Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult
Abstract This paper introduces the architecture of an emotion-aware ambient intelligent and gerontechnological project named “Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation”. The objective of the proposal is to find solutions for improving the quality of life an...
Ausführliche Beschreibung
Autor*in: |
Castillo, José Carlos [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2016 |
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Schlagwörter: |
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Anmerkung: |
© Springer Science+Business Media New York 2016 |
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Übergeordnetes Werk: |
Enthalten in: Cognitive Computation - New York, NY : Springer, 2009, 8(2016), 2 vom: 12. Feb., Seite 357-367 |
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Übergeordnetes Werk: |
volume:8 ; year:2016 ; number:2 ; day:12 ; month:02 ; pages:357-367 |
Links: |
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DOI / URN: |
10.1007/s12559-016-9383-y |
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Katalog-ID: |
SPR026507609 |
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520 | |a Abstract This paper introduces the architecture of an emotion-aware ambient intelligent and gerontechnological project named “Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation”. The objective of the proposal is to find solutions for improving the quality of life and care of the elderly who can or want to continue living at home by using emotion regulation techniques. A series of sensors is used for monitoring the elderlies’ facial and gestural expression, activity and behaviour, as well as relevant physiological data. This way the older people’s emotions are inferred and recognized. Music, colour and light are the stimulating means to regulate their emotions towards a positive and pleasant mood. Then, the paper proposes a gerontechnological software architecture that enables real-time, continuous monitoring of the elderly and provides the best-tailored reactions of the ambience in order to regulate the older person’s emotions towards a positive mood. After describing the benefits of the approach for emotion recognition and regulation in the elderly, the eight levels that compose the architecture are described. | ||
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650 | 4 | |a Emotion regulation |7 (dpeaa)DE-He213 | |
650 | 4 | |a Ambient intelligence |7 (dpeaa)DE-He213 | |
650 | 4 | |a Gerontechnology |7 (dpeaa)DE-He213 | |
650 | 4 | |a Software architecture |7 (dpeaa)DE-He213 | |
700 | 1 | |a Castro-González, Álvaro |4 aut | |
700 | 1 | |a Fernández-Caballero, Antonio |4 aut | |
700 | 1 | |a Latorre, José Miguel |4 aut | |
700 | 1 | |a Pastor, José Manuel |4 aut | |
700 | 1 | |a Fernández-Sotos, Alicia |4 aut | |
700 | 1 | |a Salichs, Miguel A. |4 aut | |
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10.1007/s12559-016-9383-y doi (DE-627)SPR026507609 (SPR)s12559-016-9383-y-e DE-627 ger DE-627 rakwb eng Castillo, José Carlos verfasserin aut Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media New York 2016 Abstract This paper introduces the architecture of an emotion-aware ambient intelligent and gerontechnological project named “Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation”. The objective of the proposal is to find solutions for improving the quality of life and care of the elderly who can or want to continue living at home by using emotion regulation techniques. A series of sensors is used for monitoring the elderlies’ facial and gestural expression, activity and behaviour, as well as relevant physiological data. This way the older people’s emotions are inferred and recognized. Music, colour and light are the stimulating means to regulate their emotions towards a positive and pleasant mood. Then, the paper proposes a gerontechnological software architecture that enables real-time, continuous monitoring of the elderly and provides the best-tailored reactions of the ambience in order to regulate the older person’s emotions towards a positive mood. After describing the benefits of the approach for emotion recognition and regulation in the elderly, the eight levels that compose the architecture are described. Emotion recognition (dpeaa)DE-He213 Emotion regulation (dpeaa)DE-He213 Ambient intelligence (dpeaa)DE-He213 Gerontechnology (dpeaa)DE-He213 Software architecture (dpeaa)DE-He213 Castro-González, Álvaro aut Fernández-Caballero, Antonio aut Latorre, José Miguel aut Pastor, José Manuel aut Fernández-Sotos, Alicia aut Salichs, Miguel A. aut Enthalten in Cognitive Computation New York, NY : Springer, 2009 8(2016), 2 vom: 12. Feb., Seite 357-367 (DE-627)594779472 (DE-600)2486574-6 1866-9964 nnns volume:8 year:2016 number:2 day:12 month:02 pages:357-367 https://dx.doi.org/10.1007/s12559-016-9383-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 8 2016 2 12 02 357-367 |
