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Measuring QoE of a Teleconsultation App in Mental Health Using a Pentagram Model

  • Systems-Level Quality Improvement
  • Published:
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Abstract

The QoE measurement has become a novel theme today. To achieve a quality service and minimize the negative impact that traffic on network can cause, it’s very important to manage the devices that intervene in this service. Hence, the QoE evaluation allows obtaining benefits both customers and service providers. The main objective of this paper is to measure QoE of a teleconsultation application in Mental Health named Psiconnect, using an approach based on pentagram model. For the QoE evaluation of Psiconnect application we used the pentagram model based on the measurement of 5 factors (integrality, retainability, availability, usability, and instantaneousness). This model allows to design quantifiable metrics for quality evaluations. Using the model cited the value of QoE for Psiconnect is 1.793 (between 1.6 and 1.8). Comparing with Mean Opinion Scores (MOS) test, some users are dissatisfied with the use of the application although the result is near 1.8, so the most of users are satisfied with the use of teleconsultation service based in Skype in the Psiconnect app. There are different models to measure QoE having into account subjective parameters. This is important an estimation of QoE in a quantitative form. Other models can be used to improve the quality of apps.

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References

  1. Ojanpera, T., Uitto, M., and Vehkapera, J., QoE-based management of medical video transmission in wireless networks. Proceeding of the IEEE Netw Oper Manag Symp.:1–6, 2014.

  2. Péteri, T., Varga, N., Bokor, L., A Survey on Multimedia Quality of Experience Assessment Approaches in Mobile Healthcare Scenarios. In: Springer, editor. eHealth 360°. 484–491, 2016.

    Google Scholar 

  3. Floris, A., and Atzori, L., Quality of experience in the multimedia internet of things : Definition and practical use- cases. Proc IEEE Int Conf Commun Work.:1747–1752, 2015.

  4. Ullah, M., Fiedler, M., and Wac, K., On the ambiguity of quality of service and quality of experience requirements for eHealth services. Proceeding of the6th. Int Symp Med Inf Commun Technol.:1–4, 2012.

  5. Li, L., Rong, M., and Zhang, G., An internet of things QoE evaluation method based on multiple linear regression analysis. Proc10th Int Conf Comput Sci Educ.:925–928, 2015.

  6. Ikeda, Y., Kouno, S., Shiozu, A., and Noritake, K., A framework of scalable QoE modeling for application explosion in the internet of things. ProcIEEE 3rd World Forum Internet Things, WF-IoT.:425–429, 2016.

  7. Kim, H. J., and Choi, S. G., QoE assessment model for multimedia streaming services using QoS parameters. Multimed. Tools Appl. 72(3):2163–2175, 2014.

    Article  Google Scholar 

  8. Gómez, G., Hortigüela, L., Pérez, Q., Lorca, J., García, R., and Aguayo-Torres, M. C., YouTube QoE evaluation tool for android wireless terminals. EURASIP J. Wirel. Commun. Netw. 164, 2014.

  9. Skorin-kapov, L., Varela, M. A., Multi-Dimensional View of QoE : the ARCU Model. Proceeding of theMIPRO, 2012 Proc 35th Int Conv. 662–666, 2012.

  10. Lounis, A., Alilat, F., Agoulmine, N., Neural Network Model of QoE for Estimation Video Streaming over 5G network. In: 2018 International Workshop on ADVANCEs in ICT Infrastructures and Services (ADVANCE’2018). 21, 2018.

  11. Volpato, F., Da Silva, M. P., Goncalves, A. L., and Dantas, M. A. R., An autonomic QoE-aware management architecture for software-defined networking. Proceeding of theIEEE 26th. Int Conf Enabling Technol Infrastruct Collab Enterp WETICE 2017:220–225, 2017.

  12. Gong, Y., Yang, F., Huang, L., and Su, S., Model-based approach to measuring quality of experience. Proceeding of the2009 First Int Conf Emerg Netw Intell:29–32, 2009.

  13. De la Torre Díez, I., Góngora Alonso, S., Hamrioui, S., López-Coronado, M., and Motta Cruz, E., Systematic review about QoS and QoE in telemedicine and eHealth services and applications. J. Med. Syst. 42(10):182, 2018.

    Article  Google Scholar 

  14. Martínez-Pérez B, De La Torre-Díez I, Candelas-Plasencia S, López-Coronado M. Development and evaluation of tools for measuring the quality of experience (QoE) in mHealth applications. J. Med. Syst. 2013;37(5):9976.

  15. Jing, H., and Wendong, W., A service implementation scenario measuring users’ QoE. J Beijing Univ Posts Telecommun. 30(2):106–109, 2007.

    Google Scholar 

  16. Sauro, J., and Kindlund, E., A method to standardize usability metrics into a single score. Proc SIGCHI Conf Hum factors Comput Syst.:401–409, 2005.

  17. Krasula, L., and Le Callet, P., Emerging science of QoE in multimedia applications: Concepts, experimental guidelines, and validation of models. In: Academic Press Library in. Signal Process.:163–209, 2018.

  18. Velasco-Morejón, D., and Martínez-Pérez, B., de la Torre-Díez I, López-Coronado M. PSICONNECT: A platform for communication between medical staff, caregivers and patients with psychiatric problems. e-Society. 101, 2014.

  19. Shin, D. H., Conceptualizing and measuring quality of experience of the internet of things: Exploring how quality is perceived by users. Inf. Manag. 54(8):998–1011, 2017.

    Article  Google Scholar 

  20. Moya Neyra, J., Alonso Irizar, C., and Anías, C. C., Evaluación de QoE en servicios IP basada en parámetros de QoS. Ing Electrónica, Automática y Comun. 38(3):36–46, 2017.

    Google Scholar 

  21. De Cicco L, Mascolo S, Palmisano V. QoE-driven resource allocation for massive video distribution. Ad Hoc Netw.2019; 89:170–176.

    Article  Google Scholar 

  22. Skorin-Kapov, L., and Matijasevic, M., Analysis of QoS requirements for e-health services and mapping to evolved packet system QoS classes. Int. J. Telemed. Appl. 9, 2010.

  23. Montero, R., Pagès, A., Agraz, F., and Spadaro, S., Supporting QoE/QoS-aware end-to-end network slicing in future 5G-enabled optical networks. Proc Metro and Data Center Optical Networks and Short-Reach Links II. International Society for Optics and Photonics.:109460F, 2019.

  24. Khokhar Muhammad, J., Saber Nawfal, A., Spetebroot, T., and Barakat, C., An intelligent sampling framework for controlled experimentation and QoE modeling. Comput. Netw. 147:246–261, 2018.

    Article  Google Scholar 

  25. Cavaro-Ménard, C., Lu, Z. G., Le Callet, P.. QoE for telemedicine: Challenges and trends. Proc Applications of Digital Image Processing XXXVI. International Society for Optics and Photonics. 88561A, 2013.

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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, France

    Eduardo Motta Cruz

  3. 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. Eduardo Motta Cruz
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  4. Manuel A. Franco
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Correspondence to Isabel de la Torre Díez.

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de la Torre Díez, I., Alonso, S.G., Cruz, E.M. et al. Measuring QoE of a Teleconsultation App in Mental Health Using a Pentagram Model. J Med Syst 43, 213 (2019). https://doi.org/10.1007/s10916-019-1342-1

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  • DOI: https://doi.org/10.1007/s10916-019-1342-1

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