Consensus based framework for digital mobility monitoring

Abstract

Digital mobility assessment using wearable sensor systems has the potential to capture walking performance in a patient’s natural environment. It enables monitoring of health status and disease progression and evaluation of interventions in real-world situations. In contrast to laboratory settings, real-world walking occurs in non-conventional environments and under unconstrained and uncontrolled conditions. Despite the general understanding, there is a lack of agreed definitions about what constitutes real-world walking, impeding the comparison and interpretation of the acquired data across systems and studies. The goal of this study was to obtain expert-based consensus on specific aspects of real-world walking and to provide respective definitions in a common terminological framework. An adapted Delphi method was used to obtain agreed definitions related to real-world walking. In an online survey, 162 participants from a panel of academic, clinical and industrial experts with experience in the field of gait analysis were asked for agreement on previously specified definitions. Descriptive statistics was used to evaluate whether consent (> 75% agreement as defined a priori) was reached. Of 162 experts invited to participate, 51 completed all rounds (31.5% response rate). We obtained consensus on all definitions (“Walking” > 90%, “Purposeful” > 75%, “Real-world” > 90%, “Walking bout” > 80%, “Walking speed” > 75%, “Turning” > 90% agreement) after two rounds. The identification of a consented set of real-world walking definitions has important implications for the development of assessment and analysis protocols, as well as for the reporting and comparison of digital mobility outcomes across studies and systems. The definitions will serve as a common framework for implementing digital and mobile technologies for gait assessment and are an important link for the transition from supervised to unsupervised gait assessment.

Pedometers and Accelerometers in Multiple Sclerosis: Current and New Applications

“…Those results provided a proof-of-concept that free-living accelerometer data may be related to physical function, and recent evidence suggests that unsupervised assessments are necessary for acquiring real-world mobility data [ 48 , 51 ]. This is especially true, because gait characteristics from shorter walking bouts during daily living appear to be more informative about the disability level than longer bouts that are typically applied in laboratory-based tests [ 28 ].…”

An Algorithm for Accurate Marker-Based Gait Event Detection in Healthy and Pathological Populations During Complex Motor Tasks

“…The PI signals were used to isolate the different walking bouts [defined as comprising of at least two right and two left strides ( Kluge et al, 2021 )] and all reference GEs ( r GEs) were identified according to the methodology proposed and validated by Salis et al (2021) .…”

Design and validation of a multi-task, multi-phase protocol for real-world gait simulation

“…As part of an observational study (Mobilise-D [24]), a convenience sample of 108 participants were recruited from six cohort groups that included older healthy adults (HA) and participants with potentially altered mobility due to Parkinson's Disease (PD), Multiple Sclerosis (MS), Proximal Femoral Fracture (PFF), Chronic Obstructive Pulmonary Disease (COPD) or Congestive Heart Failure (CHF). Besides other inclusion and exclusion criteria [25], participants were able to walk four meters and had no comorbidities impacting mobility. Data were collected across ve gait laboratories after receiving written informed consent (Ethics approvals: The Newcastle upon Tyne Hospitals NHS Foundation Trust and She eld Teaching Hospitals NHS Foundation Trust: London -Bloomsbury Research Ethics committee, 19/LO/1507; Tel Aviv Sourasky Medical Center: the Helsinki Committee, 0551-19TLV; Robert Bosch Foundation for Medical Research: medical faculty of the University of Tübingen, 647/2019BO2; University of Kiel: medical faculty of Kiel University, D540/19).…”

“…Data were collected across ve gait laboratories after receiving written informed consent (Ethics approvals: The Newcastle upon Tyne Hospitals NHS Foundation Trust and She eld Teaching Hospitals NHS Foundation Trust: London -Bloomsbury Research Ethics committee, 19/LO/1507; Tel Aviv Sourasky Medical Center: the Helsinki Committee, 0551-19TLV; Robert Bosch Foundation for Medical Research: medical faculty of the University of Tübingen, 647/2019BO2; University of Kiel: medical faculty of Kiel University, D540/19). Participant demographics were collected, and patient characterisation was completed based on clinical assessments speci c to each cohort [25] (Table 1). Experimental Protocol…”