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Accurately assessing people’s gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors). The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (SDA, including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-hours of real-world unsupervised activity. Excellent absolute agreement (ICC > 0.95) and very limited mean absolute errors were observed for all cohorts and DMOs (cadence ≤ 0.61 steps/min, stride length ≤ 0.02 m, walking speed ≤ 0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the SDA (cadence 2.72–4.87 steps/min, stride length 0.04–0.06 m, walking speed 0.03–0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-hours acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.

Background: Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim of this study is to propose and validate a multi-task and multi-phase protocol for simulating real-world gait accounting for all these factors within a single set of observations carried out within a limited laboratory space, while ensuring minimisation of participant burden and safety.Methods: The protocol included eight motor tasks at varying speed, incline/steps, surface, path shape, cognitive demand, and included postures that may abruptly alter the participants’ strategy of walking. It was deployed in a convenience sample of 108 participants 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). A novelty introduced in the protocol was the tiered approach to increase difficulty both within the same task (e.g., by allowing use of aids or armrests) and across tasks.Results: The protocol proved to be safe and feasible and the addition of the more complex tasks allowed a much greater spread in walking speeds to be achieved compared to standard straight walking trials. Furthermore, it allowed a relatively realistic representation of daily life relevant mobility aspects and can therefore be used for the validation of monitoring devices used in real life.Conclusions: The suitability of the protocol for measuring gait in a variety of pathological conditions suggests that it can also be used to detect changes in gait due to, for example, the onset or progression of a disease, or due to therapy.Trial registration: ISRCTN – 12246987.