TY  - JOUR
A1  - Schönherr, Désirée
A1  - Paulick, Jane
A1  - Strauß, Bernhard
A1  - Deisenhofer, Anne-Katharina
A1  - Schwartz, Brian
A1  - Rubel, Julian
A1  - Lutz, Wolfgang
A1  - Stangier, Ulrich
A1  - Altmann, Uwe
T1  - Identification of movement synchrony : validation of windowed cross-lagged correlation and -regression with peak-picking algorithm
T2  - PLoS one
N2  - In psychotherapy, movement synchrony seems to be associated with higher patient satisfaction and treatment outcome. However, it remains unclear whether movement synchrony rated by humans and movement synchrony identified by automated methods reflect the same construct. To address this issue, video sequences showing movement synchrony of patients and therapists (N = 10) or not (N = 10), were analyzed using motion energy analysis. Three different synchrony conditions with varying levels of complexity (naturally embedded, naturally isolated, and artificial) were generated for time series analysis with windowed cross-lagged correlation/ -regression (WCLC, WCLR). The concordance of ratings (human rating vs. automatic assessment) was computed for 600 different parameter configurations of the WCLC/WCLR to identify the parameter settings that measure movement synchrony best. A parameter configuration was rated as having a good identification rate if it yields high concordance with human-rated intervals (Cohen’s kappa) and a low amount of over-identified data points. Results indicate that 76 configurations had a good identification rate (IR) in the least complex condition (artificial). Two had an acceptable IR with regard to the naturally isolated condition. Concordance was low with regard to the most complex (naturally embedded) condition. A valid identification of movement synchrony strongly depends on parameter configuration and goes beyond the identification of synchrony by human raters. Differences between human-rated synchrony and nonverbal synchrony measured by algorithms are discussed.
KW  - Signal bandwidth
KW  - Musculoskeletal system
KW  - Behavior
KW  - Human mobility
KW  - Research errors
KW  - Sequence analysis
KW  - Algorithms
KW  - Normal distribution
Y1  - 2019
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/48867
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-488670
SN  - 1932-6203
N1  - Copyright: © 2019 Schoenherr et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
VL  - 14
IS  - (2): e0211494
SP  - 1
EP  - 24
PB  - PLoS
CY  - Lawrence, Kan.
ER  -