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Name Mobilise-D
Long Name Connecting digital mobility assessment to clinical outcomes for regulatory and clinical endorsement
Description Connecting digital mobility assessment to clinical outcomes for regulatory and clinical endorsement. Mobilise-D will develop a comprehensive system to monitor and evaluate people’s gait based on digital technologies, including sensors worn on the body. The project focuses on conditions which often affect mobility, namely chronic obstructive pulmonary disease, Parkinson’s disease, multiple sclerosis, hip fracture recovery, and congestive heart failure. The Mobilise-D results will help to improve the accurate assessment of daily life mobility in clinical trials and patient treatment, thereby contributing to improve and more personalised care.
Objectives 1. Define through consensus, literature review and technical development, optimal digital mobility outcomes for clinical validation. 2. Use our clinical networks to leverage existing and new cohorts to support clinical validation of digital mobility outcomes. 3. Determine the clinical validity of digital mobility outcomes. 4. Build a platform for robust digital-data management, defining standards for storage, analysis and sharing of digital mobility data. 5. Define and set the standards for technology-unbiased digital mobility assessment. 6. Create enduring impact by establishing the largest biobank of digital mobility data to support ongoing algorithm development, as well as technical and clinical validation. 7. Ensure dissemination of the project results and sustainability beyond the life of the project.
Website https://www.mobilise-d.eu/
Start date 01-04-2019
End date 31-03-2024
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Name Projects Type of institution Country  
Sanofi-Aventis Recherche & Developpement EPAD EQIPD AETIONOMY IM2PACT PHAGO NEURONET Mobilise-D IDEA-FAST EPND EFPIA France
Amgen EPAD EMIF Mobilise-D EFPIA Belgium
Novartis Pharma AG EPAD IMPRiND EQIPD AETIONOMY IM2PACT PRISM RADAR-AD ROADMAP Mobilise-D Pharma-Cog EPND EFPIA Switzerland
Pfizer Limited EPAD EQIPD EMIF IM2PACT PRISM Mobilise-D IDEA-FAST EFPIA United Kingdom
Alma Mater Studiorum - Universita Di Bologna PRISM Mobilise-D PRISM2 Academia Italy
Merck Kommanditgesellschaft Auf Aktien EMIF Mobilise-D Pharma-Cog EFPIA Germany
Imperial College Of Science Technology And Medicine EQIPD Mobilise-D IDEA-FAST Academia United Kingdom
The University Of Sheffield IM2PACT Mobilise-D Academia United Kingdom
Astrazeneca AB MOPEAD PHAGO Mobilise-D IDEA-FAST PD-MIND Pharma-Cog EFPIA Sweden
Teva Pharmaceutical Industries Limited PD-MitoQUANT Mobilise-D EQIPD EPND EFPIA Israel
Katholieke Universiteit Leuven RADAR-CNS Mobilise-D Academia Belgium
Universita Vita-Salute San Raffaele RADAR-CNS Mobilise-D Academia Italy
Universitatsklinikum Erlangen EMIF Mobilise-D Academia Germany
Bayer Aktiengesellschaft Mobilise-D EFPIA Germany
Eresearch Technology Inc Mobilise-D EFPIA United States
Grunenthal GMBH Mobilise-D EFPIA Germany
Icon Clinical Research Limited Mobilise-D EFPIA Ireland
Centre Hospitalier Universitaire Montpellier Mobilise-D Academia France
Christian-Albrechts-Universitaet Zu Kiel Mobilise-D IDEA-FAST Academia Germany
Ecole Polytechnique Federale De Lausanne Mobilise-D Academia Switzerland
Friedrich-Alexander-Universitaet Erlangen Nuernberg Mobilise-D Academia Germany
Fundación Privada Instituto de Salud Global Barcelona Mobilise-D Academia Spain
Norges teknisk-naturvitenskapelige universitet - NTNU Mobilise-D Academia Norway
Robert Bosch Gesellschaft Fur Medizinische Forschung Mbh Mobilise-D Academia Germany
The Foundation For Medical Research Infrastructural Development And Health Services Next To The Medical Center Tel Aviv Mobilise-D Academia Israel
Universitat Zurich Mobilise-D Academia Switzerland
University College Dublin, National University Of Ireland, Dublin Mobilise-D Academia Ireland
University Of Newcastle Upon Tyne Mobilise-D IDEA-FAST Academia United Kingdom
University Of Northumbria At Newcastle Mobilise-D Academia United Kingdom
Ixscient Limited, Uxbridge Mobilise-D IDEA-FAST SME United Kingdom
McRoberts BV Mobilise-D IDEA-FAST SME Netherlands
Penumologisches Forschungsinstitutan Der Lungenclinic Grosshansdorf GMBH Mobilise-D SME Germany
Universita Degli Studi Di Sassari Mobilise-D Academia Italy
Sheffield Teaching Hospitals NHS Foundation Trust Mobilise-D Other United Kingdom
