During Microsoft’s annual Ability Summit, they announced a new partnership with the University of Washington to establish the Center for Research and Education on Accessible Technology (CREATE) and kicked-off the collaboration with an inaugural investment of $2.5 million. CREATE is an interdisciplinary team whose mission is to make technology, and the world, more accessible.
The CREATE leadership will be comprised of six campus departments and three different colleges including the Steele lab’s own Heather Feldner and Katherine M. Steele. This fantastic news was featured on The Seattle Times and Greek Wire.
Get excited and help us congratulate Heather, Kat, and all those involved and cheer them on to CREATE!
These results suggest that control theory modeling can provide a platform to successfully quantify device performance in the absence of errors arising from motor impairments
Photo (top and bottom) of a user using a slider (top) and muscles (bottom) to control a cursor on the screen. (Top image) Side image of user. User rests their elbow and pinches the slider and moves the slider towards and away from their body to control the cursor. (Bottom image) Side image of user. User is strapped to a rigid device holding a bar with hands supinated towards the ceiling, with the forearms at a 90 degree angle from the upper arms. Electrodes are placed on the biceps and triceps and labelled. Arrows pointing up and down indicate that users move their arm up and down to control the cursor.
Background:Manual device interaction requires precise coordination which may be difficult for users with motor impairments. Muscle interfaces provide alternative interaction methods that may enhance performance, but have not yet been evaluated for simple (eg. mouse tracking) and complex (eg. driving) continuous tasks. Control theory enables us to probe continuous task performance by separating user input into intent and error correction to quantify how motor impairments impact device interaction
Aim: Propose and extend an experimental and analytical method to guide future development of accessible interfaces like muscle interfaces using control theory
Method: We compared the effectiveness of a manual versus a muscle interface for eleven users without and three users with motor impairments performing continuous tasks.
Results: Both user groups preferred and performed better with the muscle versus the manual interface for the complex continuous task.
Interpretation: Results suggest muscle interfaces and algorithms that can detect and augment user intent may be especially useful for future design of interfaces for continuous tasks.
Momona also gave a phenomenal talk on this paper last week in the University of Washington’s ‘DUB Shorts’ series (video posted below). Nice job Momona!
Congratulations to Alyssa Spomer for being awarded the Husky 100. This award recognizes 100 students who are making the most of their time at UW through coursework, research, volunteer and leadership efforts, internships, and jobs: they have created their own Husky Experience.
Please help us in congratulating and welcoming Alyssa into the 2020 Husky 100 class!
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.
This study demonstrated that muscle activations estimated from static optimization using generic musculoskeletal modeling does not accurately predict EMG profiles for children with CP or TD peers. Constraining activation patterns to experimentally measured synergies increased estimated muscle stresses, but did not improve the estimation of muscle activations for either group.
Constraining simulated activations in inverse dynamic simulations to subject-specific synergies alone does not improve estimation of muscle activations during gait for generic musculoskeletal models.
Background
Neuromusculoskeletal simulation provides a promising platform to inform the design of assistive devices or inform rehabilitation. For these applications, a simulation must be able to accurately represent the person of interest, such as an individual with a neurologic injury. If a simulation fails to predict how an individual recruits and coordinates their muscles during movement, it will have limited utility for informing design or rehabilitation. While inverse dynamic simulations have previously been used to evaluate anticipated responses from interventions, like orthopaedic surgery or orthoses, they frequently struggle to accurately estimate muscle activations, even for tasks like walking. The simulated muscle activity often fails to represent experimentally measured muscle activity from electromyographic (EMG) recordings. Research has theorized that the nervous system may simplify the range of possible activations used during dynamic tasks, by constraining activations to weighted groups of muscles, referred to as muscle synergies. Synergies are altered after neurological injury, such as stroke or cerebral palsy (CP), and may provide a method for improving subject-specific models of neuromuscular control.
Purpose
The aim of this study was to test whether constraining simulation to synergies could improve estimated muscle activations compared to EMG data.
Method
We evaluated modeled muscle activations during gait for six typically developing children (TD) and six children with CP. Muscle activations were estimated with: 1) static optimization (SO), minimizing muscle activations squared, and 2) synergy static optimization (SynSO), minimizing synergy activations squared using the weights identified from EMG data for 2-5 synergies.
Results
While SynSO caused changes in estimated activations compared to SO, the correlation to EMG data was not higher in SynSO than SO for either TD or CP groups . The correlations to EMG were higher in CP than TD for both SO (CP: 0.48, TD: 0.36) and SynSO (CP: 0.46, TD: 0.26 for 5 synergies). Constraining activations to SynSO caused the simulated muscle stress to increase compared to SO for all individuals, causing a 157% increase with two synergies.
Conclusions
These results suggest that constraining simulated activations in inverse dynamic simulations to subject-specific synergies alone does not improve estimation of muscle activations during gait for generic musculoskeletal models.
During Microsoft’s annual Ability Summit, they announced a new partnership with the University of Washington to establish the Center for Research and Education on Accessible Technology (CREATE) and kicked-off the collaboration with an inaugural investment of $2.5 million. CREATE is an interdisciplinary team whose mission is to make technology, and the world, more accessible.
