Reformulation in the phase plane enhances smoothness rater accuracy in stroke

The WGD-A Dataset of Assembly Line Working Gestures for Ergonomic Analysis and Work-Related Injuries Prevention

This paper wants to stress the importance of human movement monitoring to prevent musculoskeletal disorders by proposing the WGD—Working Gesture Dataset, a publicly available dataset of assembly line working gestures that aims to be used for worker’s kinematic analysis. It contains kinematic data acquired from healthy subjects performing assembly line working activities using an optoelectronic motion capture system. The acquired data were used to extract quantitative indicators to assess how the working tasks were performed and to detect useful information to estimate the exposure to the factors that may contribute to the onset of musculoskeletal disorders. The obtained results demonstrate that the proposed indicators can be exploited to early detect incorrect gestures and postures and, consequently to prevent work-related disorders. The approach is general and independent on the adopted motion analysis system. It wants to provide indications for safely performing working activities. For example, the proposed WGD can also be used to evaluate the kinematics of workers in real working environments thanks to the adoption of unobtrusive measuring systems, such as wearable sensors through the extracted indicators and thresholds.

Smoothness metrics for reaching performance after stroke. Part 1: which one to choose?

Background

Smoothness is commonly used for measuring movement quality of the upper paretic limb during reaching tasks after stroke. Many different smoothness metrics have been used in stroke research, but a ‘valid’ metric has not been identified. A systematic review and subsequent rigorous analysis of smoothness metrics used in stroke research, in terms of their mathematical definitions and response to simulated perturbations, is needed to conclude whether they are valid for measuring smoothness. Our objective was to provide a recommendation for metrics that reflect smoothness after stroke based on: (1) a systematic review of smoothness metrics for reaching used in stroke research, (2) the mathematical description of the metrics, and (3) the response of metrics to simulated changes associated with smoothness deficits in the reaching profile.

Methods

The systematic review was performed by screening electronic databases using combined keyword groups Stroke, Reaching and Smoothness. Subsequently, each metric identified was assessed with mathematical criteria regarding smoothness: (a) being dimensionless, (b) being reproducible, (c) being based on rate of change of position, and (d) not being a linear transform of other smoothness metrics. The resulting metrics were tested for their response to simulated changes in reaching using models of velocity profiles with varying reaching distances and durations, harmonic disturbances, noise, and sub-movements. Two reaching tasks were simulated; reach-to-point and reach-to-grasp. The metrics that responded as expected in all simulation analyses were considered to be valid.

Results

The systematic review identified 32 different smoothness metrics, 17 of which were excluded based on mathematical criteria, and 13 more as they did not respond as expected in all simulation analyses. Eventually, we found that, for reach-to-point and reach-to-grasp movements, only Spectral Arc Length (SPARC) was found to be a valid metric.

Conclusions

Based on this systematic review and simulation analyses, we recommend the use of SPARC as a valid smoothness metric in both reach-to-point and reach-to-grasp tasks of the upper limb after stroke. However, further research is needed to understand the time course of smoothness measured with SPARC for the upper limb early post stroke, preferably in longitudinal studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00949-6.

Whole-body kinematics and coordination in a complex dance sequence: Differences across skill levels

This study examined differences across skill levels in the kinematics of a complex, whole-body, asymmetrical, cyclical dance sequence, the 'Alternate Basic' in Cha-Cha-Cha, to determine whether observed differences were consistent with Bernstein's (1967) model of development of coordination. Bernstein proposed that with novel motor skills, beginners move their bodies rigidly and spastically, freezing kinematic degrees of freedom (DOF) to constrain the motor system. As the skill becomes practised, the DOF unfreeze and movements become more dynamic, allowing the integration of reactional elements (passive forces, moments, etc.) and organisation of more complex coordinative structures. Twenty-nine dancers - beginners (n = 10), intermediates (n = 10), experts (n = 9) - performed 12 cycles of the dance sequence (total duration ~60 s). Three-dimensional kinematic data from 36 joint angles were collected using a 14-camera infrared motion capture system. Most joints displayed increased amplitude and speed of movement, especially early in skill progression (beginner-intermediate stage), with no evidence of any decreases, showing that unfreezing occurred around the general movement pattern early. Speed of movement continued to increase later (intermediate-expert stage), as well as further unfreezing of the upper limbs. Changes to intra-limb couplings were limited, comprising some early reductions in coupling strength. Principal component analyses (PCA) showed that the structure of movement became more organised with increased skill. There was an early reduction in the number of coordinative structures, while later, movement was integrated more into the first coordinative structure. As predicted by Bernstein's coordination development model, therefore, the kinematic DOF unfroze as skill level progressed, leading to increased organisation of coordinative structures. The results of this study support the importance of a whole-body perspective in studies of coordination, with incorporation of kinetic variables in future research in order to examine the role that reactional elements play in motor skill development.