The Newcastle Upon Tyne Hospitals NHS Foundation Trust Mobilise-D Other United Kingdom
Takeda Pharmaceuticals International AG EPND EPAD PRISM RADAR-AD ROADMAP IDEA-FAST Mobilise-D NEURONET EFPIA Switzerland
WP number Description Project  
WP1 Project management and oversight Mobilise-D
WP2 Algorithm development and technical validation Mobilise-D
WP3 Database development and data management Mobilise-D
WP4 Definition and validation of digital mobility outcomes against clinical endpoints Mobilise-D
WP5 Regulatory, HTA and payer consensus over operational definitions Mobilise-D
WP6 Statistical analysis, evaluation of results and data availability Mobilise-D
WP7 Stakeholder information and results dissemination and exploitation Mobilise-D
Deliverable number Title Project Submission date Link Keywords  
D2.3 First study subject approvals package Mobilise-D 30-06-2020 https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5d18132a8&appId=PPGMS Validation study, outcomes, training, data, collection, analysis, study, recruitment
D1.2 Risk Assessment Process and Management Procedure Mobilise-D 29-05-2019 https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5d1814266&appId=PPGMS Risk Assessment Process, Management Procedure
D7.2 Report on publications, presentations, and event organisation Mobilise-D 30-03-2020 https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5cda4b4af&appId=PPGMS publications, presentations, event, dissemination, communication
D3.1 System Requirements Specification (including definition of data acquisition, transmission, integration, processing, analysics and governance requirements) Mobilise-D 30-04-2020 https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5cec0eeb3&appId=PPGMS System Requirements Specification, data acquisition, transmission, integration, processing, analysics, governance
D1.3 Mobilise-D Data Management Plan Mobilise-D 30-09-2019 https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5c7d5bbad&appId=PPGMS Technical validation study, description of data, data collection, data organisation, metadata, data storage, data security, data generation, data sharing, data re-use
D2.2 Gold standard solutions for technical validation Mobilise-D 31-03-2019 https://www.mobilise-d.eu/wp-content/uploads/2020/12/Summary_D2.2.pdf
D4.1 Updated systematic review on primary and secondary clinical endpoints Mobilise-D 31-03-2020 https://www.mobilise-d.eu/wp-content/uploads/2020/12/Symmary_D4.1-Updated-systematic-review-on-clinical-endpoints.pdf
D7.1 Communication plan and Dissemination strategy, including project identity Mobilise-D 30-09-2019 https://www.mobilise-d.eu/wp-content/uploads/2020/12/Summary_D7.1-Communication-and-Dissemination-strategy-1.pdf
D7.3 Guidelines for open access and data sharing Mobilise-D 31-03-2020 https://www.mobilise-d.eu/wp-content/uploads/2020/12/Summary_D7.3-Guidelines-for-open-access-and-data-sharing.pdf
D4.2 Ethical approval including all amendments Mobilise-D 08-01-2021 https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5d7d4ab55&appId=PPGMS
D6.1 Statistical description report on digital mobility outcomes, health outcomes and their relationships Mobilise-D 31-12-2020 https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5d797d306&appId=PPGMS
D1.4 Data Management Plan V2 Mobilise-D 30-09-2021 https://www.mobilise-d.eu/wp-content/uploads/2022/01/Mobilise-D-Deliverable-D1.4-Data-Management-Plan-2-V1.0.pdf
D2.1 Digital mobility database of existing real-world and laboratory data and algorithms Mobilise-D 01-01-2020 https://www.mobilise-d.eu/wp-content/uploads/2020/12/Summary_D2.1-Digital-mobility-database-of-existing-RW-and-lab-data-and-alg-confidential.pdf
D2.4 Midterm recruitment report Mobilise-D 01-11-2020 https://www.mobilise-d.eu/wp-content/uploads/2022/01/Summary_D2.4-Midterm-recruitment-report.pdf
D2.5 Implemented algorithms for WB detection, step detection, RWS estimate, secondary outcomes and confounders Mobilise-D 01-11-2020 https://www.mobilise-d.eu/wp-content/uploads/2022/01/Summary_D2.5-Implemented-algorithms.pdf
D3.2 Platform build, implementation and testing with relevant stakeholder groups Mobilise-D 01-12-2020 https://www.mobilise-d.eu/wp-content/uploads/2022/01/Summary_D3.2-Platform-build-implementation-and-testing.pdf
D3.3 Suite of patient and investigator facing software tools for data capture Mobilise-D 01-12-2020 https://www.mobilise-d.eu/wp-content/uploads/2022/01/Summary_D3.3-Suite-of-patient-and-investigator-facing-software-tools-for-data-capture.pdf
