Insights into motor performance deficits after stroke: an automated and refined analysis of the lower-extremity motor coordination test (LEMOCOT)

Background The lower-extremity motor coordination test (LEMOCOT) is a performance-based measure used to assess motor coordination deficits after stroke. We aimed to automatically quantify performance on the LEMOCOT and to extract additional performance parameters based on error analysis in persons with stroke (PwS) and healthy controls. We also aimed to explore whether these parameters provide additional information regarding motor control deficit that is not captured by the traditional LEMOCOT score. In addition, the associations between the LEMOCOT score, parameters of error and performance-based measures of lower-extremity impairment and gait were tested. Methods Twenty PwS (age: 62 ± 11.8 years, time after stroke onset: 84 ± 83 days; lower extremity Fugl-Meyer: 30.2 ± 3.7) and 20 healthy controls (age: 42 ± 15.8 years) participated in this cross-sectional exploratory study. Participants were instructed to move their big toe as fast and accurately as possible between targets marked on an electronic mat equipped with force sensors (Zebris FDM-T, 60 Hz). We extracted the contact surface area of each touch, from which the endpoint location, the center of pressure (COP), and the distance between them were computed. In addition, the absolute and variable error were calculated. Results PwS touched the targets with greater foot surface and demonstrated a greater distance between the endpoint location and the location of the COP. After controlling for the number of in-target touches, greater absolute and variable errors of the endpoint were observed in the paretic leg than in the non-paretic leg and the legs of controls. Also, the COP variable error differentiated between the paretic, non-paretic, and control legs and this parameter was independent of in-target counts. Negative correlations with moderate effect size were found between the Fugl Meyer assessment and the error parameters. Conclusions PwS demonstrated lower performance in all outcome measures than did controls. Several parameters of error indicated differences between legs (paretic leg, non-paretic leg and controls) and were independent of in-target touch counts, suggesting they may reflect motor deficits that are not identified by the traditional LEMOCOT score.

Lumbo-pelvic proprioception in sitting is impaired in subgroups of low back pain–But the clinical utility of the differences is unclear. A systematic review and meta-analysis

Background Altered spinal postures and altered motor control observed among people with non-specific low back pain have been associated with abnormal processing of sensory inputs. Evidence indicates that patients with non-specific low back pain have impaired lumbo-pelvic proprioceptive acuity compared to asymptomatic individuals. Objective To systematically review seated lumbo-pelvic proprioception among people with non-specific low back pain. Methods Five electronic databases were searched to identify studies comparing lumbo-pelvic proprioception using active repositioning accuracy in sitting posture in individuals with and without non-specific low back pain. Study quality was assessed by using a modified Downs and Black’s checklist. Risk of bias was assessed using an adapted tool for cross-sectional design and case–control studies. We performed meta-analysis using a random effects model. Meta-analyses included subgroup analyses according to disability level, directional subgrouping pattern, and availability of vision during testing. We rated the quality of evidence using the GRADE approach. Results 16 studies met the eligibility criteria. Pooled meta-analyses were possible for absolute error, variable error, and constant error, measured in sagittal and transverse planes. There is very low and low certainty evidence of greater absolute and variable repositioning error in seated tasks among non-specific low back pain patients overall compared to asymptomatic individuals (sagittal plane). Subgroup analyses indicate moderate certainty evidence of greater absolute and variable error in seated tasks among directional subgroups of adults with non-specific low back pain, along with weaker evidence (low-very low certainty) of greater constant error. Discussion Lumbo-pelvic proprioception is impaired among people with non-specific low back pain. However, the low certainty of evidence, the small magnitude of error observed and the calculated “noise” of proprioception measures, suggest that any observed differences in lumbo-pelvic proprioception may be of limited clinical utility. PROSPERO-ID CRD42018107671

Role of Proprioception in Slow and Rapid Movements

This study aimed to compare the contributions of sources of proprioception to the reproduction accuracy of relatively slower and more rapid arm movements. We recruited 34 volunteers and gave them dart throwing tasks under two different durations followed by joint position sense (JPS) tests and force sense (FS) tests at the elbow and the wrist. We found moderately positive correlations between slow movement performance and proprioceptive acuity with FS (wrist) and JPS (elbow), accounting for 52% of the absolute errors ( p < .001), and, with FS (wrist), accounting for 50% of the variable error ( p < .001). Moreover, we observed a smaller correlation between rapid movement performance and proprioceptive acuity, accounting for 17% of absolute errors with JPS (elbow; p = .008) and 11% of variable error ( p = .033). These results suggest that relatively slow movement performance is partly determined by performers’ proprioceptive acuity of the movement-related limbs. Relatively rapid movement performance is also affected by correctional proprioceptive feedback, though to a lesser degree.

