline) and unilateral (complex) standing. We also investigated the relationship between each participant’s ability to modulate soleus H-reflex excitability and the complexity of their walking neural control pattern determined from muscle synergy analysis. Finally, six of the eight participants completed an exoskeleton walking protocol, where soleus H-reflexes were collected during the stance phase of walking with and without stance-phase plantar flexor resistance.

Results: Participants displayed a significant reduction in soleus H-reflex excitability (− 26 ± 25%, p = 0.04) with unilateral standing, and a strong positive relationship was observed between more refined neural control during walking and an increased ability to modulate reflex excitability (R = 0.79, p = 0.04). There was no difference in neuromuscular outcome measures with and without the ankle exoskeleton (p values all > 0.05), with variable reflex responses to walking with ankle exoskeleton resistance.

Interpretation: These findings provide evidence that ambulatory individuals with CP retain some capacity to modulate lower-limb reflexes in response to increased task complexity, and that less refined neural control during walking appears to be related to deficits in reflex modulation.

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.

NBC Learn: Exoskeletons and Engineering

Dr. Steele Media, Orthoses November 12, 2019October 12, 2021Cerebral Palsy, engineering, Exoskeleton, Orthoses, prototype

We partnered with NBC Learn to share some of our work on exoskeletons to help encourage students to consider a career in engineering. What can be more exciting than musculoskeletal modeling, exoskeletons, horses, and stuffed animals?

Check out the video – a lesson plan will also be posted soon for classrooms to use.

Go team!