D3.4 Integrated end to end data collection, management and analytics platform Mobilise-D 01-03-2021 https://www.mobilise-d.eu/wp-content/uploads/2022/01/Summary_D3.4-Integrated-end-to-end-data-collection-management-and-analytics-platform.pdf
D4.3 First study subject approvals package of the CVS Mobilise-D 01-12-2020 https://www.mobilise-d.eu/wp-content/uploads/2022/01/Summary_D4.3-First-study-subject-approvals-package-of-the-CVS.pdf
D5.1 Regulatory Plan Mobilise-D 01-10-2020 https://www.mobilise-d.eu/wp-content/uploads/2022/01/Summary_D5.1-Regulatory-Plan.pdf
D5.2 Regulatory Plan Mobilise-D 01-10-2020 https://www.mobilise-d.eu/wp-content/uploads/2022/01/Summary_D5.2-Regulatory-Plan.pdf
D7.4 Initial Exploitation Strategy Mobilise-D 01-03-2021 https://www.mobilise-d.eu/wp-content/uploads/2022/01/Summary_D7.4-Initial-Exploitation-Strategy.pdf
Title First author last name Year Project Link Keywords  
Wearable sensors can reliably quantify gait alterations associated with disability in people with progressive multiple sclerosis in a clinical setting Angelini 2020 Mobilise-D https://doi.org/10.1007/s00415-020-09928-8 test-retest reliability, Gait analysis, Balance, Temporal parameters, Regularity, Six-minute walk, clinical,
A wearable sensor identifies alterations in community ambulation in multiple sclerosis: contributors to real-world gait quality and physical activity Shema-Shiratzky 2020 Mobilise-D https://doi.org/10.1007/s00415-020-09759-7 Accelerometer, Activity, Daily living, Gait, Inertial measurement units, Multiple sclerosis, Wearables
Detection of Gait From Continuous Inertial Sensor Data Using Harmonic Frequencies Ullrich 2020 Mobilise-D https://doi.org/10.1109/JBHI.2020.2975361 algorithm, gait, sensor, cyclic activities
Gait variability as digital biomarker of disease severity in Huntington’s disease Gaßner 2020 Mobilise-D https://doi.org/10.1007/s00415-020-09789-1 Huntington’s disease, Gait analysis, Wearable sensors, Gait variability, Regularity of gait
Long-term unsupervised mobility assessment in movement disorders Warmerdam 2020 Mobilise-D https://doi.org/10.1016/S1474-4422(19)30397-7 mobile, wearable, assessment
Accelerometry-based digital gait characteristics for classification of Parkinson’s disease: what counts? Rehman 2020 Mobilise-D https://doi.org/10.1109/OJEMB.2020.2966295 Spatiotemporal phenomena , Tools , Accelerometers , Parkinson's disease , Data models , Complexity theory
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 Angelini 2019 Mobilise-D https://doi.org/10.3390/s20010079 Accelerometry, instrumentation, Accelerometry, Gait, Multiple Sclerosis, physiopathology, Retrospective Studies, Wearable Electronic Devices
Credibility of In Silico Trial Technologies—A Theoretical Framing Viceconti 2019 Mobilise-D http://dx.doi.org/10.1109/JBHI.2019.2949888 In silico medicine , in silico trials , in silico-augmented clinical trials , credibility of predictive models , regulatory science , biomedical products
Orientation Estimation Through Magneto-Inertial Sensor Fusion: A Heuristic Approach for Suboptimal Parameters Tuning Caruso 2020 Mobilise-D https://ieeexplore.ieee.org/document/9201115/keywords#keywords Magnetic separation, Sensor fusion, Optical filters, Magnetometers, Accelerometers, Filtering algorithms
Clinical Relevance of Standardized Mobile Gait Tests. Reliability Analysis Between Gait Recordings at Hospital and Home in Parkinson’s Disease: A Pilot Study Gaßner 2020 Mobilise-D https://content.iospress.com/articles/journal-of-parkinsons-disease/jpd202129 Parkinson’s disease, gait analysis, wearable sensors, telemedicine, home monitoring
Walking-related digital mobility outcomes as clinical trial endpoint measures: protocol for a scoping review Polhemus 2020 Mobilise-D https://bmjopen.bmj.com/content/bmjopen/10/7/e038704.full.pdf Parkinson-s disease; chronic airways disease; geriatric medicine; multiple sclerosis; orthopaedic & trauma surgery; telemedicine.
A roadmap to inform development, validation and approval of digital mobility outcomes: the Mobilise-D approach Rochester 2020 Mobilise-D https://doi.org/10.1159/000512513 Remote Monitoring, Body-worn devices, Digital mobility outcomes
Toward a Regulatory Qualification of Real-World Mobility Performance Biomarkers in Parkinson’s Patients Using Digital Mobility Outcomes Viceconti 2020 Mobilise-D https://doi.org/10.3390/s20205920 Regulatory Qualification, Real-World Mobility, Performance Biomarkers, Parkinson, Digital Mobility, Outcome
