scholarly journals Relationships Between Stepping-Reaction Movement Patterns and Clinical Measures of Balance, Motor Impairment, and Step Characteristics After Stroke

2021 ◽  
Author(s):  
Courtney L Pollock ◽  
Michael A Hunt ◽  
S Jayne Garland ◽  
Tanya D Ivanova ◽  
James M Wakeling

Abstract Objective Successful stepping reactions, led by either the paretic or nonparetic leg, in response to a loss of balance are critical to safe mobility poststroke. The purpose of this study was to measure sagittal plane hip, knee, ankle, and trunk kinematics during 2-step stepping reactions initiated by paretic and nonparetic legs of people who had stroke and a control group. Methods Principal component analysis (PCA) was used to reduce the data into movement patterns explaining interlimb coordination of the stepping and stance legs. Correlations among principal components loading scores and clinical measures of balance ability (as measured on the Community Balance and Mobility scale), motor impairment (as measured on the foot and leg sections of the Chedoke-McMaster Stroke Assessment), and step characteristics (length and velocity) were used to examine the effect of stroke on stepping reaction movement patterns. Results The first 5 principal components explained 95.9% of the movement pattern of stepping reactions and differentiated between stepping reactions initiated by paretic legs, nonparetic legs, or the legs of controls. Moderate-strong associations (ρ/r > 0.50) between specific principal component loading scores and clinical measures and step characteristics were dependent on the initiating leg. Lower levels of motor impairment, higher levels of balance ability, and faster and longer steps were associated with stepping reactions initiated by the paretic leg that comprised paretic leg flexion and nonparetic leg extension. Step initiation with the nonparetic leg showed associations between higher scores on clinical measures and movement patterns of flexion in both paretic and nonparetic legs. Conclusions Movement patterns of stepping reactions poststroke were influenced by the initiating leg. After stroke, specific movement patterns showed associations with clinical measures depending on the initiating leg, suggesting that these movement patterns are important to retraining of stepping reactions. Specifically, use of flexion patterning and assessment of between-leg pattern differentiation may be important aspects to consider during retraining of stepping reactions poststroke. Impact Evidence-based interventions targeting balance reactions are still in their infancy. This investigation of stepping reactions poststroke addresses a major gap in research.

Healthcare ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1321
Author(s):  
Wenjing Quan ◽  
Huiyu Zhou ◽  
Datao Xu ◽  
Shudong Li ◽  
Julien S. Baker ◽  
...  

Kinematics data are primary biomechanical parameters. A principal component analysis (PCA) of waveforms is a statistical approach used to explore patterns of variability in biomechanical curve datasets. Differences in experienced and recreational runners’ kinematic variables are still unclear. The purpose of the present study was to compare any differences in kinematics parameters for competitive runners and recreational runners using principal component analysis in the sagittal plane, frontal plane and transverse plane. Forty male runners were divided into two groups: twenty competitive runners and twenty recreational runners. A Vicon Motion System (Vicon Metrics Ltd., Oxford, UK) captured three-dimensional kinematics data during running at 3.3 m/s. The principal component analysis was used to determine the dominating variation in this model. Then, the principal component scores retained the first three principal components and were analyzed using independent t-tests. The recreational runners were found to have a smaller dorsiflexion angle, initial dorsiflexion contact angle, ankle inversion, knee adduction, range motion in the frontal knee plane and hip frontal plane. The running kinematics data were influenced by running experience. The findings from the study provide a better understanding of the kinematics variables for competitive and recreational runners. Thus, these findings might have implications for reducing running injury and improving running performance.


Author(s):  
Nichole Houle ◽  
Aaron M. Johnson

Purpose The purpose of this study was to investigate the relationships among subjective auditory-perceptual ratings of vocal quality, objective acoustic and aerodynamic measures of vocal function, and patient-perceived severity of their vocal complaint. Method This study was a retrospective chart review of adult patients evaluated at a single outpatient center over a 1.5-year time period. Twenty-two clinical objective and subjective measures of voice were extracted from 676 charts (310 males, 366 females). To identify the underlying concepts addressed in an initial voice assessment, principal component analyses were conducted for males and females to account for sex differences. Linear regression models were conducted to examine the relationship between the principal components and patient perceived severity. Results Seven principal components were identified for both sexes and accounted for 75% and 71% of the variance in the clinical measures, respectively. Of these seven principal components, only two predicted male patient perceived severity, which accounted for 22% of the variance. In contrast, four principal components predicted female patient perceived severity of their voice disorder and accounted for 19% of the variance. Conclusions The results highlight the underlying aspects of vocal quality and functioning that are evaluated during an initial assessment. Male and female patients differ in which of these components may contribute self-perceived severity of a voice disorder. Identifying these underlying components may support clinical decision making when developing a clinical protocol and highlights the overlap between patient concerns and clinical measures. Supplemental Material https://doi.org/10.23641/asha.16879603


