Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control.

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. Interestingly, however, the manifold's absolute location demonstrated day-to-day drift. Strikingly, representational statistics, especially variance, could be flexibly regulated to increase discernability during BCI control without somatotopic changes. Discernability strengthened with practice and was specific to the BCI, demonstrating remarkable contextual specificity. Accounting for drift, and leveraging the flexibility of representations, allowed neuroprosthetic control of a robotic arm and hand for over 7 months without recalibration. Our study offers insight into how electrocorticography can both track representational statistics across long periods and allow long-term complex neuroprosthetic control.

Reachable Workspace and Proximal Function Measures for Quantifying Upper Limb Motion.

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. However, these motions may not be biologically consistent, which can result in noisy, inaccurate movements. This paper introduces a rigid body modelling method to enforce biological feasibility of the recovered motions. This method is evaluated on an existing depth camera assessment: the reachable workspace (RW) measure for assessing gross shoulder function. As a rigid body model is used, position estimates of new proximal targets can be added, resulting in a proximal function (PF) measure for assessing a subject's ability to touch specific body landmarks. The accuracy, and repeatability of these measures is assessed on ten asymptomatic subjects, with and without rigid body constraints. This analysis is performed both on a low-cost depth camera system and a gold-standard active motion capture system. The addition of rigid body constraints was found to improve accuracy and concordance of the depth camera system, particularly in lateral reaching movements. Both RW and PF measures were found to be feasible candidates for clinical assessment, with future analysis needed to determine their ability to detect changes within specific patient populations.

ISSLS PRIZE IN BIOENGINEERING SCIENCE 2019: biomechanical changes in dynamic sagittal balance and lower limb compensatory strategies following realignment surgery in adult spinal deformity patients.

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. Little is known about the compensatory biomechanical strategies for stabilizing sagittal balance during functional movements in ASD patients. METHODS: We collected in-clinic motion data from 15 ASD patients and 10 controls during an unassisted sit-to-stand (STS) functional maneuver. Joint motions were measured using noninvasive 3D depth mapping sensor technology. Mathematical methods were used to attain high-fidelity joint-position tracking for biomechanical modeling. This approach provided reliable measurements for biomechanical behaviors at the spine, hip, and knee. These included peak sagittal vertical axis (SVA) over the course of the STS, as well as forces and muscular moments at various joints. We compared changes in dynamic sagittal balance (DSB) metrics between pre- and post-surgery and then separately compared pre- and post-surgical data to controls. RESULTS: Standard radiographic and patient-reported outcomes significantly improved following realignment surgery. From the DSB biomechanical metrics, peak SVA and biomechanical loads and muscular forces on the lower lumbar spine significantly reduced following surgery (- 19 to - 30%, all p < 0.05). In addition, as SVA improved, hip moments decreased (- 28 to - 65%, all p < 0.05) and knee moments increased (+ 7 to + 28%, p < 0.05), indicating changes in lower limb compensatory strategies. After surgery, DSB data approached values from the controls, with some post-surgical metrics becoming statistically equivalent to controls. CONCLUSIONS: Longitudinal changes in DSB following successful multi-level spinal realignment indicate reduced forces on the lower lumbar spine along with altered lower limb dynamics matching that of controls. Inadequate improvement in DSB may indicate increased risk of post-surgical mechanical failure. These slides can be retrieved under Electronic Supplementary Material.

Estimating Sit-to-Stand Dynamics Using a Single Depth Camera.

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. An allometrically scaled, sagittal plane dynamic model is used to estimate the joint torques at the ankles, knees, hips, and low back, as well as the torso momenta, and shear and normal loads at the L5-S1 disk. These dynamic metrics are applied to the sit-to-stand motion and validated against a gold-standard biomechanical system consisting of full-body active motion-capture and force-sensing systems. The metrics obtained from the proposed method were found to have excellent concordance with peak metrics that are consistent with prior biomechanical studies. This suggests the feasibility of using this system for rapid clinical assessment, with applications in diagnostics, longitudinal tracking, and quantifying patient recovery.

Simple Spline Representation for Identifying Sit-to-Stand Strategies.

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. This formulation is inherently differentiable, defines a clear start and end point of the motion, and allows for secondary analysis of dynamic and energetic effects. This method is tested on two healthy subjects performing four different standing strategies. The spline method was found to accurately capture the standing action, with mean absolute errors of 1-2 cm for joint position, and 2-3 degrees angular error across the different standing strategies. Analysis of the spline trajectories revealed strategy-specific differences in kinematic, kinetic, and dynamic bio-markers. This suggests that low order splines can be used to accurately capture variations in sit-to-stand actions.

Passive Knee Assistance Affects Whole-Body Biomechanics During Sit-to-Stand.

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. Initial human experiments were conducted with two subjects under two foot-placement conditions. The human and device kinematics and dynamics were modelled, allowing for the assessment of the biomechanical effects of the device. The assistance resulted in a decrease in the human knee torque as well as changes in whole-body biomechanics, notably an increase in the linear momentum of the upper body and a decrease in the anterior excursion of the center of mass. These results indicate that single-joint assistance at the knee has the potential to both facilitate successful STS and positively alter whole-body biomechanics.

Kinematic and Kinetic Validation of an Improved Depth Camera Motion Assessment System Using Rigid Bodies.

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. In this work, we present a fast framework for adding biomechanical constraints to the joint estimates provided by a depth camera system. We also present a new model for the lower lumbar joint angle. We validate key joint position, angle, and velocity measurements against a gold standard active motion-capture system on ten healthy subjects performing sit to stand (STS). Our method showed significant improvement in mean absolute error and intraclass correlation coefficients for the recovered joint angles and position-based metrics. These improvements suggest that depth cameras can provide an accurate and clinically viable method of rapidly assessing the kinematics and kinetics of the STS action, providing data for further analysis using biomechanical or machine learning methods.

Tracking Kinematic and Kinetic Measures of Sit to Stand using an Instrumented Spine Orthosis.

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. This paper introduces an Instrumented Spine Orthosis (ISO) that can capture the motions of the subjects torso without requiring the use of a control computer or other dedicated motion capture equipment. This system is used to collect the peak torso angles and velocities for a single subject performing sit-to-stand actions. The accuracy of the ISO is evaluated using motion capture, during different sit-to-stand protocols designed to highlight motion changes that have been seen in subjects with reduced mobility. This system was found to provide reliable measurements of these kinematic and kinetic torso measures across all tested motions, demonstrating the potential for the use of Instrumented Spine Orthotics to provide quantitative measures during the surgical recovery process.

A functional method for generating individualized spine models from motion-capture data.

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. These models are driven by the motion of the thorax and pelvis as observed by eight surface landmarks. We apply this method to experimental data from ten subjects performing flexion/extension and sit-to-stand motions. The recovered functional models are assessed against an allometric model though the analysis of marker residuals. We found that the functional models provide lower residuals than the allometric methods. Between the functional models, the two-joint model provided lower residuals with less sensitivity to the training action, while the one-joint model should be trained on the motion of interest.

Fusing motion-capture and inertial measurements for improved joint state recovery: An application for sit-to-stand actions.

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. This paper introduces an algorithm to fuse motion-capture and inertial measurements to recover the full state during a sit-to-stand task. This algorithm is then compared to three other methods: Kalman filtering on motion-capture or inertial measurements alone and the standard angular recovery/differentiation method. It is shown that the fusion of both optical and inertial measurements reduce the ripple and offset artefacts which become pronounced in high acceleration human motions.