The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions

no code implementations • 22 Dec 2021 • Shaoxiong Sun, Amos A Folarin, Yuezhou Zhang, NIcholas Cummins, Shuo Liu, Callum Stewart, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Petroula Laiou, Heet Sankesara, Gloria Dalla Costa, Letizia Leocani, Per Soelberg Sørensen, Melinda Magyari, Ana Isabel Guerrero, Ana Zabalza, Srinivasan Vairavan, Raquel Bailon, Sara Simblett, Inez Myin-Germeys, Aki Rintala, Til Wykes, Vaibhav A Narayan, Matthew Hotopf, Giancarlo Comi, Richard JB Dobson, RADAR-CNS consortium

In this work, we extracted 96 activity features in different temporal granularities (from minute-level to day-level) and explored their utility in estimating 6MWT scores in a European (Italy, Spain, and Denmark) MS cohort of 337 participants over an average of 10-month duration.

Feature Importance feature selection +1

Fitbeat: COVID-19 Estimation based on Wristband Heart Rate

no code implementations • 19 Apr 2021 • Shuo Liu, Jing Han, Estela Laporta Puyal, Spyridon Kontaxis, Shaoxiong Sun, Patrick Locatelli, Judith Dineley, Florian B. Pokorny, Gloria Dalla Costa, Letizia Leocan, Ana Isabel Guerrero, Carlos Nos, Ana Zabalza, Per Soelberg Sørensen, Mathias Buron, Melinda Magyari, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Callum Stewart, Amos A Folarin, Richard JB Dobson, Raquel Bailón, Srinivasan Vairavan, NIcholas Cummins, Vaibhav A Narayan, Matthew Hotopf, Giancarlo Comi, Björn Schuller

This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data.

Specificity