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Mingli Xia ◽  
Shuai Guo

This study evaluates the static balance ability of human body based on a lower limb rehabilitation robot. According to the balance parameters obtained from the movement trajectory of the center of human pelvis, SPSS statistical software was used to verify that there was a significant difference between the two groups ( p < 0.01 ). Principal component analysis is used to allocate the weight of each parameter and establish the comprehensive evaluation value. The comprehensive evaluation value of the control group was 0.383 ± 0.038, and the experimental group was 0.875 ± 0.136. When the subject’s comprehensive evaluation value is between 0.739 and 1.011, it indicates the presence of balance dysfunction, and when it is between 0.345 and 0.421, it indicates that the balance of the lower limbs of the subject is normal. Experimental results show that this evaluation method can objectively and quantitatively reflect the static equilibrium state of human body.


Author(s):  
Farzaneh Yazdani ◽  
Mohsen Razeghi ◽  
Mohammad Taghi Karimi ◽  
Hadi Raeisi Shahraki ◽  
Milad Salimi Bani

Despite the theoretical link between foot hyperpronation and biomechanical dysfunction of the pelvis, the literature lacks evidence that confirms this assumption in truly hyperpronated feet subjects during gait. Changes in the kinematic pattern of the pelvic segment were assessed in 15 persons with hyperpronated feet and compared to a control group of 15 persons with normally aligned feet during the stance phase of gait based on biomechanical musculoskeletal simulation. Kinematic and kinetic data were collected while participants walked at a comfortable self-selected speed. A generic OpenSim musculoskeletal model with 23 degrees of freedom and 92 muscles was scaled for each participant. OpenSim inverse kinematic analysis was applied to calculate segment angles in the sagittal, frontal and horizontal planes. Principal component analysis was employed as a data reduction technique, as well as a computational tool to obtain principal component scores. Independent-sample t-test was used to detect group differences. The difference between groups in scores for the first principal component in the sagittal plane was statistically significant (p = 0.01; effect size = 1.06), but differences between principal component scores in the frontal and horizontal planes were not significant. The hyperpronation group had greater anterior pelvic tilt during 20%–80% of the stance phase. In conclusion, in persons with hyperpronation we studied the role of the pelvic segment was mainly to maintain postural balance in the sagittal plane by increasing anterior pelvic inclination. Since anterior pelvic tilt may be associated with low back symptoms, the evaluation of foot posture should be considered in assessing the patients with low back and pelvic dysfunction.


2006 ◽  
Vol 27 (2) ◽  
pp. 87-92 ◽  
Author(s):  
Willem K.B. Hofstee ◽  
Dick P.H. Barelds ◽  
Jos M.F. Ten Berge

Hofstee and Ten Berge (2004a) have proposed a new look at personality assessment data, based on a bipolar proportional (-1, .. . 0, .. . +1) scale, a corresponding coefficient of raw-scores likeness L = ΢XY/N, and raw-scores principal component analysis. In a normal sample, the approach resulted in a structure dominated by a first principal component, according to which most people are faintly to mildly socially desirable. We hypothesized that a more differentiated structure would arise in a clinical sample. We analyzed the scores of 775 psychiatric clients on the 132 items of the Dutch Personality Questionnaire (NPV). In comparison to a normative sample (N = 3140), the eigenvalue for the first principal component appeared to be 1.7 times as small, indicating that such clients have less personality (social desirability) in common. Still, the match between the structures in the two samples was excellent after oblique rotation of the loadings. We applied the abridged m-dimensional circumplex design, by which persons are typed by their two highest scores on the principal components, to the scores on the first four principal components. We identified five types: Indignant (1-), Resilient (1-2+), Nervous (1-2-), Obsessive-Compulsive (1-3-), and Introverted (1-4-), covering 40% of the psychiatric sample. Some 26% of the individuals had negligible scores on all type vectors. We discuss the potential and the limitations of our approach in a clinical context.


Methodology ◽  
2016 ◽  
Vol 12 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Gregor Sočan

Abstract. When principal component solutions are compared across two groups, a question arises whether the extracted components have the same interpretation in both populations. The problem can be approached by testing null hypotheses stating that the congruence coefficients between pairs of vectors of component loadings are equal to 1. Chan, Leung, Chan, Ho, and Yung (1999) proposed a bootstrap procedure for testing the hypothesis of perfect congruence between vectors of common factor loadings. We demonstrate that the procedure by Chan et al. is both theoretically and empirically inadequate for the application on principal components. We propose a modification of their procedure, which constructs the resampling space according to the characteristics of the principal component model. The results of a simulation study show satisfactory empirical properties of the modified procedure.


