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

 Oh for fucks sake, this is just assessments. Useless for survivors recovery.

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

 

• Shirley Handelzalts,
• Yogev Koren,
• Noy Goldhamer,
• Adi Yeshurun-Tayer,
• Yisrael Parmet,
• Lior Shmuelof &
• Simona Bar-Haim 

Journal of NeuroEngineering and Rehabilitation volume 18, Article number: 155 (2021) Cite this article

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Abstract

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.

Introduction

Motor coordination can be defined as the ability to produce context-dependent organized movements in spatial and temporal domains [1, 2]. During walking, relative motion between body segments needs to be adaptable to accommodate internal and external demands, in turn allowing for accurate foot placement and safe mobility [3,4,5]. Stroke survivors often demonstrate impaired motor coordination of the upper and lower extremities [6] that may cause limitations in the performance of daily activities, reduced participation, and decreased quality of life [7].

Performance-based measures of coordination for persons with neurological disorders are often based on time and criterion (e.g., Finger-to-Nose test [8], lower-extremity motor coordination test [9]), however, they do not quantify performance quality (i.e., how well movements are performed, whether they reflect a return toward premorbid pattern). In the Fugl Meyer Assessment, a commonly used measure to evaluate lower and upper extremity impairments after stroke, coordination is measured as the difference in time to alternately touch the targets five times between the more- and less-affected extremity [10]. In addition, the endpoint trajectory straightness/smoothness (tremor) and the precision (dysmetria) are estimated. However, the performance of these components is estimated on a 3-level rating scale [10], which limits the ability to detect and quantify small changes over time. A quantitative evaluation of the endpoint movement to target in terms of smoothness, straightness, error magnitude, speed and range of joint motion might provide a more refined and informative scale to characterize motor control deficits after stroke than merely time and criterion [11]. Here, we focus on quantifying the error (i.e., accuracy) of the performance in the lower-extremity motor coordination test (LEMOCOT) in persons with stroke (PwS).

The LEMOCOT is a performance-based measure of coordination [9]. In the test, performed while sitting, participants are instructed to move their lower extremity as fast and accurately as possible and alternately touch with their big toe a proximal and a distal target on the floor. The number of targets touched in 20 s constitutes the score. The LEMOCOT demonstrated appropriate measurement properties i.e. intra-, inter-rater, and test–retest reliability and construct validity in PwS [12]. In the current exploratory study, the LEMOCOT was performed on an electronic mat equipped with force sensors to quantify motor performance in terms of accuracy (i.e., endpoint absolute error) and consistency (i.e., endpoint variable error). Our assumption was that in a well-controlled movement, the endpoint location and the center of pressure (COP) location of the foot would be congruent to accurately reach the target, whereas in a less controlled movement (e.g., ‘throwing’ the leg towards the test’s targets) they would not. Therefore, we computed the accuracy and consistency for both—the endpoint location and the COP location. These measures might provide a more detailed and comprehensive assessment of motor deficits after stroke and may enable us to capture even subtle changes over time or in response to training interventions that may not be reflected in the traditional score (i.e., number of in target touches performed in 20 s). Furthermore, understanding how well PwS can perform targeted reaching with the paretic and non-paretic leg may be relevant for rehabilitation in terms of locomotor and balance control tasks, especially in activities where the margin for error in foot placement is small, such as negotiating cluttered travel paths or stepping over an obstacle.

For study purposes, we developed an algorithm to automatically compute the traditional LEMOCOT score of ‘in-target’ touch counts and calculate additional parameters of motor performance. Therefore, we aimed to (1) estimate the validity of our algorithm and script, (2) quantify motor performance in the LEMOCOT using parameters of error in PwS and healthy controls, (3) investigate whether these parameters provide different or additional information to that provided by the traditional score, and finally, (4) to determine the association between the traditional LEMOCOT score, parameters of error and performance-based measures of lower extremity motor impairments and gait.

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