MoveLab®: Validation and Development of Novel Cross-Platform Gait and Mobility Assessments Using Gold Standard Motion Capture and Clinical Standard Assessment

Wearable health assessment devices enable real-time clinical- and home-based patient monitoring. Human gait analysis is a widely accepted musculoskeletal assessment. The 30 s Sit-to-Stand (STS) and Timed-Up-and-Go (TUG) are clinical frailty assessments used alongside gait analysis. This study assessed the reliability and validity of the MoveLab<sup>®</sup> (Agile Kinetic 2024) approach to measure gait spatiotemporal parameters (STPs), STS, and TUG using a waist-worn mobile phone, compared to the Gold Standard 3D marker-based motion capture (Qualisys AB, Sweden) and the Clinical Standard assessment of the STS and TUG test methods. Movement data, recorded simultaneously for 25 healthy volunteers (14 female and 11 male, Age = 31.8 ± 11.6 yrs) in a Biomechanics Laboratory using the Gold Standard system, the Clinical Standard assessments, and MoveLab<sup>®</sup>, was analyzed using Intraclass Correlation (ICC) and Bland-Altman plots (Python) to quantify the correlations, consistency, and significance across the output parameters. Comparing the methods, the STP consistency ranged from acceptable to good for all the tested parameters (ICC 0.299-0.894). The highest and lowest correlations were cycle time and terminal double support time, respectively. The TUG showed good agreement (ICC 0.757). Generally, an equal number of MoveLab<sup>®</sup> STS repetitions were observed. MoveLab<sup>®</sup> demonstrated validity and reliability for a range of key movement parameters using a pouch-worn mobile phone device in healthy adults in a controlled laboratory environment.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2025-09-12
DOI
https://doi.org/10.3390/s25185706
Primary Topic
Cerebral Palsy and Movement Disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MoveLab®: Validation and Development of Novel Cross-Platform Gait and Mobility Assessments Using Gold Standard Motion Capture and Clinical Standard Assessment

Colleen Farrell, Jenny Williams, Ζ. Glavcheva, Catherine Avril Holt et al.
Sensors
Cerebral Palsy and Movement Disorders
article

MoveLab®: Validation and Development of Novel Cross-Platform Gait and Mobility Assessments Using Gold Standard Motion Capture and Clinical Standard Assessment

Colleen Farrell, Jenny Williams, Ζ. Glavcheva, Catherine Avril Holt, Katie Powell, P. O. Bishop, Ahmad Amer, Finchley Harwood
article en

Abstract

Wearable health assessment devices enable real-time clinical- and home-based patient monitoring. Human gait analysis is a widely accepted musculoskeletal assessment. The 30 s Sit-to-Stand (STS) and Timed-Up-and-Go (TUG) are clinical frailty assessments used alongside gait analysis. This study assessed the reliability and validity of the MoveLab<sup>®</sup> (Agile Kinetic 2024) approach to measure gait spatiotemporal parameters (STPs), STS, and TUG using a waist-worn mobile phone, compared to the Gold Standard 3D marker-based motion capture (Qualisys AB, Sweden) and the Clinical Standard assessment of the STS and TUG test methods. Movement data, recorded simultaneously for 25 healthy volunteers (14 female and 11 male, Age = 31.8 ± 11.6 yrs) in a Biomechanics Laboratory using the Gold Standard system, the Clinical Standard assessments, and MoveLab<sup>®</sup>, was analyzed using Intraclass Correlation (ICC) and Bland-Altman plots (Python) to quantify the correlations, consistency, and significance across the output parameters. Comparing the methods, the STP consistency ranged from acceptable to good for all the tested parameters (ICC 0.299-0.894). The highest and lowest correlations were cycle time and terminal double support time, respectively. The TUG showed good agreement (ICC 0.757). Generally, an equal number of MoveLab<sup>®</sup> STS repetitions were observed. MoveLab<sup>®</sup> demonstrated validity and reliability for a range of key movement parameters using a pouch-worn mobile phone device in healthy adults in a controlled laboratory environment.

SensorsVol. 25(18)
Agilent Technologies (United Kingdom) (GB), Cardiff University (GB)
Openalex Percentile: Top 71%
Cerebral Palsy and Movement Disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.