TY  - JOUR
PY  - 2020//
TI  - Is Fidgety Philip's ground truth also ours? The creation and application of a machine learning algorithm
JO  - Journal of psychiatric research
A1  - Beyzaei, Nadia
A1  - Bao, Seraph
A1  - Bu, Yanyun
A1  - Hung, Linus
A1  - Hussaina, Hebah
A1  - Maher, Khaola Safia
A1  - Chan, Melvin
A1  - Garn, Heinrich
A1  - Kloesch, Gerhard
A1  - Kohn, Bernhard
A1  - Kuzeljevic, Boris
A1  - McWilliams, Scout
A1  - Spruyt, Karen
A1  - Tse, Emmanuel
A1  - Machiel Van der Loos, Hendrik F.
A1  - Kuo, Calvin
A1  - Ipsiroglu, Osman S.
SP  - 144
EP  - 151
VL  - 131
IS  - 
N2  - BACKGROUND: Behavioral observations support clinical in-depth phenotyping but phenotyping and pattern recognition are affected by training background. As Attention Deficit Hyperactivity Disorder, Restless Legs syndrome/Willis Ekbom disease and medication induced activation syndromes (including increased irritability and/or akathisia), present with hyperactive-behaviors with hyper-arousability and/or hypermotor-restlessness (H-behaviors), we first developed a non-interpretative, neutral pictogram-guided phenotyping language (PG-PL) for describing body-segment movements during sitting (Data in Brief).   METHODOLOGY & RESULTS: The PG-PL was applied for annotating 12 1-min sitting-videos (inter-observer agreements >85%->97%) and these manual annotations were used as a ground truth to develop an automated algorithm using OpenPose, which locates skeletal landmarks in 2D video. We evaluated the algorithm's performance against the ground truth by computing the area under the receiver operator curve (>0.79 for the legs, arms, and feet, but 0.65 for the head). While our pixel displacement algorithm performed well for the legs, arms, and feet, it predicted head motion less well, indicating the need for further investigations.   CONCLUSION: This first automated analysis algorithm allows to start the discussion about distinct phenotypical characteristics of H-behaviors during structured behavioral observations and may support differential diagnostic considerations via in-depth phenotyping of sitting behaviors and, in consequence, of better treatment concepts.<p />  <p>Language: en</p>
LA  - en
SN  - 0022-3956
UR  - http://dx.doi.org/10.1016/j.jpsychires.2020.08.033
ID  - ref1
ER  -