Thoughts regarding the qualitative analysis of human movement

The qualitative analysis of human movement is composed of many parts. Trying to assess the contribution of each of these components to the whole process of qualitative analysis is difficult. Evaluating a qualitative approach to human movement analysis using quantitative procedures can lead to misinterpretations. Qualitative analysis of movement has components important to its success which cannot be gauged by traditional biomechanical standards.     

Quantitative analysis of human movement synergies: constructive pattern analysis for gait

To record three-dimensional coordinates of the joints from normal human subjects during locomotion, we used a digital motion analysis system (ELITE). Recordings were obtained under several different conditions, which included normal walking and stepping over obstacles. Principal component analysis was used to analyze coordinate data after conversion of the data to segmental angles. This technique gave a stable summary of the redundancy in gait kinematic data in the form of reduced variables (principal components). By modeling the shapes of the phase plots of reduced variables (distortion analysis) and using a limited number of model parameters, good resolution was obtained between subtly different conditions. Hence, it was possible to accurately resolve small distributed changes in gait patterns within subjects. These methods seem particularly suited to longitudinal studies in which relevant movement features are not known a priori. Assumptions and neurophysiological applications are discussed.     

Quantitative analysis of qualitative data

This paper presents an overview of an approach to the quantitative analysis of qualitative data with theoretical and methodological explanations of the two cornerstones of the approach, Alternating Least Squares and Optimal Scaling. Using these two principles, my colleagues and I have extended a variety of analysis procedures originally proposed for quantitative (interval or ratio) data to qualitative (nominal or ordinal) data, including additivity analysis and analysis of variance; multiple and canonical regression; principal components; common factor and three mode factor analysis; and multidimensional scaling. The approach has two advantages: (a) If a least squares procedure is known for analyzing quantitative data, it can be extended to qualitative data; and (b) the resulting algorithm will be convergent. Three completely worked through examples of the additivity analysis procedure and the steps involved in the regression procedures are presented.Presented as the Presidential Address to the Psychometric Society's Annual meeting, May, 1981. I wish to express my deep appreciation to Jan de Leeuw and Yoshio Takane. Our team effort was essential for the developments reported in this paper. Without this effort the present paper would not exist. Portions of this paper appear in Lantermann, E. D. & Feger, H. (Eds.)Similarity and Choice, Hans Huber, Vienna, 1980. The present paper benefits greatly from a set of detailed comments made by Joseph Kruskal on the earlier paper.     

Fourier analysis of movement patterns in pigeons

Fourier analysis describes the amount of variation in a time series by partitioning it into sinusoids of different amplitudes and wavelengths and quantifying the extent to which these waves are synchronized. The importance of a given wave is represented by its contribution to the explained variance of the time series. To illustrate its potential application to the study of movement, Fourier analysis was used to quantify the movement patterns of 2 pigeons on a variable-interval (VI) and a variable-time (VT) schedule of reinforcement. For comparison, the movements of 2 pigeons that did not receive reinforcement were similarly analyzed. Characteristic frequencies were higher during VI than during VT, and relatively low during nonreinforcement. We concluded that Fourier analysis can be used to represent movement patterns compactly, study their periodicity, stereotypy, and resonance, and assist in computer simulations and models of movement.     

Dynamic representations of human body movement

Psychophysical and neurophysiological studies suggest that human body motions can be readily recognized. Human bodies are highly articulated and can move in a nonrigid manner. As a result, we perceive highly dissimilar views of the human form in motion. How does the visual system integrate multiple views of a human body in motion so that we can perceive human movement as a continuous event? The results of a set of priming experiments suggest that motion can readily facilitate the linkage of different views of a moving human. Positive priming was found for novel views of a human body that fell within the path of human movement. However, no priming was observed for novel views outside the path of motion. Furthermore, priming was restricted to those views that satisfied the biomechanical constraints of human movement. These results suggest that visual representation of human movement may be based upon the movement limitations of the human body and may reflect a dynamic interaction of motion and object-recognition processes.     

Redundancy analysis for qualitative variables

Redundancy analysis (also called principal components analysis of instrumental variables) is a technique for two sets of variables, one set being dependent of the other. Its aim is maximization of the explained variance of the dependent variables by a linear combination of the explanatory variables. The technique is generalized to qualitative variables; it then gives implicitly a simultaneous optimal scaling of the dependent, qualitative variables. Examples are taken from the Dutch Life Situation Survey 1977, using Satisfaction with Life and Happiness as dependent variables. The analysis leads to one well-being scale, defined by the explanatory variables Marital status, Schooling, Income and Activity.The views expressed in this paper are those of the author and do not necessarily reflect the policies of the Netherlands Central Bureau of Statistics.     

