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Review Data
Scoping review to identify existing studies in four medical conditions (Parkinson’s Disease, Multiple Sclerosis, Chronic Obstructive Pulmonary Disease, Hip Fracture), organize the results of those studies, and compare results between conditions and DMOs to suggest future research priorities. We screened over 20,000 articles to identify 855 publications that met our eligibility criteria.
Available Review Data
Data from systematic review on clinical utility of digital mobility outcomes.
Interview Data
- Semi-structured interviews with 20 professionals with academic, industry or clinical
backgrounds, experienced in using wearable devices in research. - Semi-structured interviews with 30 participants in the Technical Validation Study.
Young Adult Reference (YAR) Data
Experimental data collected on 20 healthy subjects during both in-lab and real-world sessions. In the“In-lab” session, data are recorded during a large variety of different motor activities and walking conditions using: 1) A single inertial measurement unit attached at the pelvis level; 2) An optoelectronic stereo-photogrammetric system (for ground truth data); and 3) the INDIP system (multi-sensor network to establish real-world ground truth data). The “Out-of-Lab” session includes both indoor and outdoor conditions for a total duration of 2.5 hours using the single inertial unit and the INDIP system.
Available YAR Data
The Mobilise-D procedure for data standardization.
Technical Validation Study (TVS) Data
Retrospective analysis of legacy digital mobility datasets for algorithm testing and validation, and a cross-sectional study with 115 participants (Chronic Obstructive Pulmonary Disease, Multiple Sclerosis, Parkinson’s Disease, Hip Fracture recovery, Congestive Heart Failure, and healthy adults) to assess performance of various algorithms under different experimental scenarios, including both in- and out-of–lab recordings. Data collection is currently ongoing.
Available TVS Data
GUI and example data for ensuring comparability of stereophotogrammetric data.
Marker-based algorithm and example data for gait event detection.
Questionnaire used to guide the ranking methodology adopted within Mobilise-D.
Questionnaire with the initially proposed definitions of terms related to real-world walking assessed in round one.
A multi-sensor wearable system for the assessment of diseased gait in real-world conditions
Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium
Clinical Validation Study (CVS) Data
Clinical Validation Study (CVS): Prospective, 2-year follow-up of up to 2400 patients from 4 cohorts (Chronic Obstructive Pulmonary Disease, Multiple Sclerosis, Parkinson’s Disease, Hip Fracture recovery) over 5 time points at 16 clinical sites across Europe. Data includes comprehensive baseline assessment, clinical measurements, and daily-life activity monitoring. Data collection is ongoing.