This paper examines the use of relative phase measures to characterize postural coordination strategies, which may add to the understanding of how the postural system is regulated during functional movements. However, relative phase measures have broader application in describing coordination patterns under various skillful tasks, and demonstrating coordination changes during of learning of motor skills and after injuries. Relative phase measures the relationship between two joint or body segment angles to characterize inter-joint coordination patterns. Since relative phase measures incorporates both spatial and temporal aspects of angular movement, it may be more sensitive to picking up differences of coordination patterns (Haddad et al, 2010; Kurz and Stergiou, 2004). Relative phase measures have been used to measure limb coordination during walking (Barela et al., 2000; Burgess-Limerick et al., 1993; Kurz and Stergiou, 2002; 2004, Haddad et al, 2010), weightlifting (Hu and Ning, 2015), swimming (Komar, et al., 2014), swinging (Teulier and Delignieres, 2007) and gymnastic skills (Gautieret al, 2009). Stable and unstable coordination patterns have been found using relative phase with oscillating bimanual tasks (e.g. Kelso, 1984; Milliex et al., 2005), visual tracking postural tasks and matching postural coordination to ankle-hip position plane figures (e.g. Bardy et al., 2002; Faugloire et al., 2006; 2009, James, 2014). Relative phase between pelvis and trunk movements are used to identify coordination changes in individuals with low back fatigue during weightlifting (Hu and Ning, 2015) and for those persons with low back pain during sit to stand tasks (Shum et al 2005). Runners with low back pain showed differences in trunk and pelvis continuous relative phase during walking and running when compared to runners without a history of low back pain (Seay et al, 2011). Relative phase measures have also been applied to examine coordination during learning of sports related tasks, such as swimming (Komar et al, 2014), swinging (Teulier and Delignieres, 2007) and gymnastic skills (Delignieres, et al, 1998; Gautieret al, 2009). All of the tasks studied can be characterized to have either discrete or continuous movements.
Mean absolute relative phase (MARP), deviation phase (DP) and point-estimation relative phase (PRP) are potential measures to characterize coordination during the performance of tasks. We focus on postural coordination during the performance of a serial reaching task. MARP and DP are single measures derived from continuous relative phase curves that could quantify coordination patterns and describe the stability of the patterns during functional movements. PRP measures relative phase by comparing the time to maximal or minimal angular displacement of one joint within a cycle of angular displacement of a reference joint (Kurz and Stergiou, 2004; Wheat and Glazer, 2006; Zanone and Kelso, 1992). Basic descriptive statistics of PRP across the movement cycles provides information about coordination modes and variability within a single trial (Bardy, 2005; Bardy et al., 2002; Fauglorie et al., 2006, Oullier, et al, 2002). Postural coordination patterns have previously been characterized in terms of in-phase (close to 0 degrees) and anti-phase (close to 180 degrees) hip and ankle relationships in visual tracking tasks using PRP (Bardy et al., 1999; Bardy, et al., 2002; Faugloire, et al., 2006; Oullier et al., 2002; James, 2014). In-phase and anti-phase postural coordination patterns may also be demonstrated during reaching tasks.
The selection of a relative phase measure must relate to the type of movement within the task being assessed, e. g. continuous or discrete movements. PRP measures may be easily attained during continuous cyclical movement tasks, such as walking or frequency induced postural sway, where clear displacement peaks of the comparison angles are repeatedly attainable. MARP has been proposed as a valid measure of joint relationships during gait cycles (Kutz and Stergiou, 2004) and might also characterize in-phase and anti-phase postural sway patterns. Because MARP is an average of a continuous relative phase curve over the duration of a movement, lower values are interpreted as representing more in-phase associations while higher values are interpreted as indicating more anti-phase relationships. Low DP values are considered to represent increased stability whereas high DP values represent decreased stability of the coordination pattern (Kurz and Stergiou, 2004). MARP and DP may be of greater value during the analysis of discrete movements or phases of movements where a description of the dynamics of the inter-joint interactions across the entire movement is desired.
