Proposed Mobility Assessments with Simultaneous Full-Body Inertial Measurement Units and Optical Motion Capture in Healthy Adults and Neurological Patients for Future Validation Studies: Study Protocol

Abstract

Healthy adults and neurological patients show unique mobility patterns over the course of their lifespan and disease. Quantifying these mobility patterns could support diagnosing, tracking disease progression and measuring response to treatment. This quantification can be done with wearable technology, such as inertial measurement units (IMUs). Before IMUs can be used to quantify mobility, algorithms need to be developed and validated with age and disease-specific datasets. This study proposes a protocol for a dataset that can be used to develop and validate IMU-based mobility algorithms for healthy adults (18–60 years), healthy older adults (>60 years), and patients with Parkinson’s disease, multiple sclerosis, a symptomatic stroke and chronic low back pain. All participants will be measured simultaneously with IMUs and a 3D optical motion capture system while performing standardized mobility tasks and non-standardized activities of daily living. Specific clinical scales and questionnaires will be collected. This study aims at building the largest dataset for the development and validation of IMU-based mobility algorithms for healthy adults and neurological patients. It is anticipated to provide this dataset for further research use and collaboration, with the ultimate goal to bring IMU-based mobility algorithms as quickly as possible into clinical trials and clinical routine.

A Deep Learning Approach for Gait Event Detection from a Single Shank-Worn IMU: Validation in Healthy and Neurological Cohorts

“…Gait analyses were performed in the Universitätsklinikum Schleswig-Holstein (UKSH) campus Kiel, Germany. The study [ 54 ] was approved by the ethical committee of the medical faculty at the UKSH (no: D438/18). In total, data from 157 participants were included for the current analysis, including data from young adults (YA; age: 18–60 years), older adults (OA; age: >60 years), people with Parkinson’s Disease (PD; according to the UK Brain Bank criteria [ 55 ]), people with a recent (<4 weeks) symptomatic stroke (stroke), people with multiple sclerosis (MS; according to the McDonalds criteria [ 56 ]), people with chronic low back pain (cLBP), and people with diagnoses not fitting in any aforementioned groups or disorders with no explicit diagnosis (other) ( Table 1 ).…”

“…Marker data were recorded using a twelve-camera OMC system (Qualisys AB, Göteborg, Sweden) at a sampling frequency of 200 Hz. IMU data were recorded at the same sampling frequency, and both systems were synchronized using a TTL signal [ 54 ].…”

Postural Sway in Parkinson's Disease and Multiple Sclerosis Patients During Tasks With Different Complexity

“…The MS patients were additionally evaluated with the Expanded Disability Status Scale (EDSS). The full study protocol can be found elsewhere ( 36 ).…”

Parkinson’s disease multimodal complex treatment improves gait performance: an exploratory wearable digital device-supported study

“…Normal distribution was tested with the Shapiro–Wilk test and Q–Q-Plots. Parameters “Step count” and “Stride length” were normalized for a velocity of 1 m/s for all participants as these parameters have repeatedly been shown to correlate significantly with gait velocity [ 66 ]. For the checking boxes walking task, both original and corrected step count and stride length were included in the analyses.…”