A Review on Deep Learning for Quality of Life Assessment Through the Use of Wearable Data
Quality of Life (QoL) assessment has evolved over time, encompassing diverse aspects of human existence beyond just health. This paper presents a comprehensive review of the integration of Deep Learning (DL) techniques in QoL assessment, focusing on the analysis of wearable data. QoL, as defined by...
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IEEE
2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10841411/ |
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| author | Vasileios Skaramagkas Ioannis Kyprakis Georgia S. Karanasiou Dimitris I. Fotiadis Manolis Tsiknakis |
| author_facet | Vasileios Skaramagkas Ioannis Kyprakis Georgia S. Karanasiou Dimitris I. Fotiadis Manolis Tsiknakis |
| author_sort | Vasileios Skaramagkas |
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| description | Quality of Life (QoL) assessment has evolved over time, encompassing diverse aspects of human existence beyond just health. This paper presents a comprehensive review of the integration of Deep Learning (DL) techniques in QoL assessment, focusing on the analysis of wearable data. QoL, as defined by the World Health Organisation, encompasses physical, mental, and social well-being, making it a multifaceted concept. Traditional QoL assessment methods, often reliant on subjective reports or informal questioning, face challenges in quantification and standardization. To address these challenges, DL, a branch of machine learning inspired by the human brain, has emerged as a promising tool. DL models can analyze vast and complex datasets, including patient-reported outcomes, medical images, and physiological signals, enabling a deeper understanding of factors influencing an individual's QoL. Notably, wearable sensory devices have gained prominence, offering real-time data on vital signs and enabling remote healthcare monitoring. This review critically examines DL's role in QoL assessment through the use of wearable data, with particular emphasis on the subdomains of physical and psychological well-being. By synthesizing current research and identifying knowledge gaps, this review provides valuable insights for researchers, clinicians, and policymakers aiming to enhance QoL assessment with DL. Ultimately, the paper contributes to the adoption of advanced technologies to improve the well-being and QoL of individuals from diverse backgrounds. |
| format | Article |
| id | doaj-art-72499331f2834b60bc6fc6f56aa9d017 |
| institution | Kabale University |
| issn | 2644-1276 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| series | IEEE Open Journal of Engineering in Medicine and Biology |
| spelling | doaj-art-72499331f2834b60bc6fc6f56aa9d0172025-01-28T00:02:11ZengIEEEIEEE Open Journal of Engineering in Medicine and Biology2644-12762025-01-01626126810.1109/OJEMB.2025.352645710841411A Review on Deep Learning for Quality of Life Assessment Through the Use of Wearable DataVasileios Skaramagkas0https://orcid.org/0000-0002-3279-8016Ioannis Kyprakis1Georgia S. Karanasiou2https://orcid.org/0000-0001-9478-0375Dimitris I. Fotiadis3https://orcid.org/0000-0002-5987-9350Manolis Tsiknakis4https://orcid.org/0000-0001-8454-1450Department of Electrical and Computer Engineering, Biomedical Informatics and eHealth Laboratory, Hellenic Mediterranean University, Heraklion, GreeceDepartment of Electrical and Computer Engineering, Biomedical Informatics and eHealth Laboratory, Hellenic Mediterranean University, Heraklion, GreeceUnit of Medical Technology Intelligent Information Systems, University of Ioannina, Ioannina, GreeceUnit of Medical Technology Intelligent Information Systems, University of Ioannina, Ioannina, GreeceDepartment of Electrical and Computer Engineering, Biomedical Informatics and eHealth Laboratory, Hellenic Mediterranean University, Heraklion, GreeceQuality of Life (QoL) assessment has evolved over time, encompassing diverse aspects of human existence beyond just health. This paper presents a comprehensive review of the integration of Deep Learning (DL) techniques in QoL assessment, focusing on the analysis of wearable data. QoL, as defined by the World Health Organisation, encompasses physical, mental, and social well-being, making it a multifaceted concept. Traditional QoL assessment methods, often reliant on subjective reports or informal questioning, face challenges in quantification and standardization. To address these challenges, DL, a branch of machine learning inspired by the human brain, has emerged as a promising tool. DL models can analyze vast and complex datasets, including patient-reported outcomes, medical images, and physiological signals, enabling a deeper understanding of factors influencing an individual's QoL. Notably, wearable sensory devices have gained prominence, offering real-time data on vital signs and enabling remote healthcare monitoring. This review critically examines DL's role in QoL assessment through the use of wearable data, with particular emphasis on the subdomains of physical and psychological well-being. By synthesizing current research and identifying knowledge gaps, this review provides valuable insights for researchers, clinicians, and policymakers aiming to enhance QoL assessment with DL. Ultimately, the paper contributes to the adoption of advanced technologies to improve the well-being and QoL of individuals from diverse backgrounds.https://ieeexplore.ieee.org/document/10841411/Deep learninghealthcaremachine learningquality of lifewearable data |
| spellingShingle | Vasileios Skaramagkas Ioannis Kyprakis Georgia S. Karanasiou Dimitris I. Fotiadis Manolis Tsiknakis A Review on Deep Learning for Quality of Life Assessment Through the Use of Wearable Data IEEE Open Journal of Engineering in Medicine and Biology Deep learning healthcare machine learning quality of life wearable data |
| title | A Review on Deep Learning for Quality of Life Assessment Through the Use of Wearable Data |
| title_full | A Review on Deep Learning for Quality of Life Assessment Through the Use of Wearable Data |
| title_fullStr | A Review on Deep Learning for Quality of Life Assessment Through the Use of Wearable Data |
| title_full_unstemmed | A Review on Deep Learning for Quality of Life Assessment Through the Use of Wearable Data |
| title_short | A Review on Deep Learning for Quality of Life Assessment Through the Use of Wearable Data |
| title_sort | review on deep learning for quality of life assessment through the use of wearable data |
| topic | Deep learning healthcare machine learning quality of life wearable data |
| url | https://ieeexplore.ieee.org/document/10841411/ |
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