Towards a secure cloud repository architecture for the continuous monitoring of patients with mental disorders
IntroductionAdvances in Information Technology are transforming healthcare systems, with a focus on improving accessibility, efficiency, resilience, and service quality. Wearable devices such as smartwatches and mental health trackers enable continuous biometric data collection, offering significant...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Digital Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2025.1567702/full |
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| author | Dimitra Georgiou Stamatis Katsaounis Panayiotis Tsanakas Ilias Maglogiannis Parisis Gallos |
| author_facet | Dimitra Georgiou Stamatis Katsaounis Panayiotis Tsanakas Ilias Maglogiannis Parisis Gallos |
| author_sort | Dimitra Georgiou |
| collection | DOAJ |
| description | IntroductionAdvances in Information Technology are transforming healthcare systems, with a focus on improving accessibility, efficiency, resilience, and service quality. Wearable devices such as smartwatches and mental health trackers enable continuous biometric data collection, offering significant potential to enhance chronic disorder treatment and overall healthcare quality. However, these technologies introduce critical security and privacy risks, as they handle sensitive patient data.MethodsTo address these challenges, this paper proposes a security-by-design cloud-based architecture that leverages wearable body sensors for continuous patient monitoring and mental disorder prediction. The system integrates an Elasticsearch-powered backend to manage biometric data securely. A dedicated framework was developed to ensure confidentiality, integrity, and availability (CIA) of patient data through secure communication protocols and privacy-preserving mechanisms.ResultsThe proposed architecture successfully enables secure real-time biometric monitoring and data processing from wearable devices. The system is designed to operate 24/7, ensuring robust performance in continuously tracking both mental and physiological health indicators. The inclusion of Elasticsearch provides scalable and efficient data indexing and retrieval, supporting timely healthcare decisions.DiscussionThis work addresses key security and privacy challenges inherent in continuous biometric data collection. By incorporating a security-by-design approach, the proposed framework enhances trustworthiness in healthcare monitoring technologies. The solution demonstrates the feasibility of balancing real-time health monitoring needs with stringent data protection requirements. |
| format | Article |
| id | doaj-art-a165b375db434b8b9d4a58b250c8ea77 |
| institution | OA Journals |
| issn | 2673-253X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Digital Health |
| spelling | doaj-art-a165b375db434b8b9d4a58b250c8ea772025-08-20T02:37:41ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2025-06-01710.3389/fdgth.2025.15677021567702Towards a secure cloud repository architecture for the continuous monitoring of patients with mental disordersDimitra Georgiou0Stamatis Katsaounis1Panayiotis Tsanakas2Ilias Maglogiannis3Parisis Gallos4Department of Digital Systems, School of Information and Communication Technologies, University of Piraeus, Piraeus, GreeceDepartment of Electrical & Computer Engineering, School of Electrical and Computer Engineering, National Technical University of Athens, Athens, GreeceDepartment of Electrical & Computer Engineering, School of Electrical and Computer Engineering, National Technical University of Athens, Athens, GreeceDepartment of Digital Systems, School of Information and Communication Technologies, University of Piraeus, Piraeus, GreeceDepartment of Digital Systems, School of Information and Communication Technologies, University of Piraeus, Piraeus, GreeceIntroductionAdvances in Information Technology are transforming healthcare systems, with a focus on improving accessibility, efficiency, resilience, and service quality. Wearable devices such as smartwatches and mental health trackers enable continuous biometric data collection, offering significant potential to enhance chronic disorder treatment and overall healthcare quality. However, these technologies introduce critical security and privacy risks, as they handle sensitive patient data.MethodsTo address these challenges, this paper proposes a security-by-design cloud-based architecture that leverages wearable body sensors for continuous patient monitoring and mental disorder prediction. The system integrates an Elasticsearch-powered backend to manage biometric data securely. A dedicated framework was developed to ensure confidentiality, integrity, and availability (CIA) of patient data through secure communication protocols and privacy-preserving mechanisms.ResultsThe proposed architecture successfully enables secure real-time biometric monitoring and data processing from wearable devices. The system is designed to operate 24/7, ensuring robust performance in continuously tracking both mental and physiological health indicators. The inclusion of Elasticsearch provides scalable and efficient data indexing and retrieval, supporting timely healthcare decisions.DiscussionThis work addresses key security and privacy challenges inherent in continuous biometric data collection. By incorporating a security-by-design approach, the proposed framework enhances trustworthiness in healthcare monitoring technologies. The solution demonstrates the feasibility of balancing real-time health monitoring needs with stringent data protection requirements.https://www.frontiersin.org/articles/10.3389/fdgth.2025.1567702/fullhealthcare platformssecuritycloud computingelasticsearchsensors |
| spellingShingle | Dimitra Georgiou Stamatis Katsaounis Panayiotis Tsanakas Ilias Maglogiannis Parisis Gallos Towards a secure cloud repository architecture for the continuous monitoring of patients with mental disorders Frontiers in Digital Health healthcare platforms security cloud computing elasticsearch sensors |
| title | Towards a secure cloud repository architecture for the continuous monitoring of patients with mental disorders |
| title_full | Towards a secure cloud repository architecture for the continuous monitoring of patients with mental disorders |
| title_fullStr | Towards a secure cloud repository architecture for the continuous monitoring of patients with mental disorders |
| title_full_unstemmed | Towards a secure cloud repository architecture for the continuous monitoring of patients with mental disorders |
| title_short | Towards a secure cloud repository architecture for the continuous monitoring of patients with mental disorders |
| title_sort | towards a secure cloud repository architecture for the continuous monitoring of patients with mental disorders |
| topic | healthcare platforms security cloud computing elasticsearch sensors |
| url | https://www.frontiersin.org/articles/10.3389/fdgth.2025.1567702/full |
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