A wavelet-based approach to monitoring Parkinson's disease symptoms

@article{Wagner2017AWA,
  title={A wavelet-based approach to monitoring Parkinson's disease symptoms},
  author={Avishai Wagner and Naama Fixler and Yehezkel S. Resheff},
  journal={2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2017},
  pages={5980-5984}
}
Parkinson's disease is a neuro-degenerative disorder affecting tens of millions of people worldwide. Lately, there has been considerable interest in systems for at-home monitoring of patients, using wearable devices which contain inertial measurement units. We present a new wavelet-based approach for analysis of data from single wrist-worn smart-watches, and show high detection performance for tremor, bradykinesia, and dyskinesia, which have been the major targets for monitoring in this context… 

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