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Review of paper on rehabilitation with a java 3D game. (#6)
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data/game_engine_papers.db

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"Title":"Feasibility of modified remotely monitored in-home gaming technology for improving hand function in adolescents with cerebral palsy.",
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"Citations":"",
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"Relevant":true,
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"Comment":"Not reviewed yet",
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"Comment": ["3 participants (adolescents 2 boys 1 girl - 13-15) 30 minutes per week",
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"sensing glove and PlayStation 3",
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"Build on work in virtual rehabilitation",
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"Off the shelf games may not have the graduation and data collection capability required by a therapist.",
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"Yellow Dog linux was installed on PPS3 - unable to use graphics processor.",
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"3 Games:",
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"Window cleaning game: Move fingers to uncover an image (designed to be familiar to participants) Multiple images, randomised to maintain interest - also included a window cleaning sound.",
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"Butterfly game: Move fingers to scare away a butterfly or mosquito. The game difficulty was modulated by increasing the insect speed.",
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"UFO game: basically the same as butterflies, but with UFO's and shrink rays."],
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"Game Engines - Search":[
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"Java 3D"
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],
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"Game Engine - Actual":"Unknown"
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"Game Engine - Actual":"Java 3D",
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"Cited Relevant Papers":["https://www.researchgate.net/publication/228820017_Virtual_reality_rehabilitation_for_all_Vivid_GX_versus_Sony_PlayStation_II_EyeToy", "https://doi.org/10.2522/ptj.20080062", "https://www.researchgate.net/publication/11785681_Virtual_reality-enhanced_stroke_rehabilitation", "https://pubmed.ncbi.nlm.nih.gov/12201804/"]
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},
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{
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"PMID":"35944270",

static/Java_3D.js

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"DOI":"10.1109\/TITB.2009.2038995",
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"Title":"Feasibility of modified remotely monitored in-home gaming technology for improving hand function in adolescents with cerebral palsy.",
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"Citations":"",
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"Game Engine - Actual":"Unknown"
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"Game Engine - Actual":"Java 3D"
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}
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]}
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// The following is mostly copy and pasted (with thanks) from:

update_web_pages.py

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@@ -48,7 +48,14 @@ def update_game_engine_page(engine: pd.Series, publications: pd.DataFrame) -> in
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# prepare data for writing out
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papers_df = papers_df[papers_df["Relevant"]]
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papers_df = papers_df.drop(
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["PMID", "Relevant", "Comment", "Game Engines - Search"], axis=1
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[
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"PMID",
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"Relevant",
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"Comment",
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"Game Engines - Search",
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"Cited Relevant Papers",
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],
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axis=1,
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)
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papers = papers_df.to_json(None, indent=2, orient="records")
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with open("src/script_papers.js", "r") as filein:

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