| Literature DB >> 33553523 |
Melvin Chan1, Emmanuel K Tse1, Seraph Bao1, Mai Berger1, Nadia Beyzaei1, Mackenzie Campbell1, Heinrich Garn2, Hebah Hussaina1, Gerhard Kloesch3, Bernhard Kohn2, Boris Kuzeljevic4, Yi Jui Lee5, Khaola Safia Maher1, Natasha Carson1, Jecika Jeyaratnam1, Scout McWilliams1, Karen Spruyt6, Hendrik F Machiel Van der Loos5, Calvin Kuo7, Osman Ipsiroglu1,8.
Abstract
The cartoon Fidgety Philip, the banner of Western-ADHD diagnosis, depicts a 'restless' child exhibiting hyperactive-behaviors with hyper-arousability and/or hypermotor-restlessness (H-behaviors) during sitting. To overcome the gaps between differential diagnostic considerations and modern computing methodologies, we have developed a non-interpretative, neutral pictogram-guided phenotyping language (PG-PL) for describing body-segment movements during sitting (Journal of Psychiatric Research). To develop the PG-PL, seven research assistants annotated three original Fidgety Philip cartoons. Their annotations were analyzed with descriptive statistics. To review the PG-PL's performance, the same seven research assistants annotated 12 snapshots with free hand annotations, followed by using the PG-PL, each time in randomized sequence and on two separate occasions. After achieving satisfactory inter-observer agreements, the PG-PL annotation software was used for reviewing videos where the same seven research assistants annotated 12 one-minute long video clips. The video clip annotations were finally used to develop a machine learning algorithm for automated movement detection (Journal of Psychiatric Research). These data together demonstrate the value of the PG-PL for manually annotating human movement patterns. Researchers are able to reuse the data and the first version of the machine learning algorithm to further develop and refine the algorithm for differentiating movement patterns. CrownEntities:
Keywords: Adverse drug reactions; Misdiagnosis; Movement disorders; Over-medication; Sleep-related movement disorders
Year: 2021 PMID: 33553523 PMCID: PMC7851356 DOI: 10.1016/j.dib.2021.106770
Source DB: PubMed Journal: Data Brief ISSN: 2352-3409