Remote Monitoring of Treatment Response in Parkinson's Disease: The Habit of Typing on a Computer

Mov Disord. 2019 Oct;34(10):1488-1495. doi: 10.1002/mds.27772. Epub 2019 Jun 18.


Objective: The recent advances in technology are opening a new opportunity to remotely evaluate motor features in people with Parkinson's disease (PD). We hypothesized that typing on an electronic device, a habitual behavior facilitated by the nigrostriatal dopaminergic pathway, could allow for objectively and nonobtrusively monitoring parkinsonian features and response to medication in an at-home setting.

Methods: We enrolled 31 participants recently diagnosed with PD who were due to start dopaminergic treatment and 30 age-matched controls. We remotely monitored their typing pattern during a 6-month (24 weeks) follow-up period before and while dopaminergic medications were being titrated. The typing data were used to develop a novel algorithm based on recursive neural networks and detect participants' responses to medication. The latter were defined by the Unified Parkinson's Disease Rating Scale-III (UPDRS-III) minimal clinically important difference. Furthermore, we tested the accuracy of the algorithm to predict the final response to medication as early as 21 weeks prior to the final 6-month clinical outcome.

Results: The score on the novel algorithm based on recursive neural networks had an overall moderate kappa agreement and fair area under the receiver operating characteristic (ROC) curve with the time-coincident UPDRS-III minimal clinically important difference. The participants classified as responders at the final visit (based on the UPDRS-III minimal clinically important difference) had higher scores on the novel algorithm based on recursive neural networks when compared with the participants with stable UPDRS-III, from the third week of the study onward.

Conclusions: This preliminary study suggests that remotely gathered unsupervised typing data allows for the accurate detection and prediction of drug response in PD. © 2019 International Parkinson and Movement Disorder Society.

Keywords: Parkinson's disease; drug monitoring; machine learning; neural network; technology.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cognition / physiology
  • Female
  • Habits*
  • Humans
  • Male
  • Minimal Clinically Important Difference
  • Parkinson Disease / diagnosis
  • Parkinson Disease / drug therapy*
  • ROC Curve
  • Severity of Illness Index