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IoT-Based Services and Applications for Mental Health in the Literature

  • Systems-Level Quality Improvement
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Abstract

Internet of Things (IoT) has emerged as a new paradigm today, connecting a variety of physical and virtual elements integrated with electronic components, sensors, actuators and software to collect and exchange data. IoT is gaining increasing attention as a priority research topic in the Health sector in general and in specific areas such as Mental Health. The main objective of this paper is to show a review of the existing research works in the literature, referring to the main IoT services and applications in Mental Health diseases. The scientific databases used to carry out the review are Google Scholar, IEEE Xplore, PubMed, Science Direct, and Web of Science, taking into account as date of publication the last 10 years, from 2008 to the present. Several search criteria were established such as “IoT OR Internet of Things AND (Application OR Service) AND Mental Health” selecting the most interesting articles. A total of 51 articles were found on IoT-based services and applications in Mental Health, of which 14 have been identified as relevant works in mental health. Many of the publications (more than 60%) found show the applications developed for monitoring patients with mental disorders through sensors and networked devices. The inclusion of the new IoT technology in Health brings many benefits in terms of monitoring, welfare interventions and providing alert and information services. In pathologies such as Mental Health is a vital factor to improve the patient life quality and effectiveness of the medical service.

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References

  1. Dimitrov, D. V., Medical internet of things and big data in healthcare. Healthc. Inform. Res. 22(3):156–163, 2016.

    Article  Google Scholar 

  2. Zois, D. S., Sequential decision – Making in healthcare IoT : Real – Time health monitoring, Treatments and Interventions. 2016 IEEE 3rd World Forum Internet Things. ;24–29, 2016.

  3. Hassanalieragh, M., Page, A., Soyata, T., Sharma, G., Aktas, M., and Mateos, G. et al., Health monitoring and management using internet-of-things (IoT) sensing with cloud-based processing: opportunities and challenges. Proc. 2015 IEEE Int. Conf. Serv. Comput. SCC. 285–292, 2015.

  4. Hamrioui, S., and Lorenz, P., Efficient wireless mobile networks communications applied to e-health. 2017 IEEE Int. Conf. Commun. 1–6, 2017.

  5. Hamrioui, S., and Lorenz, P., Load balancing algorithm for efficient and reliable IoT communications within E-health environment. IEEE Glob. Commun. Conf. GLOBECOM 2017:1–6, 2017.

  6. Ahouandjinou, A. S. R. M., and Assogba, K., Motamed C. smart and pervasive ICU based-IoT for improving intensive health care. 2016 Int. Conf. Bio-Eng. Smart Technol. BioSMART 2016:1–4, 2016.

    Google Scholar 

  7. Hamrioui, S., Lorenz, P., Lloret, J., and Lalam, M., Energy efficient in medical ad hoc sensors network by exploiting routing protocols. 2014 IEEE Glob. Commun. Conf. GLOBECOM. 2417–2422, 2014.

  8. Wan, J., Gu, X., Chen, L., and Wang, J., Internet of things for ambient assisted living: Challenges and future opportunities. 2017 Int. Conf. Cyber-Enabled Distrib. Comput. Knowl. Discov. 354–357, 2017.

  9. Sahu, S., and Sharma, A., Detecting brainwaves to evaluate mental health using LabVIEW and applications. Proc. IEEE Int. Conf. Emerg. Technol. Trends Comput. Commun. Electr. Eng. ICETT 2017:3–6, 2016.

  10. Stellbrink, A., and Meisenzahl, E., Big data market analysis of e-health in medical neuroscience. Eur. Psychiatr. 41:S39, 2017.

    Article  Google Scholar 

  11. Medrano-Gil, A. M., de los Ríos Pérez, S., Fico, G., Montalvá Colomer, J. B., Cea Sáncez, G., Cabrera-Umpierrez, M. F., et al., Definition of technological solutions based on the internet of things and smart cities paradigms for active and healthy ageing through Cocreation. Wirel. Commun. Mob. Comput. 1–15, 2018.

  12. Ivascu, T., Manate, B., and Negru, V., A multi-agent architecture for ontology-based diagnosis of mental disorders. Proc. 17th Int. Symp. Symb. Numer. Algorithms Sci. Comput. SYNASC. 423–430, 2015.

  13. Aledavood, T., Hoyos, A. M. T., Alakörkkö, T., Kaski, K., Saramäki, J., Isometsä, E. et al., Data collection for mental health studies through digital platforms: requirements and design of a prototype. JMIR Res. Protoc. 6(6):e110, 2017.

    Article  Google Scholar 

  14. Saha, H. N., Auddy, S., Pal, S., Kumar, S., Pandey, S., and Singh, R., et al., Health monitoring using internet of things (IoT). 2017 8th. Annu. Ind. Autom. Electromech. Eng. Conf. 69–73, 2017.