Quantifying Below-Water Fluvial Geomorphic Change: The Implications of Refraction Correction, Water Surface Elevations, and Spatially Variable Error

Much of the geomorphic work of rivers occurs underwater. As a result, high resolutionquantification of geomorphic change in these submerged areas is important. Currently, to quantify thischange, multiple methods are required to get high resolution data for both the exposed and submergedareas. Remote sensing methods are often limited to the exposed areas due to the challenges imposedby the water, and those remote sensing methods for below the water surface require the collection ofextensive calibration data in-channel, which is time-consuming, labour-intensive, and sometimesprohibitive in dicult-to-access areas. Within this paper, we pioneer a novel approach for quantifyingabove- and below-water geomorphic change using Structure-from-Motion photogrammetry andinvestigate the implications of water surface elevations, refraction correction measures, and thespatial variability of topographic errors. We use two epochs of imagery from a site on the River Teme,Herefordshire, UK, collected using a remotely piloted aircraft system (RPAS) and processed usingStructure-from-Motion (SfM) photogrammetry. For the first time, we show that: (1) Quantification ofsubmerged geomorphic change to levels of accuracy commensurate with exposed areas is possiblewithout the need for calibration data or a dierent method from exposed areas; (2) there is minimaldierence in results produced by dierent refraction correction procedures using predominantlynadir imagery (small angle vs. multi-view), allowing users a choice of software packages/processingcomplexity; (3) improvements to our estimations of water surface elevations are critical for accuratetopographic estimation in submerged areas and can reduce mean elevation error by up to 73%;and (4) we can use machine learning, in the form of multiple linear regressions, and a Gaussian NaïveBayes classifier, based on the relationship between error and 11 independent variables, to generate ahigh resolution, spatially continuous model of geomorphic change in submerged areas, constrained byspatially variable error estimates. Our multiple regression model is capable of explaining up to 54%of magnitude and direction of topographic error, with accuracies of less than 0.04 m. With on-goingtesting and improvements, this machine learning approach has potential for routine application inspatially variable error estimation within the RPAS–SfM workflow.

Can Stroboscopic Training Improve Time-to-Collision Judgments of Laterally Moving Objects?

We investigated whether effects of stroboscopic training on time-to-collision (TTC) judgments depend on the optical flow pattern. Prior research showed that TTC judgments of lateral motion reflected benefits of stroboscopic viewing (Ballester, Huertas, Uji, & Bennett, 2017; Smith & Mitroff, 2012), but TTC judgments of approach motion did not reflect such benefits (Braly & DeLucia, 2017). This discrepancy may be due to differences in the optical flow patterns between lateral and approach motion. In lateral motion, the optical flow pattern is linear; the change in the object’s optical position is the same throughout its trajectory. In approach motion, the optical flow pattern is non-linear; the change in the object’s optical size increases as it gets closer to the eye. It has been proposed that this difference in the optical flow pattern underlies the greater accuracy of TTC judgments that occur with lateral motion compared to approach motion (Schiff & Oldak, 1990). In the current study, we measured effects of stroboscopic viewing on TTC judgments of lateral motion using identical methods in our prior study of approach motion. Although prior research demonstrated potential benefits of stroboscopic viewing for judgments of lateral motion, the stimulus was visible when the response was made. Prior demonstrations that the object’s trajectory (and thus nature of the optic flow) affects TTC judgments were demonstrated with prediction-motion (PM) tasks in which the object disappeared before a response was made. The two types of tasks are putatively based on different visual information and cognitive processes (Tresilian, 1995). Thus, we used a PM task in the current study. Participants viewed computer simulations of an object that moved laterally toward a target and then disappeared. They pressed a mouse button at the exact time that they thought the object would hit the target. Mean constant error and variable error of TTC judgments were compared among intervention conditions of stroboscopic training (5 minutes in duration), continuous viewing (practice without feedback), and a control filler task. Performance was measured during four sessions—pre-test, intervention, immediately after intervention, and 10 minutes after intervention. When distance was far, participants in the stroboscopic intervention condition were, on average, less variable at the 10-minute posttest compared to the pretest. Although the difference was not statistically significant, it is noteworthy that performance did not significantly degrade over time as it did in the filler condition, and in our prior study of approach motion (Braly & DeLucia, 2017). Such results suggest that stroboscopic training can protect against performance degradation over time (due to fatigue, monotony, etc). A protective effect also was observed in the continuous vision condition (performance did not degrade over time); however, observations of the means suggest that performance would have degraded over time if longer training was completed. When TTC was 3.0 s, performance in the stroboscopic intervention was not more variable in the immediate posttest compared to the pretest and, more importantly, was less variable at the ten-minute posttest (although p = 0.0515). Our results show that under specific conditions (when TTC was 3.0 s; when distance was far) stroboscopic training can protect against performance degradation over time; that is, variable error did not increase. Such protective effects of stroboscopic training were not observed in our earlier study of approach motion (Braly & DeLucia, 2017). Neither study showed a significant effect of stroboscopic training on constant error. The implication is that the effects of stroboscopic training depend on the nature of the optical flow pattern. In future studies, it is important to systematically determine the conditions under which stroboscopic training can improve performance. Results will have important implications for traffic safety and for driver training programs.