Recent machine learning advancements in sensor-based mobility analysis: Deep learning for Parkinson's disease assessment. - Björn M. Eskofier; Sunghoon Ivan Lee; Jean-Francois Daneault; Fatemeh Noushin Golabchi; Gabriela Ferreira-Carvalho; Gloria Vergara-Diaz; Stefano Sapienza; Gianluca Costante; Jochen Klucken; Thomas Kautz; Paolo Bonato (EMBC, 2016)

Using a Minimum Set of Wearable Sensors to Assess Quality of Movement in Stroke Survivors. - Stefano Sapienza; Catherine P. Adans-Dester; Anne T. O'Brien; Gloria Vergara-Diaz; Sunghoon Ivan Lee; Shyamal Patel; Randie Black-Schaffer; Ross Zafonte; Paolo Bonato; Claire Meagher; Ann-Marie Hughes; Jane H. Burridge; et al. (CHASE, 2017)

Human balance models optimized using a large-scale, parallel architecture with applications to mild traumatic brain injury. - Gregory A. Ciccarelli; Michael Nolan; Hrishikesh M. Rao; Tanya Talkar; Anne T. O'Brien; Gloria Vergara-Diaz; Ross Zafonte; Thomas F. Quatieri; Ryan J. McKindles; Paolo Bonato; Adam C. Lammert (HPEC, 2020)

Detection of Subclinical Mild Traumatic Brain Injury (mTBI) Through Speech and Gait. - Tanya Talkar; Sophia Yuditskaya; James R. Williamson; Adam C. Lammert; Hrishikesh Rao 002; Daniel J. Hannon; Anne T. O'Brien; Gloria Vergara-Diaz; Richard DeLaura; Douglas E. Sturim; Gregory A. Ciccarelli; Ross Zafonte; et al. (INTERSPEECH, 2020)

Enabling precision rehabilitation interventions using wearable sensors and machine learning to track motor recovery. - Catherine P. Adans-Dester; Nicolas Hankov; Anne T. O'Brien; Gloria Vergara-Diaz; Randie Black-Schaffer; Ross Zafonte; Jennifer G. Dy; Sunghoon Ivan Lee; Paolo Bonato (npj Digit. Medicine, 2020)

mHealth and wearable technology should replace motor diaries to track motor fluctuations in Parkinson's disease. - Michael Kelley Erb; Daniel R. Karlin; Bryan Ho; Kevin Thomas 004; Federico Parisi; Gloria P. Vergara-Diaz; Jean-Francois Daneault; Paul W. Wacnik; Hao Zhang 090; Tairmae Kangarloo; Charmaine Demanuele; Chris R. Brooks; et al. (npj Digit. Medicine, 2020)

Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge. - Solveig K. Sieberts; Jennifer Schaff; Marlena Duda; Bálint Á Pataki; Ming Sun; Phil Snyder; Jean-Francois Daneault; Federico Parisi; Gianluca Costante; Udi Rubin; Peter Banda; Yooree Chae; et al. (npj Digit. Medicine, 2021)

Predicting and Monitoring Upper-Limb Rehabilitation Outcomes Using Clinical and Wearable Sensor Data in Brain Injury Survivors. - Sunghoon Ivan Lee; Catherine P. Adans-Dester; Anne T. O'Brien; Gloria P. Vergara-Diaz; Randie Black-Schaffer; Ross Zafonte; Jennifer G. Dy; Paolo Bonato (IEEE Trans. Biomed. Eng., 2021)

Wearable Technology and Machine Learning to Monitor Upper-Limb Use in Brain Injury Survivors. - Cristiana Ernesto; Federico Parisi; Catherine P. Adans-Dester; Anne T. O'Brien; Gloria Vergara-Diaz; Randie Black-Schaffer; Ross Zafonte; Hugo Ferreira 001; Paolo Bonato (CHASE, 2022)