The evolution of methods for the capture of human movement leading to markerless motion capture for biomechanical applications

Abstract

Over the centuries the evolution of methods for the capture of human movement has been motivated by the need for new information on the characteristics of normal and pathological human movement. This study was motivated in part by the need of new clinical approaches for the treatment and prevention of diseases that are influenced by subtle changes in the patterns movement. These clinical approaches require new methods to measure accurately patterns of locomotion without the risk of artificial stimulus producing unwanted artifacts that could mask the natural patterns of motion. Most common methods for accurate capture of three-dimensional human movement require a laboratory environment and the attachment of markers or fixtures to the body's segments. These laboratory conditions can cause unknown experimental artifacts. Thus, our understanding of normal and pathological human movement would be enhanced by a method that allows the capture of human movement without the constraint of markers or fixtures placed on the body. In this paper, the need for markerless human motion capture methods is discussed and the advancement of markerless approaches is considered in view of accurate capture of threedimensional human movement for biomechanical applications. The role of choosing appropriate technical equipment and algorithms for accurate markerless motion capture is critical. The implementation of this new methodology offers the promise for simple, time-efficient, and potentially more meaningful assessments of human movement in research and clinical practice. The feasibility of accurately and precisely measuring 3D human body kinematics for the lower limbs using a markerless motion capture system on the basis of visual hulls is demonstrated.

A 2D Markerless Gait Analysis Methodology: Validation on Healthy Subjects

“…The use of a silhouette-based approach implies that no information related to the pixel greyscale intensity or color values are exploited, except for the background subtraction procedure [7, 8]. This should make the method less sensitive to change in light conditions or cameras specifications [7, 8].…”

“…This should make the method less sensitive to change in light conditions or cameras specifications [7, 8]. …”

“…However, in the abovementioned studies, the analyses were either limited to a single joint [20, 21], or they lacked a validation against a clinically accepted gold standard [22, 23]. These limitations hampered the wide spread use of such techniques in clinical settings [4, 7, 9]. …”

Changes of balance and gait in spastic hemiparesis are correlated with asymmetry of quiet stance

“…However, recent studies have shown a nonlinear chaotic behaviour of the stabilogram [1]. Because of the intrinsic complexity of the stabilogram, the aim of this work is to analyze posturographic data without any consideration on their dynamics and to investigate their behaviour in terms of regularity and complexity.…”

“…In the markerless analysis of human movement, one of the most used algorithms for the tracking of human body segments in visual hull sequences [1] is the Iterative Closest Point (ICP) algorithm [2]. This latter is used to execute the registration of three-dimensional images; it does not require the assignment of a priori correspondences between the geometric data of two sets of points, lines, curves, etc.…”