Parental divorce as a factor in children''s perception of human relationships: An analysis of human movement responses in the Rorschach test

The subjects were 108 Swedish children between 10 and 12 years old, who constituted a divorce and a non-divorce group of 27 girls and 27 boys each. Rorschach Tests were administered individually and human movement responses were analysed. Non-divorce children perceived more cooperative and fewer hostile interactions than the divorce children. Responses containing figures engaged in hostile interaction were most common among divorce girls, whereas the divorce boys had difficulties in perceiving any interaction whatsoever. The different effect of parental divorce on the ability of girls and boys to develop satisfactory social relationships is discussed.     

Long latency reflex regulation in human ballistic movement

Step torque perturbations were applied to adduct the index during either a 25° ballistic or a 25° slow abduction movement. Subjects were instructed to react as quickly and as forcefully as possible in the opposite direction to the perturbation. The resulting long latency reflex (LLR) EMG activity was studied in the first dorsal interosseus. The LLR measured when the perturbation occurred in the first part of the movement was not different in a ballistic movement than a ramp movement. In our experiments, the LLR was the same in the first as well as in the second part of a ballistic movement. The LLR observed when the perturbation was applied at the onset of the agonist EMG burst (before the onset of a ballistic movement) was either similar or reduced when recorded during the ballistic movement.     

3-D eye movement analysis

This paper presents a novel three-dimensional (3-D) eye movement analysis algorithm for binocular eye tracking within virtualreality (VR). The user’s gaze direction, head position, and orientation are tracked in order to allow recording of the user’s fixations within the environment. Although the linear signal analysis approach is itself not new, its application to eye movement analysis in three dimensions advances traditional two-dimensional approaches, since it takes into account the six degrees of freedom of head movements and is resolution independent. Results indicate that the 3-D eye movement analysis algorithm can successfully be used for analysis of visual process measures in VR. Process measures not only can corroborate performance measures, but also can lead to discoveries of the reasons for performance improvements. In particular, analysis of users’ eye movements in VR can potentially lead to further insights into the underlying cognitive processes of VR subjects.     

Common functional principal components analysis: a new approach to analyzing human movement data

In many human movement studies angle-time series data on several groups of individuals are measured. Current methods to compare groups include comparisons of the mean value in each group or use multivariate techniques such as principal components analysis and perform tests on the principal component scores. Such methods have been useful, though discard a large amount of information. Functional data analysis (FDA) is an emerging statistical analysis technique in human movement research which treats the angle-time series data as a function rather than a series of discrete measurements. This approach retains all of the information in the data. Functional principal components analysis (FPCA) is an extension of multivariate principal components analysis which examines the variability of a sample of curves and has been used to examine differences in movement patterns of several groups of individuals. Currently the functional principal components (FPCs) for each group are either determined separately (yielding components that are group-specific), or by combining the data for all groups and determining the FPCs of the combined data (yielding components that summarize the entire data set). The group-specific FPCs contain both within and between group variation and issues arise when comparing FPCs across groups when the order of the FPCs alter in each group. The FPCs of the combined data may not adequately describe all groups of individuals and comparisons between groups typically use t-tests of the mean FPC scores in each group. When these differences are statistically non-significant it can be difficult to determine how a particular intervention is affecting movement patterns or how injured subjects differ from controls. In this paper we aim to perform FPCA in a manner allowing sensible comparisons between groups of curves. A statistical technique called common functional principal components analysis (CFPCA) is implemented. CFPCA identifies the common sources of variation evident across groups but allows the order of each component to change for a particular group. This allows for the direct comparison of components across groups. We use our method to analyze a biomechanical data set examining the mechanisms of chronic Achilles tendon injury and the functional effects of orthoses.     

Using AGENDA for qualitative data analysis

Computerized approaches to qualitative analysis have lagged significantly behind comparable developments in quantitative analysis. AGENDA, a PC-based, free-form database package, manipulates text as data, performs the basic tasks of qualitative data analysis, and satisfies the criteria of computerized field research methods. AGENDA's contributions to qualitative research outweigh its limitations.     

Speech-related body movement in aphasia: period analysis of upper arms and head movement.

The effects of aphasia on coverbal body movement have important implications for the understanding of both normal and pathological speech processes. The related findings were often inconsistent, partly due to inherent methodological difficulties which could be reduced by the use of advanced techniques of movement monitoring (Hadar, 1991). The present study employed a new computerized system, CODA-3, which locates small prismatic markers and computes by triangulation their three-dimensional position at 100 Hz. Movement of the head and the upper arms was monitored in 15 aphasic and normal subjects engaged in speech during a naturalistic interview. Movement analysis was based on automatized identification of successive movement extrema ("period analysis") and the computation of amplitude, duration, and velocity of each period. The results showed higher incidence and amplitude of all body movement in the aphasic population. Fluent aphasics showed this particularly with "symbolic," content-bearing movements, while nonfluent aphasics were higher than controls in both symbolic and "motor" (simple and small) movements. No deficit in the internal organization of movement was seen in the aphasic population. These results indicate that aphasics increase their coverbal movement in compensation for their speech impairment: fluent aphasics compensate primarily for a symbolic impairment, while nonfluent aphasics compensate more for a motor impairment.