Abstract
Breast cancer is the most common tumor in western women and statistically 1 out of 8 women will develop breast cancer over their lifetime. Once overcome it, the stage of rehabilitation that the patient should follow is critical to recover from the suffered disease. In this paper, a system composed of three applications, one for smartwatches, one for smartphones and a web application, is presented. Applications for handheld devices are directed to the patient who is undergoing rehabilitation and allow to monitor parameters of interest, such as the heart rate, energy expenditure and arm mobility, that will indicate whether the rehabilitation process being followed is improving the health of the patient or not. The web application is directed to a medical expert with the objective of tracking rehabilitation conducted by the patients.
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References
Merrell, R.C., Doarn, C.R.: m-health. Telemedicine e-Health 20(2), 99–101 (2014)
Liu, C., Zhu, Q., Holroyd, K.A., Seng, E.K.: Status and trends of mobile-health applications for ios devices: a developer’s perspective. J. Syst. Softw. 84(11), 2022–2033 (2011)
Sun, M., Burke, L.E., Mao, Z.-H., Chen, Y., Chen, H.-C., Bai, Y., Li, Y., Li, C., Jia, W.: ebutton: a wearable computer for health monitoring and personal assistance. In: Proceedings of the 51st Annual Design Automation Conference on Design Automation Conference, pp. 1–6. ACM (2014)
Mekky, S.: Wearable computing and the hype of tracking personal activity (2013)
Globocan 2012: Estimated cancer incidence, mortality and prevalence worldwide in 2012. http://globocan.iarc.fr/old/FactSheets/cancers/breast-new.asp. Accessed 23 Jan 2017
Arab, C., Dias, D.P.M., de Almeida Barbosa, R.T., de Carvalho, T.D., Valenti, V.E., Crocetta, T.B., Ferreira, M., de Abreu, L.C., Ferreira, C.: Heart rate variability measure in breast cancer patients and survivors: a systematic review. Psychoneuroendocrinology 68, 57–68 (2016)
Caro-Moran, E., Fernandez-Lao, C., Galiano-Castillo, N., Cantarero-Villanueva, I., Arroyo-Morales, M., Rodriguez, L.D.: Heart rate variability in breast cancer survivors after the first year of treatments a case-controlled study. Biol. Res. Nurs. 18(1), 43–49 (2016)
A new breast cancer study enlists fitbit trackers. https://blog.fitbit.com/a-new-breast-cancer-study-enlists-fitbit-trackers/. Accessed 5 July 2016
Jovanov, E.: Preliminary analysis of the use of smartwatches for longitudinal health monitoring. In: 37th Annual International Conference of the IEEE on Engineering in Medicine and Biology Society (EMBC 2015), pp. 865–868. IEEE (2015)
Banos, O., Amin, M.B., Khan, W.A., Afzal, M., Hussain, M., Kang, B.H., Lee, S.: The mining minds digital health and wellness framework. Biomed. Eng. Online 15(1), 165–186 (2016)
Banos, O., Villalonga, C., Garcia, R., Saez, A., Damas, M., Holgado, J.A., Lee, S., Pomares, H., Rojas, I.: Design, implementation and validation of a novel open framework for agile development of mobile health applications. Biomed. Eng. Online 14(S2:S6), 1–20 (2015)
Banos, O., Villalonga, C., Damas, M., Gloesekoetter, P., Pomares, H., Rojas, I.: Physiodroid: combining wearable health sensors and mobile devices for a ubiquitous, continuous, and personal monitoring. Sci. World J. 2014(490824), 1–11 (2014)
Mukhopadhyay, S.C.: Wearable sensors for human activity monitoring: a review. IEEE Sensors J. 15(3), 1321–1330 (2015)
Bovelli, D., Plataniotis, G., Roila, F., ESMO Guidelines Working Group, et al.: Cardiotoxicity of chemotherapeutic agents and radiotherapy-related heart disease: ESMO clinical practice guidelines. Ann. Oncol. 21(Suppl. 5), v277–v282 (2010)
Ruiz-Zafra, A., Orantes-González, E., Noguera, M., Benghazi, K., Heredia-Jimenez, J.: A comparative study on the suitability of smartphones and IMU for mobile, unsupervised energy expenditure calculi. Sensors 15(8), 18270–18286 (2015)
Patel, S., Park, H., Bonato, P., Chan, L., Rodgers, M.: A review of wearable sensors and systems with application in rehabilitation. J. Neuroeng. Rehabil. 9(1), 21 (2012)
Leuenberger, K., Gonzenbach, R., Wachter, S., Luft, A., Gassert, R.: A method to qualitatively assess arm use in stroke survivors in the home environment. Med. Biol. Eng. Comput. 55, 141–150 (2016)
Madgwick, S.O.H., Harrison, A.J.L., Vaidyanathan, R.: Estimation of IMU and MARG orientation using a gradient descent algorithm. In: 2011 IEEE International Conference on Rehabilitation Robotics, pp. 1–7. IEEE (2011)
Wearable API. https://developers.google.com/android/reference/com/google/android/gms/wearable/Wearable. Accessed 23 Jan 2017
Activity recognition API, November 2016. https://developers.google.com/android/reference/com/google/android/gms/location/ActivityRecognitionApi. Accessed 23 Jan 2017
Transmitting network data using volley. https://developer.android.com/training/volley/index.html. Accessed 23 Jan 2017
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Ollero, J., Moral-Munoz, J.A., Rojas, I., Banos, O. (2017). Mobile Health System for Evaluation of Breast Cancer Patients During Treatment and Recovery Phases. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2017. Lecture Notes in Computer Science(), vol 10209. Springer, Cham. https://doi.org/10.1007/978-3-319-56154-7_58
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DOI: https://doi.org/10.1007/978-3-319-56154-7_58
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