Searching across hundreds of databases

Our searching services are busy right now. Your search will reload in five seconds.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium.

M Encarna Micó-Amigo | Tecla Bonci | Anisoara Paraschiv-Ionescu | Martin Ullrich | Cameron Kirk | Abolfazl Soltani | Arne Küderle | Eran Gazit | Francesca Salis | Lisa Alcock | Kamiar Aminian | Clemens Becker | Stefano Bertuletti | Philip Brown | Ellen Buckley | Alma Cantu | Anne-Elie Carsin | Marco Caruso | Brian Caulfield | Andrea Cereatti | Lorenzo Chiari | Ilaria D'Ascanio | Bjoern Eskofier | Sara Fernstad | Marcel Froehlich | Judith Garcia-Aymerich | Clint Hansen | Jeffrey M Hausdorff | Hugo Hiden | Emily Hume | Alison Keogh | Felix Kluge | Sarah Koch | Walter Maetzler | Dimitrios Megaritis | Arne Mueller | Martijn Niessen | Luca Palmerini | Lars Schwickert | Kirsty Scott | Basil Sharrack | Henrik Sillén | David Singleton | Beatrix Vereijken | Ioannis Vogiatzis | Alison J Yarnall | Lynn Rochester | Claudia Mazzà | Silvia Del Din | Mobilise-D consortium
Journal of neuroengineering and rehabilitation | 2023

Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validate DMOs estimated using real-world gait data from six different cohorts, focusing on gait sequence detection, foot initial contact detection (ICD), cadence (CAD) and stride length (SL) estimates.

Pubmed ID: 37316858 RIS Download

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

None found

Associated grants

  • Agency: Wellcome Trust, United Kingdom
  • Agency: Department of Health, United Kingdom

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


MATLAB (tool)

RRID:SCR_001622

Multi paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.

View all literature mentions