2020 ◽  
Vol 4 (11) ◽  
pp. 676-681
Author(s):  
V.V. Sapozhnikova ◽  
◽  
A.L. Bondarenko ◽  

Aim: to determine the association between clinical laboratory parameters, the production of cytokines (IL-17A, -23, -33, -35), and specific IgM and IgG in the serum of patients with Lyme borreliosis without erythema migrans. Patients and Methods: complete blood count, the concentrations of IL-17A, -23, -33, -35, and the levels of specific IgM and IgG were measured during acute infection and convalescence (n=30). The control group included age- and sex-matched healthy individuals (n=30). Statistical analysis was performed using the StatSoft Statistica v 10.0 software (parametric and non-parametric methods and multifactorial analysis, i.e., principal component analysis). Results: most (80%) patients with Lyme borreliosis without erythema migrans are the people of working age. In most patients, the combination of the specific antibodies against Borrelia afzelii and Borrelia garinii (76.7%) and severe intoxication and inflammatory process (100%) were detected. Moderate and severe disease associated with meningism was diagnosed in 90% and 10%, respectively. The mean duration of hectic period was 8.3±1.27 days. Abnormal ECG was reported in 40% of patients, i.e., conduction abnormalities in 20%, sinus bradycardia in 16.7%,and sinus tachycardia in 3.3%. The clinical laboratory signs of hepatitis without jaundice were identified in 26.7%. During treatment, the significant reduction in band and segmented neutrophil counts as well as the significant increase in platelet count were revealed compared to these parameters at admission. Abnormal cytokine levels (i.e., the increase in IL-17A, -23, -33 and the deficiency of IL-35) were detected. Conclusions: multifactorial analysis has demonstrated that the severity of immunological abnormalities in patients with Lyme borreliosis without erythema migrans is associated with fever, cardiac and liver disorders, the high levels of IL-23 and IL-33, and the lack of IL-35 and specific IgM and IgG. KEYWORDS: tick-borne borreliosis, Lyme disease without erythema migrans, clinical laboratory signs, cytokines, specific antibodies, multifactorial analysis, principal component analysis. FOR CITATION: Sapozhnikova V.V., Bondarenko A.L. Multifactorial analysis of clinical laboratory signs, the levels of IL-17A, IL-23, IL-33, IL-35, and specific antibodies in the serum of patients with Lyme borreliosis without erythema migrans. Russian Medical Inquiry. 2020;4(11):676–681. DOI: 10.32364/2587-6821-2020-4-11-676-681.


2006 ◽  
Vol 1 (1) ◽  
Author(s):  
K. Katayama ◽  
K. Kimijima ◽  
O. Yamanaka ◽  
A. Nagaiwa ◽  
Y. Ono

This paper proposes a method of stormwater inflow prediction using radar rainfall data as the input of the prediction model constructed by system identification. The aim of the proposal is to construct a compact system by reducing the dimension of the input data. In this paper, Principal Component Analysis (PCA), which is widely used as a statistical method for data analysis and compression, is applied to pre-processing radar rainfall data. Then we evaluate the proposed method using the radar rainfall data and the inflow data acquired in a certain combined sewer system. This study reveals that a few principal components of radar rainfall data can be appropriate as the input variables to storm water inflow prediction model. Consequently, we have established a procedure for the stormwater prediction method using a few principal components of radar rainfall data.


2017 ◽  
Vol 921 (3) ◽  
pp. 24-29 ◽  
Author(s):  
S.I. Lesnykh ◽  
A.K. Cherkashin

The proposed procedure of integral mapping is based on calculation of evaluation functions on the integral indicators (II) taking into account the feature of the local geographical environment, when geosystems in the same states in the different environs have various estimates. Calculation of II is realized with application of a Principal Component Analysis for processing of the forest database, allowing to consider in II the weight of each indicator (attribute). The final value of II is equal to a difference of the first (condition of geosystem) and the second (condition of environmental background) principal components. The evaluation functions are calculated on this value for various problems of integral mapping. The environmental factors of variability is excluded from final value of II, therefore there is an opportunity to find the invariant evaluation function and to determine coefficients of this function. Concepts and functions of the theory of reliability for making the evaluation maps of the hazard of functioning and stability of geosystems are used.


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