  15. Darshan, K. R., and Anandakumar, K. R., A comprehensive review on usage of internet of things (IoT) in healthcare system. 2015 Int. Conf. Emerg. Res. Electron. Comput. Sci. Technol. ICERECT. 132–136, 2015.

  16. Baig, M. M., GholamHosseini, H., Moqeem, A. A., Mirza, F., and Lindén, M., A systematic review of wearable patient monitoring systems – current challenges and opportunities for clinical adoption. J. Med. Syst. 41(7):115, 2017.

    Article  Google Scholar 

  17. Hayati, N., and Suryanegara, M., The IoT LoRa system design for tracking and monitoring patient with mental disorder. 2017 IEEE. Int. Conf. Commun. Netw. Satell. COMNETSAT 2017 - Proc. 135–139, 2017.

  18. Bone, D., Lee, C.-C., Chaspari, T., Gibson, J., and Narayanan, S., Signal processing and machine learning for mental health research and clinical applications [perspectives]. IEEE Sign. Process Mag. 34(5):196–195, 2017.

    Article  Google Scholar 

  19. Alam, M. G. R., Abedin, S. F., Al, A. M., and Hong, C. S., Web of objects based ambient assisted living framework for emergency psychiatric state prediction. Sensors. 16(9):1431, 2016.

    Article  Google Scholar 

  20. Lekjaroen, K., Ponganantayotin, R., Charoenrat, A., Funilkul, S., Supasitthimethee, U., and Triyason, T., IoT planting: Watering system using mobile application for the elderly. 20th Int. Comput. Sci. Eng. Conf. ICSEC. 1–6, 2016.

  21. Raji, A., Jeyasheeli, P. G., and Jenitha, T., IoT based classification of vital signs data for chronic disease monitoring. 2016 10th Int Conf Intell Syst Control. 1–5, 2016.

  22. Cosma, G., Brown, D., Battersby, S., Kettley, S., and Kettley, R., Analysis of multimodal data obtained from users of smart textiles designed for mental wellbeing. Int. Conf. Internet Things Glob. Commun. 1–6, 2017.

  23. Babar, M., Rahman, A., Arif, F., and Jeon, G., Energy-harvesting based on internet of things and big data analytics for smart health monitoring. Sustain Comput. Inform. Syst. 2017.

  24. Kim, J. C., and Chung, K., Depression index service using knowledge based crowdsourcing in smart health. Wirel. Pers. Commun. 93(1):255–268, 2017.

    Article  Google Scholar 

  25. McWhorter, J., Brown, L., and Khansa, L., A wearable health monitoring system for posttraumatic stress disorder. Biol. Inspired Cogn. Archit. 22:44–50, 2017.

    Google Scholar 

  26. Glenn T, Monteith S. New measures of mental state and behavior based on data collected from sensors, smartphones, and the Internet. Curr. Psychiatr. Rep. 2014;16(12):523.

  27. Mighali, V., Patrono, L., Stefanizzi, M. L., Rodrigues, J. J. P. C., and Solic, P., A smart remote elderly monitoring system based on IoT technologies. Int. Conf. Ubiquitous Futur. Netw. ICUFN. 43–48, 2017.

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Acknowledgements

This research has been made within the Program “Movilidad Investigadores UVA-BANCO SANTANDER 2018”, and it has been partially supported by European Commission and the Ministry of Industry, Energy and Tourism under the project AAL-20125036 named “Wetake Care: ICT- based Solution for (Self-) Management of Daily Living”.

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Authors and Affiliations

  1. Department of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain

    Isabel de la Torre Díez & Susel Góngora Alonso

  2. Bretagne Loire and Nantes Universities, UMR 6164, IETR Polytech Nantes, Nantes, France

    Sofiane Hamrioui & Eduardo Motta Cruz

  3. Nozaleda and Lafora Mental Health Clinic, C/ José Ortega Y Gasset, 44, 28006, Madrid, Spain

    Lola Morón Nozaleda

  4. Psiquiatry Service, Hospital Zamora, Hernán Cortés, Zamora, Spain

    Manuel A. Franco

Authors
  1. Isabel de la Torre Díez
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  2. Susel Góngora Alonso
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  3. Sofiane Hamrioui
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  4. Eduardo Motta Cruz
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  5. Lola Morón Nozaleda
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  6. Manuel A. Franco
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Correspondence to Isabel de la Torre Díez.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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This article is part of the Topical Collection on Systems-Level Quality Improvement

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de la Torre Díez, I., Alonso, S.G., Hamrioui, S. et al. IoT-Based Services and Applications for Mental Health in the Literature. J Med Syst 43, 11 (2019). https://doi.org/10.1007/s10916-018-1130-3

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  • DOI: https://doi.org/10.1007/s10916-018-1130-3

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