An Objective Methodology for the Selection of a Device for Continuous Mobility Assessment Bonci 2020 Mobilise-D https://doi.org/10.3390/s20226509 continuous monitoring, digital mobility outcomes, healthcare challenges, inertial measurement units, mobility assessment, real-world assessment, wearable technology.
Inertial sensor-based gait parameters reflect patient-reported fatigue in multiple sclerosis Ibrahim 2020 Mobilise-D https://doi.org/10.1186/s12984-020-00798-9 MS, Gait, Fatigue, Accelerometer, IMU, Machine learning, Digital biomarker
Body-Worn Sensors for Remote Monitoring of Parkinson’s Disease Motor Symptoms: Vision, State of the Art, and Challenges Ahead Del Din 2021 Mobilise-D https://doi.org/10.3233/JPD-202471 Parkinson’s disease, remote monitoring, real-world, wearables, motor symptoms, accelerometer, review article
Computational modelling of the scoliotic spine: A literature review Gould 2021 Mobilise-D https://doi.org/10.1002/cnm.3503 finite element modelling, multibody modelling, musculoskeletal modelling, review, scoliosis, scoliotic spine
Consensus based framework for digital mobility monitoring Kluge 2021 Mobilise-D https://doi.org/10.1371/journal.pone.0256541 Gait analysis, Walking, Feet, Consortia, Biological locomotion, Research assessment, Parkinson disease, Taxonomy,
A Proposal for a Linear Calculation of Gait Asymmetry van Gelder 2021 Mobilise-D https://doi.org/10.3390/sym13091560 asymmetry; gait; accelerometer; IMU
Assessing the usability of wearable devices to measure gait and physical activity in chronic conditions: a systematic review Keogh 2021 Mobilise-D https://doi.org/10.1186/s12984-021-00931-2 Usability, Wearable sensors, Gait, Physical activity, User experience
Extension of the Rigid-Constraint Method for the Heuristic Suboptimal Parameter Tuning to Ten Sensor Fusion Algorithms Using Inertial and Magnetic Sensing Caruso 2021 Mobilise-D https://doi.org/10.3390/s21186307 AHSR; MARG; MIMU; complementary filter; filter parameter tuning; human motion analysis; kalman filter; optimal parameter; orientation estimation; sensor fusion; suboptimal parameter; wearable sensors.
Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes Polhemus 2021 Mobilise-D https://doi.org/10.1038/s41746-021-00513-5 Geriatrics, Movement disorders, Predictive markers, Respiratory tract diseases,
Algorithms for Walking Speed Estimation Using a Lower-Back-Worn Inertial Sensor: A Cross-Validation on Speed Ranges Soltani 2021 Mobilise-D https://doi.org/10.1109/TNSRE.2021.3111681 Legged locomotion , Statistics , Sociology , Estimation , Instruments , Accelerometers , Walking speed , step length , cadence , inertial sensors , slow walkers , walking aids Three-dimensional displays
It’s not about the capture, it’s about what we can learn”: a qualitative study of experts’ opinions and experiences regarding the use of wearable sensors to measure gait and physical activity Keogh 2021 Mobilise-D https://doi.org/10.1186/s12984-021-00874-8 Wearable devices, Acceptability, Remote monitoring, Qualitative, Accelerometry
Technical validation of real-world monitoring of gait: a multicentric observational study Mazzà 2021 Mobilise-D http://dx.doi.org/10.1136/bmjopen-2021-050785 chronic airways disease; heart failure; hip; multiple sclerosis; parkinson's disease.
A Quality Control Check to Ensure Comparability of Stereophotogrammetric Data between Sessions and Systems Scott 2022 Mobilise-D https://doi.org/10.3390/s21248223 optoelectronic stereophotogrammetry; 3D motion capture; quality control; spot check; accuracy; systematic errors; gait; human movement
Investigating the Impact of Environment and Data Aggregation by Walking Bout Duration on Parkinson’s Disease Classification Using Machine Learning Zia Ur Rehman 2022 Mobilise-D https://doi.org/10.3389/fnagi.2022.808518 Gait, real-world data, Parkinson's disease, machine learning, real-world gait
An Algorithm for Accurate Marker-Based Gait Event Detection in Healthy and Pathological Populations During Complex Motor Tasks Bonci 2022 Mobilise-D http://dx.doi.org/10.3389/fbioe.2022.868928 gait analysis, spatio-temporal gait parameters, gait cycle, stride length, stride duration, stride speed, stereophotogrammetry
Title Description Type Project  
Using musculoskeletal models to estimate in vivo TKR kinematics and loads: effect of differences between models

