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Embedded Emotion Recognition within Cyber-Physical Systems using Physiological Signals
Cita
Miranda Calero, Jose Angel, Marino, Rodrigo, Lanza Gutiérrez, Jose Manuel, Riesgo Alcaide, Teresa 
ORCID: https://orcid.org/0000-0003-0532-8681, García Valderas, Mario and López Ongil, Celia
(2018).
Embedded Emotion Recognition within Cyber-Physical Systems using Physiological Signals.
En: "2018 Conference on Design of Circuits and Integrated Systems (DCIS)", 14-16 November 2018, Lyon, France. pp. 1-6.
https://doi.org/10.1109/DCIS.2018.8681496.
ORCID: https://orcid.org/0000-0003-0532-8681, García Valderas, Mario and López Ongil, Celia
(2018).
Embedded Emotion Recognition within Cyber-Physical Systems using Physiological Signals.
En: "2018 Conference on Design of Circuits and Integrated Systems (DCIS)", 14-16 November 2018, Lyon, France. pp. 1-6.
https://doi.org/10.1109/DCIS.2018.8681496.
Descripción
| Título: | Embedded Emotion Recognition within Cyber-Physical Systems using Physiological Signals |
|---|---|
| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | 2018 Conference on Design of Circuits and Integrated Systems (DCIS) |
| Fechas del Evento: | 14-16 November 2018 |
| Lugar del Evento: | Lyon, France |
| Título del Libro: | 2018 Conference on Design of Circuits and Integrated Systems (DCIS) |
| Fecha: | 2018 |
| Materias: | |
| ODS: | |
| Palabras Clave Informales: | Cyber-Physical System; Wearable; Embedded System; Emotion Recognition; Machine Learning |
| Escuela: | Centro de Electrónica Industrial (CEI) (UPM) |
| Departamento: | Otro |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
Resumen
Cyber-Physical Systems (CPSs) are systems designed as a network of different interacting elements, which integrate computational and physical capabilities. The human-machine interaction plays a significant role in CPSs, especially in applications where people are an active element. In this context, emotion recognition is a relevant aspect to achieve a more efficient, collaborative, and resilient machine performance in collaboration with humans. On this basis, this paper proposes an embedded machine learning approach for emotion recognition fully implemented in an ultra low-power System-on-Chip (SoC) with limited resources. To this end, the intelligence system considers a reduced set of raw physiological signals within an approximate computing focus.
Proyectos asociados
Tipo
Código
Acrónimo
Responsable
Título
Gobierno de España
TEC2017-86722-C4-2-R
Sin especificar
Sin especificar
Sin especificar
Más información
| ID de Registro: | 55161 |
|---|---|
| Identificador DC: | https://oa.upm.es/55161/ |
| Identificador OAI: | oai:oa.upm.es:55161 |
| Identificador DOI: | 10.1109/DCIS.2018.8681496 |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 01 Feb 2023 15:17 |
| Ultima Modificación: | 01 Feb 2023 15:17 |
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