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10.1007/s12559-016-9383-y doi (DE-627)SPR026507609 (SPR)s12559-016-9383-y-e DE-627 ger DE-627 rakwb eng Castillo, José Carlos verfasserin aut Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media New York 2016 Abstract This paper introduces the architecture of an emotion-aware ambient intelligent and gerontechnological project named “Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation”. The objective of the proposal is to find solutions for improving the quality of life and care of the elderly who can or want to continue living at home by using emotion regulation techniques. A series of sensors is used for monitoring the elderlies’ facial and gestural expression, activity and behaviour, as well as relevant physiological data. This way the older people’s emotions are inferred and recognized. Music, colour and light are the stimulating means to regulate their emotions towards a positive and pleasant mood. Then, the paper proposes a gerontechnological software architecture that enables real-time, continuous monitoring of the elderly and provides the best-tailored reactions of the ambience in order to regulate the older person’s emotions towards a positive mood. After describing the benefits of the approach for emotion recognition and regulation in the elderly, the eight levels that compose the architecture are described. Emotion recognition (dpeaa)DE-He213 Emotion regulation (dpeaa)DE-He213 Ambient intelligence (dpeaa)DE-He213 Gerontechnology (dpeaa)DE-He213 Software architecture (dpeaa)DE-He213 Castro-González, Álvaro aut Fernández-Caballero, Antonio aut Latorre, José Miguel aut Pastor, José Manuel aut Fernández-Sotos, Alicia aut Salichs, Miguel A. aut Enthalten in Cognitive Computation New York, NY : Springer, 2009 8(2016), 2 vom: 12. Feb., Seite 357-367 (DE-627)594779472 (DE-600)2486574-6 1866-9964 nnns volume:8 year:2016 number:2 day:12 month:02 pages:357-367 https://dx.doi.org/10.1007/s12559-016-9383-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 8 2016 2 12 02 357-367 |
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10.1007/s12559-016-9383-y doi (DE-627)SPR026507609 (SPR)s12559-016-9383-y-e DE-627 ger DE-627 rakwb eng Castillo, José Carlos verfasserin aut Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media New York 2016 Abstract This paper introduces the architecture of an emotion-aware ambient intelligent and gerontechnological project named “Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation”. The objective of the proposal is to find solutions for improving the quality of life and care of the elderly who can or want to continue living at home by using emotion regulation techniques. A series of sensors is used for monitoring the elderlies’ facial and gestural expression, activity and behaviour, as well as relevant physiological data. This way the older people’s emotions are inferred and recognized. Music, colour and light are the stimulating means to regulate their emotions towards a positive and pleasant mood. Then, the paper proposes a gerontechnological software architecture that enables real-time, continuous monitoring of the elderly and provides the best-tailored reactions of the ambience in order to regulate the older person’s emotions towards a positive mood. After describing the benefits of the approach for emotion recognition and regulation in the elderly, the eight levels that compose the architecture are described. Emotion recognition (dpeaa)DE-He213 Emotion regulation (dpeaa)DE-He213 Ambient intelligence (dpeaa)DE-He213 Gerontechnology (dpeaa)DE-He213 Software architecture (dpeaa)DE-He213 Castro-González, Álvaro aut Fernández-Caballero, Antonio aut Latorre, José Miguel aut Pastor, José Manuel aut Fernández-Sotos, Alicia aut Salichs, Miguel A. aut Enthalten in Cognitive Computation New York, NY : Springer, 2009 8(2016), 2 vom: 12. Feb., Seite 357-367 (DE-627)594779472 (DE-600)2486574-6 1866-9964 nnns volume:8 year:2016 number:2 day:12 month:02 pages:357-367 https://dx.doi.org/10.1007/s12559-016-9383-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 8 2016 2 12 02 357-367 |
