2023
DOI: 10.1049/bme2.12110
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Detection of non‐suicidal self‐injury based on spatiotemporal features of indoor activities

Abstract: Non-suicide self-injury (NSSI) can be dangerous and difficult for guardians or caregivers to detect in time. NSSI refers to when people hurt themselves even though they have no wish to cause critical or long-lasting hurt. To timely identify and effectively prevent NSSI in order to reduce the suicide rates of patients with a potential suicide risk, the detection of NSSI based on the spatiotemporal features of indoor activities is proposed. Firstly, an NSSI behaviour dataset is provided, and it includes four cat… Show more

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Cited by 33 publications
(8 citation statements)
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“…The MIGI algorithm and the D‐MIGI algorithm in this article can be extended to polynomial nonlinear models, rational models, switching models, and exponential autoregressive models. The proposed multi‐innovation gradient‐based iterative identification methods for feedback nonlinear systems by using the decomposition technique in this paper can combine other identification idea and methods 108‐117 for develop new identification algorithms of dynamical stochastic linear and nonlinear systems 118‐126 such as chemical process control systems, robot control systems, information processing systems 127‐135 and so on.…”
Section: Discussionmentioning
confidence: 99%
“…The MIGI algorithm and the D‐MIGI algorithm in this article can be extended to polynomial nonlinear models, rational models, switching models, and exponential autoregressive models. The proposed multi‐innovation gradient‐based iterative identification methods for feedback nonlinear systems by using the decomposition technique in this paper can combine other identification idea and methods 108‐117 for develop new identification algorithms of dynamical stochastic linear and nonlinear systems 118‐126 such as chemical process control systems, robot control systems, information processing systems 127‐135 and so on.…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, the convergence analysis proclaims that the AM-HLS parameter estimates converge to their true values. The algorithm proposed in this article can combine with other identification methods and be applied to MIMO systems with colored noise and other field [99][100][101][102][103][104] such as process control systems [105][106][107][108][109][110][111] and information processing systems.…”
Section: Discussionmentioning
confidence: 99%
“…$$ In summary, Equations (28)–(43) consist of the O‐AM‐HGI algorithm based on the mean value. The O‐AM‐HGI algorithms can combine some mathematical tools 72‐75 and identification approaches 76‐82 to explore parameter estimation methods of different dynamic stochastic systems 83‐89 and can be applied to signal processing and chemical process control. The computing steps of the O‐AM‐HGI algorithm in (28)–(43) are summarized as follows:…”
Section: The O‐am‐hgi Algorithmmentioning
confidence: 99%