Wearable sensors for Parkinson's disease: which data are worth collecting for training symptom detection models. - Luca Lonini; Andrew Dai 002; Nicholas Shawen; Tanya Simuni; Cynthia Poon; Leo Shimanovich; Margaret Daeschler; Roozbeh Ghaffari; John A. Rogers; Arun Jayaraman (npj Digit. Medicine, 2018)

Feasibility and utility of a clinician dashboard from wearable and mobile application Parkinson's disease data. - Jordan J. Elm; Margaret Daeschler; Lauren Bataille; Ruth B. Schneider; Amy W. Amara; Alberto J. Espay; Michal Afek; Chen Admati; Abeba Teklehaimanot; Tanya Simuni (npj Digit. Medicine, 2019)

A Predictive Model for Parkinson's Disease Reveals Candidate Gene Sets for Progression Subtype. - Saya R. Dennis; Tanya Simuni; Yuan Luo 001 (BIBM, 2020)

Deep Learning for Daily Monitoring of Parkinson's Disease Outside the Clinic Using Wearable Sensors. - Roozbeh Atri; Kevin Urban; Barbara Marebwa; Tanya Simuni; Caroline Tanner; Andrew Siderowf; Mark Frasier; Magali Haas; Lee Lancashire (Sensors, 2022)

Exploratory digital outcome measures of motor sign progression in Parkinson's disease patients treated with prasinezumab. - Kirsten I. Taylor; Florian Lipsmeier; Marzia Antonella Scelsi; Ekaterina Volkova-Volkmar; Daria Rukina; Werner Popp; Stefan Lambrecht; Judith Anzures-Cabrera; David Summers; Markus Abt; Annabelle Monnet; Timothy Kilchenmann; et al. (npj Digit. Medicine, 2025)