%0 Generic %A Angelini, Lorenza %A Carpinella, Ilaria %A Cattaneo, Davide %A Ferrarin, Maurizio %A Gervasoni, Elisa %A sharrack, basil %A Paling, David %A Nair, K P Sivaraman %A Mazza, Claudia %D 2020 %T Data for paper "Is a wearable sensor based characterisation of gait robust enough to overcome differences between measurement protocols? A multi-centric pragmatic study in patients with Multiple Sclerosis" %U https://orda.shef.ac.uk/articles/dataset/Data_for_paper_Is_a_wearable_sensor_based_characterisation_of_gait_robust_enough_to_overcome_differences_between_measurement_protocols_A_multi-centric_pragmatic_study_in_patients_with_Multiple_Sclerosis_/11395641 %R 10.15131/shef.data.11395641.v1 %2 https://orda.shef.ac.uk/ndownloader/files/21923502 %K multiple sclerosis; gait metrics; wearable sensors; test-retest reliability; sampling frequency; accelerometry; autocorrelation; harmonic ratio; six-minute walk %K Biomechanical Engineering %X
This repository has been created to support the paper "Is a wearable sensor based characterisation of gait robust enough to overcome differences between measurement protocols? A multi-centric pragmatic study in patients with Multiple Sclerosis".
The excel file includes both demographic and clinical information of each participant (1st worksheet) and the gait outcomes extracted from the wearable sensors for each participant (mean and SD values, 2nd worksheet).
For details email l.angelini@sheffield.ac.uk
%I The University of Sheffield