Clustering of Directions Improves Goodness of Fit in Kinematic Data Collected in the Transverse Plane During Robot-Assisted Rehabilitation of Stroke Patients

The kinematic character of hand trajectory in reaching tasks varies by movement direction. Often, direction is not included as a factor in the analysis of data collected during multi-directional reach tasks; consequently, this directionally insensitive model (DI) may be prone to type-II error due to unexplained variance. On the other hand, directionally specific models (DS) that account separately for each movement direction, may reduce statistical power by increasing the amount of data groupings. We propose a clustered-by-similarity (CS) in which movement directions with similar kinematic features are grouped together, maximizing model fit by decreasing unexplained variance while also decreasing uninformative sub-groupings. We tested model quality in measuring change over time in 10 kinematic features extracted from 72 chronic stroke patients participating in the VA-ROBOTICS trial, performing a targeted reaching task over 16 movement directions (8 targets, back- and forth from center) in the horizontal plane. Across 49 participants surviving a quality control sieve, 4.3 ± 1.1 (min: 3; max: 7) clusters were found among the 16 movement directions; clusters varied between participants. Among 49 participants, and averaged across 10 features, the better-fitting model for predicting change in features was found to be CS assessed by the Akaike Information criterion (61.6 ± 7.3%), versus DS (31.0 ± 7.8%) and DI (7.1 ± 7.1%). Confirmatory analysis via Extra Sum of Squares F-test showed the DS and CS models out-performed the DI model in head-to-head (pairwise) comparison in >85% of all specimens. Thus, we find overwhelming evidence that it is necessary to adjust for direction in the models of multi-directional movements, and that clustering kinematic data by feature similarly may yield the optimal configuration for this co-variate.

Product limit estimation for capturing of pressure distribution dynamics

Measurement of contact pressures at the wheelchair-seating interface is a critically important approach for laboratory research and clinical application in monitoring risk for pressure ulceration. As yet, measures obtained from pressure mapping are static in nature: there is no accounting for changes in pressure distribution over time, despite the well-known interaction between time and pressure in risk estimation. Here, we introduce the first dynamic analysis for distribution of pressure data, based on the Kaplan-Meier (KM) Product Limit Estimator (PLE) a ubiquitous tool encountered in clinical trials and survival analysis. In this approach, the pressure array-over-time data set is sub-sampled two frames at a time (random pairing), and their similarity of pressure distribution is quantified via a correlation coefficient. A large number (here: 100) of these frame pairs is then sorted into descending order of correlation value, and visualized as a KM curve; we build confidence limits via a bootstrap computed over 1000 replications. PLEs and the KM have robust statistical support and extensive development: the opportunities for extended application are substantial. We propose that the KM-PLE in particular, and dynamic analysis in general, may provide key leverage on future development of seating technology, and valuable new insight into extant datasets.

Biomechanical analysis of spasticity treatment in patients with multiple sclerosis

OBJECTIVES

New metrics for clinical spasticity are needed to assess motor performance, since scales such as the Ashworth and Tardieu are unreliable. Here, we assessed outcomes of baclofen treatment in patients with multiple sclerosis (MS) using biomechanical analysis of voluntary movements.

METHODS

Patients with MS and symptomatic limb spasticity were recruited for a pre-post baclofen titration study, along with age-matched healthy controls. Oral baclofen was titrated to optimize spasticity symptoms in all MS cases over 4 weeks. Clinical assessments included the Modified Ashworth Scale (MAS), Tardieu Scale (TS); elbow kinematics were measured via the Transient Acceleration Measurement Interface (TAMI); performance was measured as the score at 4 weeks minus the baseline score in all measures. Movement proficiency within TAMI was quantified through a scale-free smoothness measure, according to the regional excursion deviation (RED) from a constant-velocity approximant.

RESULTS

Twelve patients with MS [age: 47.8 ± 9.8 years; women: 4; disease duration: 20 ± 10 years; disease-modifying therapy use: 7; Expanded Disability Status Scale (EDSS): 6.8 ± 1.4] and eight age-matched healthy controls were evaluated concurrently (mean age: 49.5 ± 13.1 years; women = 3). In MS cases, no significant improvement in arm spasticity was observed with main effects: MAS: -41.6 ± 72.6 (p = 0.09); EDSS: -1.6 ± 10.4% (p = 0.49); and TS: -8.3 ± 2.1% (p = 0.32), -24.9 ± 63.6% (p = 0.42), and -30.7 ± 79.9% (p = 0.06), at slow, moderate, and fast speeds, respectively. However, voluntary motion smoothness, as measured by TAMI: RED, decreased significantly: 0.62 ± 0.08 versus 0.54 ± 0.09, p < 0.001, indicating significant increase in movement smoothness post treatment.

CONCLUSION

A simple biomechanical analysis of voluntary movements revealed a significant reduction of spasticity after 30 days of baclofen therapy in patients with MS that was not detected by clinical assessments.

Word generation affects continuous hand movements

Understanding interactions between cognitive and motor performance is an important theoretical and practical aim of motor neuroscience. Toward this aim, we invited university students to move one hand back and forth at a self-paced rate either in silence or while overtly generating words from semantic categories. The same participants also generated words without movement. Word generation affected manual performance but manual performance did not affect word generation. Only the timing, but not the spatial features, of the hand movements were influenced by word generation. The simplicity of our procedure argues for its future use, both for theoretical and practical purposes.

A generalized strategy for measuring performance in the velocity-position phase plane

Recent work has proposed the reformulation of smoothness measures derived from standard integrated squared jerk, as a function of position, not time. However, its promulgation was in the context of monotonic excursion data extracted from single degree-of-freedom (DOF) movements; the result was a formulation of a phase smoothness measure with limited generalizability. Here, we present a complete methodology for implementing the phase smoothness measure in arbitrary datasets, i.e. for multi-DOF movements with no assumptions of monotonicity in the kinematic profile. Additional suggestions are made for best practices.