We have used MARP for examining proximal and distal postural coordination strategies during discrete reaching (Galgon and Shewokis, 2006). In a pilot study, five healthy young adults performed a discrete arm raising and lowering reaching task with arm conditions (unilateral versus bilateral arm movements) and different target heights (three targets separated by 17 cm, vertically). Changes in postural coordination dynamics as measured by MARP were evident when examining different task constraints. Target height had a main effect on dominant shoulder-ipsilateral hip MARP, [F.sub.2,8] = 38.75, p
In our investigation of postural coordination during the learning of a novel serial reaching task, we were concerned as to whether these measures would provide a description of postural coordination that could be consistently quantified across practice. The serial reaching task included 15 sequential up and down arm movements that the subjects learned across three days of practice by following light targets, which were displayed in front of them (Figure 1). In this work we have shown that participants improved their hand accuracy and consistency in matching their hand heights to the vertical targets across practice. Participants also improved their postural regulation as measured by time to boundary derived from center of pressure data (Galgon et al., 2010). We are interested in determining, if postural coordination strategies also change when learning this dynamic serial task. Selecting a relative phase measure seems appropriate; however there remains a limitation in that the movements generated during this task could not easily be classified as either continuous or discrete.
A problem in calculating PRP within a multistep task is selecting reference points; the peaks and/or troughs in the angular displacement time series that are used for the maximum or minimum values (Wheat and Glazer, 2006). Changes in angular displacement of postural joints may be small and gradual, which may additionally contribute to problems when selecting the reference points for analyzing postural coordination. Using MARP and DP may be a problem in a serial task because discontinuous movements may create phase distortion in continuous relative phase curves. Phase distortions may include phase shifts (Kurz and Stergiou, 2002) or phase wrapping (Milliex et al., 2005), typically associated with 360degree phase angle data. A phase shift is a temporary 360 degree shift in the relative phase data array (Kurz and Stergiou, 2002). The shift occurs when the instantaneous phase angle of one joint crosses over the zero axis (values change from 360 to 0 degrees) with the comparison joint phase angle crossing the axis at a later time. The result is a temporary [+ or -] 360 degree jump in the continuous relative phase curve. Phase wrapping occurs when there is no consistent relationship between the comparison angles or when the relative phase is non-stationary (Milliex et al., 2005), e. g. when one joint was moving and the other was relatively stationary. Phase distortions induce inflation in MARP and DP values, if the distortions are not corrected. PRP measurements may be more easily applied to a serial task because the relative phase is not averaged over a complete cycle and the asymmetries and irregularities in the actual motion are eliminated (Zanone and Kelso, 1992) and phase distortions do not need to be accounted for in the calculations. However, PRP measures could potentially miss important interjoint relationship changes during a serial task. These PRP omissions might occur between point-estimations.
Although these relative phase measures are not novel in describing movement coordination patterns, they have primarily been applied to measuring postural coordination in oscillating tasks and have not been reported in the analysis of coordination for standing and reaching tasks. To our knowledge, using relative phase measures to assess the coordination dynamics of serial tasks has not been done. Within the method section, we describe visual inspection of the data and define the corrections made to the relative phase curves to ensure consistent calculation of MARP, DP and PRP with the serial reaching task. We present a comparison of the MARP and DP measurements to the PRP measurements in a subset of subjects who participated in a study examining the learning of a novel serial reaching task. Our purpose is to present the methods we used to calculate postural coordination dynamics and discuss the strengths and limitations of each measure within the context of a serial reaching task.
Seven participants were randomly selected from a sample of healthy young adults who had originally consented to participate in a learning study (Galgon et al., 2010). These seven individuals included 2 males and 5 females (mean age of 25 [+ or -] 3 years; mean shoulder height of 1.42 [+ or -] 0.08 m; mean weight of 74.4 [+ or -] 12.7 kg). Participants were included if they were between 18-49 years, and excluded, if they felt they could not easily perform the required activities, could not...