Publications by authors named "Sarah Seko"

The nervous system needs to balance the stability of neural representations with plasticity. It is unclear what is the representational stability of simple actions, particularly those that are well-rehearsed in humans, and how it changes in new contexts. Using an electrocorticography brain-computer interface (BCI), we found that the mesoscale manifold and relative representational distances for a repertoire of simple imagined movements were remarkably stable.

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There are a lack of quantitative measures for clinically assessing upper limb function. Conventional biomechanical performance measures are restricted to specialist labs due to hardware cost and complexity, while the resulting measurements require specialists for analysis. Depth cameras are low cost and portable systems that can track surrogate joint positions.

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The sit-to-stand (STS) motion is an activity of daily living which requires significant torque generation and coordinated movement at multiple joints. It is therefore important to consider the whole-body biomechanics when designing an assistive device for STS. In this study, a passive elastic orthotic was developed which provides bilateral knee extension assistance.

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Standing from a seated position is an activity of daily living and a common clinical test of strength and balance. While this action is well-studied biomechanically, there remains a need for a clear modelling method for appropriately capturing performance and discriminating between standing strategies. This paper presents a simple framework for representing the rise from a chair as a set of splines.

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Study Design: A longitudinal cohort study.

Objective: To define a set of objective biomechanical metrics that are representative of adult spinal deformity (ASD) post-surgical outcomes and that may forecast post-surgical mechanical complications. Current outcomes for ASD surgical planning and post-surgical assessment are limited to static radiographic alignment and patient-reported questionnaires.

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Kinetic and dynamic motion analysis provides quantitative, functional assessments of human ability that are unobtainable through static imaging methods or subjective surveys. While biomechanics facilities are equipped to perform this measurement and analysis, the clinical translation of these methods is limited by the specialized skills and equipment needed. This paper presents and validates a method for estimating dynamic effects such as joint torques and body momenta using a single depth camera.

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A representative model is necessary for the analysis of spine kinematics and dynamics during motion. Existing models, based on stationary imaging or cadaveric data, may not be accurate through the full range of spinal motion or for clinical populations. In this paper, we propose a functional method for estimating subject-specific spinal joint centers, generating a one-joint or two-joint kinematic model of the spine.

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Age related spinal deformity is becoming an increasingly prevalent problem, resulting in decreased quality of life. While spinal deformity can be corrected via surgical intervention, a large number of people with spinal fusions require follow-up surgery due to further degeneration. The identification of changes to a subjects kinematics and kinetics post-surgery are limited by a lack of methods to collect patient specific motion data over the course of surgical recovery.

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The study of joint kinematics and dynamics has broad clinical applications, including the identification of pathological motions or compensation strategies and the analysis of dynamic stability. High-end motion capture systems, however, are expensive and require dedicated camera spaces with lengthy setup and data processing commitments. Depth cameras, such as the Microsoft Kinect, provide an inexpensive, marker-free alternative at the sacrifice of joint-position accuracy.

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The estimate of joint angles, velocities, and accelerations is a key component of biomechanical modelling. The literature presents a variety of sensing modalities and algorithms to recover the full joint state, with tuning parameters varying between different applications, actions, and limbs. Comparisons between these methods are frequently limited to angles only, without comparison between the joint velocities and accelerations.

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