Effect of registration on cyclical kinematic data

Abstract

Given growing interest in Functional Data Analysis (FDA) as a useful method for analyzing human movement data, it is critical to understand the effects of standard FDA procedures, including registration, on biomechanical analyses. Registration is used to reduce phase variability between curves while preserving the individual curves shape and amplitude. The application of three methods available to assess registration could benefit those in the biomechanics community using FDA techniques: comparison of mean curves, comparison of average RMS values, and assessment of time-warping functions. Therefore, the present study has two purposes. First, the necessity of registration applied to cyclical data after time normalization is assessed. Second, we illustrate the three methods for evaluating registration effects. Masticatory jaw movements of 22 healthy adults (2 males, 21 females) were tracked while subjects chewed a gum-based pellet for 20 seconds. Motion data were captured at 60 Hz with two gen-locked video cameras. Individual chewing cycles were time normalized and then transformed into functional observations. Registration did not affect mean curves and warping functions were linear. Although registration decreased the RMS, indicating a decrease in inter-subject variability, the difference was not statistically significant. Together these results indicate that registration may not always be necessary for cyclical chewing data. An important contribution of this paper is the illustration of three methods for evaluating registration that are easy to apply and useful for judging whether the extra data manipulation is necessary.

Functional Data Analysis for Biomechanics

“…Because a common time interval is required for FDA analyses, it is important to assess whether registration procedures are necessary after standard time normalization has been applied to the data. Crane et al (2010) found that registration after time normalization may not always be necessary. They concluded that when obtaining an average curve was the purpose of registration, the additional alignment did not affect the interpretation of the behavior enough to warrant the additional data manipulation.…”

“…So when might registration be useful? When specific functional data analyses, such as those discussed in Section 4, will be used, Crane et al (2010) found that decreases in inter-subject variability within homogenous groups indicate registration may be justified. Because of this, when functional data analyses are used, registration improves the likelihood of finding significant differences between two or more populations, if they indeed exist.…”

“…Although representing motion data as a set of functions is not new to biomechanics analyses (Chester & Wrigley, 2008;Deluzio & Astephen, 2007;Landry et al, 2007;Lee et al, 2009;Sadeghi et al, 2002;2000), statistical methods developed specifically for analyzing these functions have not been available. More recently, FDA methods have been used within biomechanics to study mastication (Crane et al, 2010), back pain (Page et al, 2006), as well as age, gender, and speed effects on walking (Røislien et al, 2009). Given the interest in and need for treating motion data as functions, it is important that methods for analyzing a set a functions using emerging statistical methods are brought to the attention of those in the biomechanics community.…”

Toward Automatic Activity Classification and Movement Assessment During a Sports Training Session

“…joint angle) are usually reduced to a single/few discrete measure(s) that purportedly represent a joint's movement technique (e.g. peak flexion), but in reality comprises less than 2% of the available data [17], [18]. 2.…”

“…mean ±95% confidence intervals) [10]. However, this may result in a distortion of the data as key events are not time aligned across trials [18].…”