SANE (eaSy gAit aNalysis systEm): real-time dual-depth, marker-less system characterisation and robustness of gait parameters

Cafolla, Daniele; Marcela, Betsy Dayana

doi:10.3389/frobt.2026.1691113

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SANE (eaSy gAit aNalysis systEm): real-time dual-depth, marker-less system characterisation and robustness of gait parameters

Daniele Cafolla

, Betsy Dayana Marcela Chaparro Rico

Frontiers in Robotics and AI, Volume: 13, Start page: 1691113

Swansea University Authors: Daniele Cafolla , Betsy Dayana Marcela Chaparro Rico

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DOI (Published version): 10.3389/frobt.2026.1691113

Abstract

Gait analysis is essential in clinical evaluation, biomechanics, and rehabilitation, yet conventional approaches often rely on complex marker-based systems that limit accessibility and real-time feedback. The SANE (eaSy gAit aNalysis systEm) platform was launched in 2020 and has previously been eval...

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Published in:	Frontiers in Robotics and AI
ISSN:	2296-9144
Published:	Frontiers Media SA 2026
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa72160

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last_indexed	2026-06-25T06:26:49Z
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A total of 80 walking trials performed by a healthy adult (39 years, 1.74 m, 73.0 kg) were acquired across four sessions over 1 week, with complete system shutdown and restart between sessions to rigorously challenge operational stability. Session-level means, within-session standard deviations, and Relative Error Measurement (REM%) between sessions were used to quantify robustness and session-to-session variability. Across all four sessions, gait outputs remained within published normative ranges for healthy adults. REM% values for primary spatiotemporal parameters were consistently below or around 5%, and standard deviations were low and comparable to values reported for marker-based systems, indicating stable, repeatable measurements over repeated restarts and days. Real-time computation and visualisation at frame rates up to approximately 80 frames per second further distinguish this system from traditional post hoc workflows. 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spelling	2026-06-24T14:58:39.5002619 v2 72160 2026-06-24 SANE (eaSy gAit aNalysis systEm): real-time dual-depth, marker-less system characterisation and robustness of gait parameters ac4feae4da44720e216ab2e0359e4ddb 0000-0002-5602-1519 Daniele Cafolla Daniele Cafolla true false fab062f51ecae36a295bd5c53e03fef5 0000-0002-6874-2508 Betsy Dayana Marcela Chaparro Rico Betsy Dayana Marcela Chaparro Rico true false 2026-06-24 MACS Gait analysis is essential in clinical evaluation, biomechanics, and rehabilitation, yet conventional approaches often rely on complex marker-based systems that limit accessibility and real-time feedback. The SANE (eaSy gAit aNalysis systEm) platform was launched in 2020 and has previously been evaluated in multi-subject laboratory and clinical studies, where it demonstrated agreement with gold-standard marker-based systems for core spatiotemporal parameters and achieved high test–retest, inter-rater, and intra-rater reliability. Building on this validated foundation, the present work provides a system characterisation and robustness analysis of the latest dual-depth, real-time SANE implementation. The updated SANE system enables real-time extraction and visualisation of an expanded set of spatiotemporal and angular gait parameters—including gait speed, step and stride length, cadence, step and stride time, step width, foot angles, double support, and gait phase durations—using two depth cameras and AI-based pose estimation. A total of 80 walking trials performed by a healthy adult (39 years, 1.74 m, 73.0 kg) were acquired across four sessions over 1 week, with complete system shutdown and restart between sessions to rigorously challenge operational stability. Session-level means, within-session standard deviations, and Relative Error Measurement (REM%) between sessions were used to quantify robustness and session-to-session variability. Across all four sessions, gait outputs remained within published normative ranges for healthy adults. REM% values for primary spatiotemporal parameters were consistently below or around 5%, and standard deviations were low and comparable to values reported for marker-based systems, indicating stable, repeatable measurements over repeated restarts and days. Real-time computation and visualisation at frame rates up to approximately 80 frames per second further distinguish this system from traditional post hoc workflows. These findings characterise the operational robustness and real-time capabilities of the dual-depth