Author:
Adhikary Arpan,Majumder Koushik,Chatterjee Santanu,Shaw Rabindra Nath,Ghosh Ankush
Publisher
Springer Nature Singapore
Reference12 articles.
1. Juutinen, M., Wang, C., Zhu, J., Haladjian, J., Ruokolainen, J., Puustinen, J., Vehkaoja, A.: Parkinson’s disease detection from 20-step walking tests using inertial sensors of a smartphone: machine learning approach based on an observational case-control study. PLoS ONE 15(7), e0236258 (2020)
2. Mazilu, S., Hardegger, M., Zhu, Z., Roggen, D., Tröster, G., Plotnik, M., Hausdorff, J.M.: Online detection of freezing of gait with smartphones and machine learning techniques. In: 2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops, pp. 123–130. IEEE (2012)
3. Tripoliti, E.E., et al.: Automatic detection of freezing of gait events in patients with Parkinson’s disease. Comput. Methods Programs Biomed. 110(1), 12–26 (2013)
4. Zhan, A., Little, M.A., Harris, D.A., Abiola, S.O., Dorsey, E., Saria, S., Terzis, A.: High frequency remote monitoring of Parkinson’s disease via smartphone: platform overview and medication response detection (2016). arXiv preprint arXiv:1601.00960
5. Anakal, S., Sandhya, P.: Clinical decision support system for chronic obstructive pulmonary disease using machine learning techniques. In: 2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT), pp. 1–5. IEEE (2017)
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