fr
Thèse
Accès libre
Anglais

Enhancing wellbeing using artificial intelligence techniques

Contributeurs/tricesKyritsis, Athanasios
Date de soutenance2019-12-19
Résumé

The landscape of technology is rapidly evolving, and its pace of growth is not slowing down. During the last decades, and especially after the mass adoption of the internet, new technological advances have revolutionized every aspect of human life. We are living in the ubiquitous computing era, where connected devices form the internet of things and produce data faster than we can logically process. The goal of this thesis is to propose new algorithms, methodologies, and applications that can be used as components in health and wellbeing systems that support healthy aging, enhance human-machine interactions, and support postoperative rehabilitation with the use of machine learning techniques.

eng
Mots-clés
  • Abnormality detection
  • Active assisted living
  • Activity recognition
  • Ambient assisted living
  • Bluetooth
  • Bluetooth low energy
  • Deep learning
  • EHealth
  • Feature extraction
  • Health informatics
  • Indoor localization
  • Indoor positioning
  • Machine learning
  • MHealth
  • Mobile applications
  • Mobile devices
  • Neural networks
  • Pattern recognition
  • Postoperative rehabilitation
  • Room-level accuracy
  • RSSI
  • Senior citizens
  • Smart devices
  • Smartphones
  • Smartwatches
  • Stress detection
  • Survey
  • User requirements
  • Wearable computers
  • Wearable sensors
Citation (format ISO)
KYRITSIS, Athanasios. Enhancing wellbeing using artificial intelligence techniques. 2019. doi: 10.13097/archive-ouverte/unige:130751
Fichiers principaux (1)
Thesis
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Identifiants
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Informations techniques

Création12.02.2020 13:58:00
Première validation12.02.2020 13:58:00
Heure de mise à jour15.03.2023 21:08:37
Changement de statut15.03.2023 21:08:36
Dernière indexation29.01.2024 22:06:38
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