In today's life, stress has become a big issue because of excessive working load, study pressure, and unhealthy lifestyle habits. It also impacts the physical health. Typical stress monitoring systems are largely reactive, meaning that they only detect stress once it has occurred, and thus cannot provide timely intervention. In this study, a proactive stress management model based on the wearable physiological signals and intelligent decision-making is proposed, with the aim of predicting or controlling the physiological changes caused by stress by using physiological signals as the input to the system. The proposed system combines three models: Bidirectional Long Short-Term Memory (Bi-LSTM) forecasting, Deep Reinforcement Learning (DRL), and SHAP explainability, to create a predictive and adaptive health support system.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Paperback. Condición: new. Paperback. In today's life, stress has become a big issue because of excessive working load, study pressure, and unhealthy lifestyle habits. It also impacts the physical health. Typical stress monitoring systems are largely reactive, meaning that they only detect stress once it has occurred, and thus cannot provide timely intervention. In this study, a proactive stress management model based on the wearable physiological signals and intelligent decision-making is proposed, with the aim of predicting or controlling the physiological changes caused by stress by using physiological signals as the input to the system. The proposed system combines three models: Bidirectional Long Short-Term Memory (Bi-LSTM) forecasting, Deep Reinforcement Learning (DRL), and SHAP explainability, to create a predictive and adaptive health support system. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9786630078862
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 120 pp. Englisch. Nº de ref. del artículo: 9786630078862
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Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Proactive Stress Management Using LSTM Forecasting, Deep Reinforcement | Abhijit Kumar Jha (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630078862 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 135816244
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Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. Paperback. In today's life, stress has become a big issue because of excessive working load, study pressure, and unhealthy lifestyle habits. It also impacts the physical health. Typical stress monitoring systems are largely reactive, meaning that they only detect stress once it has occurred, and thus cannot provide timely intervention. In this study, a proactive stress management model based on the wearable physiological signals and intelligent decision-making is proposed, with the aim of predicting or controlling the physiological changes caused by stress by using physiological signals as the input to the system. The proposed system combines three models: Bidirectional Long Short-Term Memory (Bi-LSTM) forecasting, Deep Reinforcement Learning (DRL), and SHAP explainability, to create a predictive and adaptive health support system. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9786630078862
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware 120 pp. Englisch. Nº de ref. del artículo: 9786630078862
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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