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10.1007/s12559-016-9383-y doi (DE-627)SPR026507609 (SPR)s12559-016-9383-y-e DE-627 ger DE-627 rakwb eng Castillo, José Carlos verfasserin aut Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media New York 2016 Abstract This paper introduces the architecture of an emotion-aware ambient intelligent and gerontechnological project named “Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation”. The objective of the proposal is to find solutions for improving the quality of life and care of the elderly who can or want to continue living at home by using emotion regulation techniques. A series of sensors is used for monitoring the elderlies’ facial and gestural expression, activity and behaviour, as well as relevant physiological data. This way the older people’s emotions are inferred and recognized. Music, colour and light are the stimulating means to regulate their emotions towards a positive and pleasant mood. Then, the paper proposes a gerontechnological software architecture that enables real-time, continuous monitoring of the elderly and provides the best-tailored reactions of the ambience in order to regulate the older person’s emotions towards a positive mood. After describing the benefits of the approach for emotion recognition and regulation in the elderly, the eight levels that compose the architecture are described. Emotion recognition (dpeaa)DE-He213 Emotion regulation (dpeaa)DE-He213 Ambient intelligence (dpeaa)DE-He213 Gerontechnology (dpeaa)DE-He213 Software architecture (dpeaa)DE-He213 Castro-González, Álvaro aut Fernández-Caballero, Antonio aut Latorre, José Miguel aut Pastor, José Manuel aut Fernández-Sotos, Alicia aut Salichs, Miguel A. aut Enthalten in Cognitive Computation New York, NY : Springer, 2009 8(2016), 2 vom: 12. Feb., Seite 357-367 (DE-627)594779472 (DE-600)2486574-6 1866-9964 nnns volume:8 year:2016 number:2 day:12 month:02 pages:357-367 https://dx.doi.org/10.1007/s12559-016-9383-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 8 2016 2 12 02 357-367 |
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10.1007/s12559-016-9383-y doi (DE-627)SPR026507609 (SPR)s12559-016-9383-y-e DE-627 ger DE-627 rakwb eng Castillo, José Carlos verfasserin aut Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media New York 2016 Abstract This paper introduces the architecture of an emotion-aware ambient intelligent and gerontechnological project named “Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation”. The objective of the proposal is to find solutions for improving the quality of life and care of the elderly who can or want to continue living at home by using emotion regulation techniques. A series of sensors is used for monitoring the elderlies’ facial and gestural expression, activity and behaviour, as well as relevant physiological data. This way the older people’s emotions are inferred and recognized. Music, colour and light are the stimulating means to regulate their emotions towards a positive and pleasant mood. Then, the paper proposes a gerontechnological software architecture that enables real-time, continuous monitoring of the elderly and provides the best-tailored reactions of the ambience in order to regulate the older person’s emotions towards a positive mood. After describing the benefits of the approach for emotion recognition and regulation in the elderly, the eight levels that compose the architecture are described. Emotion recognition (dpeaa)DE-He213 Emotion regulation (dpeaa)DE-He213 Ambient intelligence (dpeaa)DE-He213 Gerontechnology (dpeaa)DE-He213 Software architecture (dpeaa)DE-He213 Castro-González, Álvaro aut Fernández-Caballero, Antonio aut Latorre, José Miguel aut Pastor, José Manuel aut Fernández-Sotos, Alicia aut Salichs, Miguel A. aut Enthalten in Cognitive Computation New York, NY : Springer, 2009 8(2016), 2 vom: 12. Feb., Seite 357-367 (DE-627)594779472 (DE-600)2486574-6 1866-9964 nnns volume:8 year:2016 number:2 day:12 month:02 pages:357-367 https://dx.doi.org/10.1007/s12559-016-9383-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 8 2016 2 12 02 357-367 |
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Castillo, José Carlos @@aut@@ Castro-González, Álvaro @@aut@@ Fernández-Caballero, Antonio @@aut@@ Latorre, José Miguel @@aut@@ Pastor, José Manuel @@aut@@ Fernández-Sotos, Alicia @@aut@@ Salichs, Miguel A. @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR026507609</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230331230650.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s12559-016-9383-y</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR026507609</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s12559-016-9383-y-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Castillo, José Carlos</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media New York 2016</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This paper introduces the architecture of an emotion-aware ambient intelligent and gerontechnological project named “Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation”. 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Castillo, José Carlos |
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Castillo, José Carlos misc Emotion recognition misc Emotion regulation misc Ambient intelligence misc Gerontechnology misc Software architecture Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult |
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Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult Emotion recognition (dpeaa)DE-He213 Emotion regulation (dpeaa)DE-He213 Ambient intelligence (dpeaa)DE-He213 Gerontechnology (dpeaa)DE-He213 Software architecture (dpeaa)DE-He213 |