SANE system in a controlled, single-participant setting and support its use as a practical, marker-less gait assessment tool in clinical and research environments, while motivating future studies on larger and pathological cohorts. Journal Article Frontiers in Robotics and AI 13 1691113 Frontiers Media SA 2296-9144 biomechanics, dual-depth, gait analysis, marker-less systems, movement analysis 15 5 2026 2026-05-15 10.3389/frobt.2026.1691113 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University Other 2026-06-24T14:58:39.5002619 2026-06-24T14:53:53.5665875 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Daniele Cafolla 0000-0002-5602-1519 1 Betsy Dayana Marcela Chaparro Rico 0000-0002-6874-2508 2 72160__37045__793828d8d2794a868be15b227d4e1f7a.pdf 72160.VOR.pdf 2026-06-24T14:56:41.2751369 Output 3123371 application/pdf Version of Record true © 2026 Cafolla and Chaparro-Rico. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). true eng https://creativecommons.org/licenses/by/4.0/
title	SANE (eaSy gAit aNalysis systEm): real-time dual-depth, marker-less system characterisation and robustness of gait parameters
spellingShingle	SANE (eaSy gAit aNalysis systEm): real-time dual-depth, marker-less system characterisation and robustness of gait parameters Daniele Cafolla Betsy Dayana Marcela Chaparro Rico
title_short	SANE (eaSy gAit aNalysis systEm): real-time dual-depth, marker-less system characterisation and robustness of gait parameters
title_full	SANE (eaSy gAit aNalysis systEm): real-time dual-depth, marker-less system characterisation and robustness of gait parameters
title_fullStr	SANE (eaSy gAit aNalysis systEm): real-time dual-depth, marker-less system characterisation and robustness of gait parameters
title_full_unstemmed	SANE (eaSy gAit aNalysis systEm): real-time dual-depth, marker-less system characterisation and robustness of gait parameters
title_sort	SANE (eaSy gAit aNalysis systEm): real-time dual-depth, marker-less system characterisation and robustness of gait parameters
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author	Daniele Cafolla Betsy Dayana Marcela Chaparro Rico
author2	Daniele Cafolla Betsy Dayana Marcela Chaparro Rico
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description	Gait analysis is essential in clinical evaluation, biomechanics, and rehabilitation, yet conventional approaches often rely on complex marker-based systems that limit accessibility and real-time feedback. The SANE (eaSy gAit aNalysis systEm) platform was launched in 2020 and has previously been evaluated in multi-subject laboratory and clinical studies, where it demonstrated agreement with gold-standard marker-based systems for core spatiotemporal parameters and achieved high test–retest, inter-rater, and intra-rater reliability. Building on this validated foundation, the present work provides a system characterisation and robustness analysis of the latest dual-depth, real-time SANE implementation. The updated SANE system enables real-time extraction and visualisation of an expanded set of spatiotemporal and angular gait parameters—including gait speed, step and stride length, cadence, step and stride time, step width, foot angles, double support, and gait phase durations—using two depth cameras and AI-based pose estimation. A total of 80 walking trials performed by a healthy adult (39 years, 1.74 m, 73.0 kg) were acquired across four sessions over 1 week, with complete system shutdown and restart between sessions to rigorously challenge operational stability. Session-level means, within-session standard deviations, and Relative Error Measurement (REM%) between sessions were used to quantify robustness and session-to-session variability. Across all four sessions, gait outputs remained within published normative ranges for healthy adults. REM% values for primary spatiotemporal parameters were consistently below or around 5%, and standard deviations were low and comparable to values reported for marker-based systems, indicating stable, repeatable measurements over repeated restarts and days. Real-time computation and visualisation at frame rates up to approximately 80 frames per second further distinguish this system from traditional post hoc workflows. These findings characterise the operational robustness and real-time capabilities of the dual-depth SANE system in a controlled, single-participant setting and support its use as a practical, marker-less gait assessment tool in clinical and research environments, while motivating future studies on larger and pathological cohorts.
published_date	2026-05-15T07:26:49Z
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SANE (eaSy gAit aNalysis systEm): real-time dual-depth, marker-less system characterisation and robustness of gait parameters

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