Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and Recommendations

Smartphone-embedded inertia sensors are widely available nowadays. We have developed a smartphone application that could assess temporal gait characteristics using the built-in inertia measurement unit with the aim of enabling mass screening for gait abnormality. This study aimed to examine the test...

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Main Authors: Sam Guoshi Liang, Ho Yin Chung, Ka Wing Chu, Yuk Hong Gao, Fong Ying Lau, Wolfe Ixin Lai, Gabriel Ching-Hang Fong, Patrick Wai-Hang Kwong, Freddy Man Hin Lam
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Biosensors
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Online Access:https://www.mdpi.com/2079-6374/15/7/397
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author Sam Guoshi Liang
Ho Yin Chung
Ka Wing Chu
Yuk Hong Gao
Fong Ying Lau
Wolfe Ixin Lai
Gabriel Ching-Hang Fong
Patrick Wai-Hang Kwong
Freddy Man Hin Lam
author_facet Sam Guoshi Liang
Ho Yin Chung
Ka Wing Chu
Yuk Hong Gao
Fong Ying Lau
Wolfe Ixin Lai
Gabriel Ching-Hang Fong
Patrick Wai-Hang Kwong
Freddy Man Hin Lam
author_sort Sam Guoshi Liang
collection DOAJ
description Smartphone-embedded inertia sensors are widely available nowadays. We have developed a smartphone application that could assess temporal gait characteristics using the built-in inertia measurement unit with the aim of enabling mass screening for gait abnormality. This study aimed to examine the test–retest reliability and concurrent validity of the smartphone-based gait assessment in assessing temporal gait parameters in level-ground walking. Twenty-six healthy young adults (mean age: 20.8 ± 0.7) were recruited. Participants walked at their comfortable pace on a 10 m pathway repetitively in two walking sessions. Gait data were simultaneously collected by the smartphone application and a VICON system during the walk. Gait events of heel strike and toes off were detected from the sensors signal by a peak detection algorithm. Further gait parameters were calculated and compared between the two systems. Pearson Product–Moment Correlation was used to evaluate the concurrent validity of both systems. Test–retest reliability was examined by the intraclass correlation coefficients (ICCs) between measurements from two sessions scheduled one to four weeks apart. The validity of smartphone-based gait assessment was moderate to excellent for parameters involving only heel strike detection (r = 0.628–0.977), poor to moderate for parameters involving detection of both heel strike and toes off (r = 0.098–0.704), and poor for the proportion of gait phases within a gait cycle. Reliability was good to fair for heel strike-related parameters (ICC = 0.845–0.388), good to moderate for heel strike and toes-off-related parameters (ICC = 0.827–0.582), and moderate to fair for proportional parameters. Validity was adversely affected when toe off was involved in the calculation, when there was an insufficient number of effective steps taken, or when calculating sub-phases with short duration. The use of smartphone-based gait assessment is recommended in calculating step time and stride time, and we suggest collecting no less than 100 steps per leg during clinical application for better validity and reliability.
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publisher MDPI AG
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series Biosensors
spelling doaj-art-62daf6e402de40068d9b7900ee3be18e2025-08-20T03:58:31ZengMDPI AGBiosensors2079-63742025-06-0115739710.3390/bios15070397Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and RecommendationsSam Guoshi Liang0Ho Yin Chung1Ka Wing Chu2Yuk Hong Gao3Fong Ying Lau4Wolfe Ixin Lai5Gabriel Ching-Hang Fong6Patrick Wai-Hang Kwong7Freddy Man Hin Lam8Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong KongDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong KongDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong KongDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong KongDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong KongDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong KongDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong KongDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong KongDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong KongSmartphone-embedded inertia sensors are widely available nowadays. We have developed a smartphone application that could assess temporal gait characteristics using the built-in inertia measurement unit with the aim of enabling mass screening for gait abnormality. This study aimed to examine the test–retest reliability and concurrent validity of the smartphone-based gait assessment in assessing temporal gait parameters in level-ground walking. Twenty-six healthy young adults (mean age: 20.8 ± 0.7) were recruited. Participants walked at their comfortable pace on a 10 m pathway repetitively in two walking sessions. Gait data were simultaneously collected by the smartphone application and a VICON system during the walk. Gait events of heel strike and toes off were detected from the sensors signal by a peak detection algorithm. Further gait parameters were calculated and compared between the two systems. Pearson Product–Moment Correlation was used to evaluate the concurrent validity of both systems. Test–retest reliability was examined by the intraclass correlation coefficients (ICCs) between measurements from two sessions scheduled one to four weeks apart. The validity of smartphone-based gait assessment was moderate to excellent for parameters involving only heel strike detection (r = 0.628–0.977), poor to moderate for parameters involving detection of both heel strike and toes off (r = 0.098–0.704), and poor for the proportion of gait phases within a gait cycle. Reliability was good to fair for heel strike-related parameters (ICC = 0.845–0.388), good to moderate for heel strike and toes-off-related parameters (ICC = 0.827–0.582), and moderate to fair for proportional parameters. Validity was adversely affected when toe off was involved in the calculation, when there was an insufficient number of effective steps taken, or when calculating sub-phases with short duration. The use of smartphone-based gait assessment is recommended in calculating step time and stride time, and we suggest collecting no less than 100 steps per leg during clinical application for better validity and reliability.https://www.mdpi.com/2079-6374/15/7/397gaitsensoraccelerometerwearablesmartphonetemporal parameters
spellingShingle Sam Guoshi Liang
Ho Yin Chung
Ka Wing Chu
Yuk Hong Gao
Fong Ying Lau
Wolfe Ixin Lai
Gabriel Ching-Hang Fong
Patrick Wai-Hang Kwong
Freddy Man Hin Lam
Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and Recommendations
Biosensors
gait
sensor
accelerometer
wearable
smartphone
temporal parameters
title Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and Recommendations
title_full Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and Recommendations
title_fullStr Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and Recommendations
title_full_unstemmed Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and Recommendations
title_short Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and Recommendations
title_sort validity and reliability of a smartphone based gait assessment in measuring temporal gait parameters challenges and recommendations
topic gait
sensor
accelerometer
wearable
smartphone
temporal parameters
url https://www.mdpi.com/2079-6374/15/7/397
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