A concept for emotion recognition systems for children with profound intellectual and multiple disabilities based on artificial intelligence using physiological and motion signals.
This study proposes a concept for emotion recognition systems for children with profound intellectual and multiple disabilities (PIMD) based on artificial intelligence (AI) using physiological and motion signals. First, the heartbeat interval (R–R interval, RRI) of a child with PIMD was measured, an...
| Publicado en: | Disability & Rehabilitation: Assistive Technology Vol. 19; no. 4; pp. 1319 - 1327 |
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| Autores principales: | , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
May2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=176934534&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 176934534 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17483107 1X04 jtl: Disability & Rehabilitation: Assistive Technology issn: 17483107 maglogo: Y pubinfo: dt: May2024 vid: 19 iid: 4 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 176934534 161460875 176934534 176934534 10.1080/17483107.2023.2170478 176934534 ppf: 1319 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A concept for emotion recognition systems for children with profound intellectual and multiple disabilities based on artificial intelligence using physiological and motion signals. aug: au: Tanabe, Hiroki Shiraishi, Toshihiko Sato, Haruhiko Nihei, Misato Inoue, Takenobu Kuwabara, Chika affil: Graduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Japan sug: subj: Child Behavior Evaluation Children with Disabilities Psychosocial Factors Emotions Evaluation Intellectual Disability Rehabilitation Motion Analysis Systems Artificial Intelligence Human Heart Rate Male Descriptive Statistics Adult Middle Age Funding Source Adult: 19-44 years Middle Aged: 45-64 years Male ab: This study proposes a concept for emotion recognition systems for children with profound intellectual and multiple disabilities (PIMD) based on artificial intelligence (AI) using physiological and motion signals. First, the heartbeat interval (R–R interval, RRI) of a child with PIMD was measured, and the correlation between the RRI and emotion was briefly tested in a preliminary experiment. Then, a concept based on AI for emotion recognition systems for children with PIMD was created using physiological and motion signals, and an emotion recognition system based on the proposed concept was developed using a random forest classifier taking as inputs the RRI, eye gaze, and other data acquired using low physical burden sensors. Subsequently, the developed emotion recognition system was evaluated, validating the proposed concept. Finally, we proposed a validated concept for emotion recognition systems. A correlation was found between the RRI and emotion. The emotion recognition system was created based on the proposed concept and tested. According to the results, the recognition rate of "negative" and "not negative" of 70.4% ± 6.1% (Mean ± S.D.) of the developed emotion recognition system was higher than 48.5% ± 5.0% of an unfamiliar person used as a control. The results indicate that the proposed concept for emotion recognition systems is useful for communicating with children with PIMD. A new concept based on artificial intelligence for emotion recognition systems for children with profound intellectual and multiple disabilities (PIMD) using physiological and motion signals is proposed. An emotion recognition system based on the proposed concept developed using a random forest classifier taking as inputs the heartbeat interval, eye gaze, and other data acquired using low physical burden sensors were tested in terms of the emotion recognition rate. The recognition rate of "negative" and "not negative" of the developed system (i.e., 70.4% ± 6.1%) is higher than that of an unfamiliar person (i.e., 48.5% ± 5.0%). The proposed concept for emotion recognition systems may be useful for communicating with children with PIMD. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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