The dataset contains the results of the simulations performed to estimate in vivo total knee replacement (TKR) kinematics and loads presented in the paper “C. Curreli, F. Di Puccio, G. Davico, L. Modenese, and M. Viceconti, Using Musculoskeletal Models to Estimate in vivo Total Knee Replacement Kinematics and Loads: Effect of Differences Between Models, Frontiers in Bioengineering and Biotechnology, vol. 9, p. 611, 2021, doi: 10.3389/fbioe.2021.703508”. Specifically, the dataset contains a comparison of the kinematic and dynamic results obtained with three different musculoskeletal models developed using the OpenSim software. A comparison between the predicted joint reaction forces and the in vivo loads measured by the instrumented knee implant is also reported. Experimental data used for the simulations were obtained from the fifth edition of the “Grand Challenge Competitions to Predict in vivo Knee Loads” (https://simtk.org/projects/kneeloads).

http://amsacta.unibo.it/6756/

dataset-clinical-mobilise-d-14 Mobilise-D
A Roadmap to Inform Development, Validation and Approval of Digital Mobility Outcomes

Because loss of mobility is an important feature of many health conditions, there is a need for regulatory accepted walking-related digital mobility outcomes (DMOs) as clinical trial endpoint measures in a variety of disease states. To achieve this, the consortium has elaborated a roadmap that is published (A Roadmap to Inform Development, Validation and Approval of Digital Mobility Outcomes: The Mobilise-D Approach). Part of the roadmap is the technical validation study. The consortium has started to recruit the 120 participants for this study (healthy older adults, Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, proximal femoral fracture) across sites in 3 countries: Germany, United Kingdom and Israel. The conduct of study is challenging due to the COVID-19 pandemic and recruitment is slower than anticipated. This study will identify the best algorithms to quantify real-world walking speed and other relevant characteristics to describe the way we walk using a variety of advanced technology that will then be taken for further clinical validation.

https://www.karger.com/Article/FullText/512513

tools-clinical-mobilise-d-14 Mobilise-D
Sensor fusion algorithm

The orientation of a magneto-inertial measurement unit can be estimated using a sensor fusion algorithm (SFA). However, orientation accuracy is greatly affected by the choice of the SFA parameter values which represents one of the most critical steps. A commonly adopted approach is to fine-tune parameter values to minimize the difference between estimated and true orientation. However, this can only be implemented within the laboratory setting by requiring the use of a concurrent gold-standard technology. To overcome this limitation, a Rigid-Constraint Method (RCM) was proposed to estimate suboptimal parameter values without relying on any orientation reference. The RCM method effectiveness was successfully tested on a single-parameter SFA, with an average error increase with respect to the optimal of 1.5 deg. In this work, the applicability of the RCM was evaluated on 10 popular SFAs with multiple parameters under different experimental scenarios. The average residual between the optimal and suboptimal errors amounted to 0.6 deg with a maximum of 3.7 deg. These encouraging results suggest the possibility to properly tune a generic SFA on different scenarios without using any reference. The synchronized dataset also including the optical data and the SFA codes are available online.

https://www.mdpi.com/1424-8220/21/18/6307/htm

tools-non-clinical-mobilise-d-29 Mobilise-D

 

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