An automated and intelligent Parkinson disease monitoring system using wearable computing and cloud technology
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Software
Link
http://link.springer.com/content/pdf/10.1007/s10586-017-1591-z.pdf
Reference32 articles.
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2. Rispens, S.M., van Schooten, K.S., Pijnappels, M., Daffertshofer, A., Beek, P.J., van Dieën, J.H.: Do extreme values of daily-life gait characteristics provide more information about fall risk than median values? JMIR Res. Protoc. 4(1), e4 (2015). https://doi.org/10.2196/resprot.3931
3. Cancela, J., Pastorino, M., Moreno, E., Waldmeyer, M.A.: A mobile monitoring tool for the automatic activity recognition and its application for Parkinson’s disease rehabilitation. In: World Congress on Medical Physics and Biomedical Engineering, June 7–12, 2015, Toronto, Canada, pp. 1457–1460. Springer, New York (2015)
4. Cancela, J., Pastorino, M., Arredondo, M.T., Nikita, K.S., Villagra, F., Pastor, M.A.: Feasibility study of a wearable system based on a wireless body area network for gait assessment in Parkinson’s disease patients. Sensors 14(3), 4618–4633 (2014)
5. Caldara, M., Comotti, D., Galizzi, M., Locatelli, P., Re, V., Alimonti, D., Poloni, M., Rizzetti, M.C.: A novel body sensor network for Parkinson’s disease patients rehabilitation assessment. In: 2014 11th International Conference on Wearable and Implantable Body Sensor Networks (BSN), pp. 81–86. IEEE (2014)
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