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Castillo, José Carlos Castro-González, Álvaro Fernández-Caballero, Antonio Latorre, José Miguel Pastor, José Manuel Fernández-Sotos, Alicia Salichs, Miguel A. |
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software architecture for smart emotion recognition and regulation of the ageing adult |
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Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult |
abstract |
Abstract This paper introduces the architecture of an emotion-aware ambient intelligent and gerontechnological project named “Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation”. The objective of the proposal is to find solutions for improving the quality of life and care of the elderly who can or want to continue living at home by using emotion regulation techniques. A series of sensors is used for monitoring the elderlies’ facial and gestural expression, activity and behaviour, as well as relevant physiological data. This way the older people’s emotions are inferred and recognized. Music, colour and light are the stimulating means to regulate their emotions towards a positive and pleasant mood. Then, the paper proposes a gerontechnological software architecture that enables real-time, continuous monitoring of the elderly and provides the best-tailored reactions of the ambience in order to regulate the older person’s emotions towards a positive mood. After describing the benefits of the approach for emotion recognition and regulation in the elderly, the eight levels that compose the architecture are described. © Springer Science+Business Media New York 2016 |
abstractGer |
Abstract This paper introduces the architecture of an emotion-aware ambient intelligent and gerontechnological project named “Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation”. The objective of the proposal is to find solutions for improving the quality of life and care of the elderly who can or want to continue living at home by using emotion regulation techniques. A series of sensors is used for monitoring the elderlies’ facial and gestural expression, activity and behaviour, as well as relevant physiological data. This way the older people’s emotions are inferred and recognized. Music, colour and light are the stimulating means to regulate their emotions towards a positive and pleasant mood. Then, the paper proposes a gerontechnological software architecture that enables real-time, continuous monitoring of the elderly and provides the best-tailored reactions of the ambience in order to regulate the older person’s emotions towards a positive mood. After describing the benefits of the approach for emotion recognition and regulation in the elderly, the eight levels that compose the architecture are described. © Springer Science+Business Media New York 2016 |
abstract_unstemmed |
Abstract This paper introduces the architecture of an emotion-aware ambient intelligent and gerontechnological project named “Improvement of the Elderly Quality of Life and Care through Smart Emotion Regulation”. The objective of the proposal is to find solutions for improving the quality of life and care of the elderly who can or want to continue living at home by using emotion regulation techniques. A series of sensors is used for monitoring the elderlies’ facial and gestural expression, activity and behaviour, as well as relevant physiological data. This way the older people’s emotions are inferred and recognized. Music, colour and light are the stimulating means to regulate their emotions towards a positive and pleasant mood. Then, the paper proposes a gerontechnological software architecture that enables real-time, continuous monitoring of the elderly and provides the best-tailored reactions of the ambience in order to regulate the older person’s emotions towards a positive mood. After describing the benefits of the approach for emotion recognition and regulation in the elderly, the eight levels that compose the architecture are described. © Springer Science+Business Media New York 2016 |
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title_short |
Software Architecture for Smart Emotion Recognition and Regulation of the Ageing Adult |
url |
https://dx.doi.org/10.1007/s12559-016-9383-y |
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author2 |
Castro-González, Álvaro Fernández-Caballero, Antonio Latorre, José Miguel Pastor, José Manuel Fernández-Sotos, Alicia Salichs, Miguel A. |
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Castro-González, Álvaro Fernández-Caballero, Antonio Latorre, José Miguel Pastor, José Manuel Fernández-Sotos, Alicia Salichs, Miguel A. |
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up_date |
2024-07-03T21:11:23.118Z |
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score |
7.4002676 |