AM Spomer, BC Conner, MH Schwartz, ZF Lerner, KM Steele (2023) “Audiovisual biofeedback amplifies plantarflexor adaptation during walking among children with cerebral palsy”

Journal Article in Journal of NeuroEngineering and Rehabilitation

Biofeedback is a promising noninvasive strategy to enhance gait training among individuals with cerebral palsy (CP). Commonly, biofeedback systems are designed to guide movement correction using audio, visual, or sensorimotor (i.e., tactile or proprioceptive) cues, each of which has demonstrated measurable success in CP.

Figure 1. Experimental Protocol. Audiovisual (AV) biofeedback on soleus activity was provided for the more-affected limb alongside an auto-adjusting target score. Sensorimotor (SM) biofeedback was provided for the more-affected limb using an untethered ankle exoskeleton designed to impart a resistive ankle torque through stance, proportional to baseline values. Participants completed three data collection visits (pre-acclimation, post-acclimation, and follow-up), during which they walked with both biofeedback systems independently and in combination. Trials were pseudo-randomized within and between visits to ensure that feedback modalities were presented to each participant in a different order and control for fatigue and learning effects. Each trial was 10 min long and separated into baseline, feedback, and washout phases. All data analysis was performed for early (strides 1–30), mid (strides 91–110), and late (strides 181–210) feedback phases and washout (strides 1–30). Mean soleus activity for individual strides (purple dots) was normalized to baseline activity. Between the pre-acclimation and post-acclimation visits, participants completed four, 20-min acclimation sessions where they received additional practice with both systems

Aim: The aim of this study is to evaluate how the modality of biofeedback may influence user response which has significant implications if systems are to be consistently adopted into clinical care.

Method: In this study, we evaluated the extent to which adolescents with CP (7M/1F; 14 [12.5,15.5] years) adapted their gait patterns during treadmill walking (6 min/modality) with audiovisual (AV), sensorimotor (SM), and combined AV + SM biofeedback before and after four acclimation sessions (20 min/session) and at a two-week follow-up. Both biofeedback systems were designed to target plantarflexor activity on the more-affected limb, as these muscles are commonly impaired in CP and impact walking function. SM biofeedback was administered using a resistive ankle exoskeleton and AV biofeedback displayed soleus activity from electromyography recordings during gait. At every visit, we measured the time-course response to each biofeedback modality to understand how the rate and magnitude of gait adaptation differed between modalities and following acclimation.

Results: Participants significantly increased soleus activity from baseline using AV + SM (42.8% [15.1, 59.6]), AV (28.5% [19.2, 58.5]), and SM (10.3% [3.2, 15.2]) biofeedback, but the rate of soleus adaptation was faster using AV + SM biofeedback than either modality alone. Further, SM-only biofeedback produced small initial increases in plantarflexor activity, but these responses were transient within and across sessions (p > 0.11). Following multi-session acclimation and at the two-week follow-up, responses to AV and AV + SM biofeedback were maintained.

Interpretation: This study demonstrated that AV biofeedback was critical to increase plantarflexor engagement during walking, but that combining AV and SM modalities further amplified the rate of gait adaptation. Beyond improving our understanding of how individuals may differentially prioritize distinct forms of afferent information, outcomes from this study may inform the design and selection of biofeedback systems for use in clinical care.

AACPDM 2023

Two people smiling and taking a selfie while standing in front of The Shirley Ryan Ability Lab sign. Mia has blonde hair. Charlotte has brown hair and is wearing glasses.

Lab members, Charlotte Caskey and Mia Hoffman attended the 2023 American Academy for Cerebral Palsy and Developmental Medicine (AACPDM) Annual Meeting in Chicago, IL on September 10-13, 2023.

Charlotte gave a poster presentation on “Short-Burst Interval Treadmill Training Increases Step Length and Stability for Children with Cerebral Palsy.”

Mia gave a podium presentation during the Early Detection and Diagnosis session on “Quantifying the Activity Levels of Toddlers with Down Syndrome Playing in a Partial Body Weight Support System.

Great work in the Windy City!

Amina El-Zatmah presents at the CNT 2023 Summer Undergraduate Research Symposium

Amina is wearing the Biomotum Spark exoskeleton while standing in front of her poster at her CNT presentation.This summer, the Steele Lab hosted undergraduate researcher, Amina El-Zatmah, from Santa Monica College. She finished up her 10-week summer Research Experience for Undergraduate (REU) by presenting at the 2023 Summer Undergraduate Research Symposium with the Center for Neurotechnology (CNT).

Amina gave a podium and poster presentation titled “Take A Step: The Effects of Transcutaneous Spinal Cord Stimulation and Exoskeleton Use on Step Length for Children with Cerebral Palsy“.

Amina was supported through mentorship from Charlotte Caskey, Siddhi Shrivastav, Chet Moritz, and Kat Steele.

Way to go, Amina!

 

ASB 2023 Recap

Charlotte is wearing a striped dress and black blazer standing in front of her poster at ASB.Four members of our lab – Kat, Elijah, Charlotte, & Mackenzie – attended ASB 2023 on August 8-11 in Knoxville, TN.

Elijah Kuska gave a podium presentation on “The effects of weakness, contracture, and altered control on walking energetics during crouch gait.”

Charlotte Caskey gave a poster presentation on “The effect of increased sensory feedback from neuromodulation and exoskeleton use on ankle co-contraction in children with cerebral palsy.”

Kat Steele co-hosted a workshop on “Writing a Successful NIH R01 Proposal.”

ASB 2024 will be hosted August 5-8, in Madison, WI.

 

 

Elijah is wearing a striped polo shirt and giving a presentation in front of a group of people at ASB.

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

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.