Reliability and Validity of a Wearable Inertial Sensor System for Gait Assessment in Healthy Young Adults

Hou, Ying; Wang, Shujia; Li, Jinping; Komal, Sana; Li, Ké

doi:10.1109/cisp-bmei53629.2021.9624463

Cited by 8 publications

(7 citation statements)

References 14 publications

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“…Given this information, the primary aim of this study was to determine the test–retest reliability of DT walking gait parameters using in‐shoe inertial sensors in nonconcussed individuals. It was hypothesized that gait speed and stride length would show acceptable test–retest reliability, based on findings from similar investigations 25,32 . The secondary aim of this research was to determine if gait parameters are different across the 12 m, 30 m, and 1 min out and back testing conditions.…”

Section: Introductionmentioning

confidence: 99%

“…The appeal of this technology is testing is not limited to a laboratory environment, which may improve the likelihood of natural gait being performed by patients if testing is performed with more familiar surroundings and thus allow for more accurate observations to be made by practitioners 21,22 . Inertial sensors have shown to be a reliable tool for identifying spatiotemporal gait parameters, 23 while also being reliable and valid in comparison to 3D MOCAP 24,25 . The environmental restrictions that arise from 3D MOCAP's limited field of capture are not as significant with inertial sensors given its portability.…”

Section: Introductionmentioning

confidence: 99%

“… 21 , 22 Inertial sensors have shown to be a reliable tool for identifying spatiotemporal gait parameters, 23 while also being reliable and valid in comparison to 3D MOCAP. 24 , 25 The environmental restrictions that arise from 3D MOCAP's limited field of capture are not as significant with inertial sensors given its portability. Assessing gait over a longer distance than the 8–10 m typically used for laboratory gait testing with fewer turns could provide a more accurate representation of an individual's natural gait due to minimizing the variability of gait parameters (i.e., influence of accelerations and decelerations).…”

Section: Introductionmentioning

confidence: 99%

“…It was hypothesized that gait speed and stride length would show acceptable test–retest reliability, based on findings from similar investigations. 25 , 32 The secondary aim of this research was to determine if gait parameters are different across the 12 m, 30 m, and 1 min out and back testing conditions. It was hypothesized that the greater straight‐line distances associated with the 1 min out and back protocol would be less variable than both the 12 and 30 m protocols, given that fewer turns would reduce the variability of data across the gait parameters of interest.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The variability of dual‐task walking parameters using in‐shoe inertial sensors in nonconcussed individuals: A randomized within‐subject repeated measures design

Mitchell,

Cronin

2023

Health Science Reports

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Background and AimsThere is a need for high utility and portability, and cost‐effective technologies that are suitable for assessing dual‐task gait after experiencing a concussion. Current technologies utilized such as 3D motion capture and force plates are too complex and expensive for most practitioners. The aim of this study was to quantify the variability of dual‐task walking gait parameters using in‐shoe inertial sensors in nonconcussed individuals.MethodsThis was a randomized within‐subject repeated measures design conducted within a sports laboratory. Twenty healthy, uninjured, nonconcussed participants were recruited for this study. Gait variables of interest were measured across three 2‐min continuous walking protocols (12 m, 30 m, 1 min out and back) while performing a cognitive task of counting backward in sevens from a randomly generated number between 300 and 500. Testing was completed over three occasions separated by 7 days, for a total of nine walking trials. Participants completed the testing protocols in a randomized, individual order. The primary outcome was to determine the variability of dual‐task walking gait parameters using in‐shoe inertial sensors in nonconcussed individuals across three protocols.ResultsThree to four participants were allocated to each randomized protocol order. Regarding the absolute consistency (coefficient of variation [CV]) between testing occasions, no gait measure was found to have variability above 6.5%. Relative consistency (intraclass correlation coefficient [ICC]) was acceptable (>0.70) in 95% of the variables of interest, with only three variables < 0.70. Similar variability was found across the three testing protocols.ConclusionIn‐shoe inertial sensors provide a viable option for monitoring gait parameters. This technology is also reliable across different testing distances, thus offering various testing options for practitioners. Further research needs to be conducted to examine the variability with concussed subjects.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The variability of dual‐task walking parameters using in‐shoe inertial sensors in nonconcussed individuals: A randomized within‐subject repeated measures design

Mitchell,

Cronin

2023

Health Science Reports

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“…The present study aimed to identify the key features of normal human gait using inertial unit (IMU) recordings in a walking test. Although there are many studies where inertial units are used to analyse normal human gait, each employs different features or markers to assess gait performance [25][26][27][28][29][30][31][32][33][34][35][36]. The current literature lacks concise studies that specify which key features may be used to optimally distinguish the most relevant events in human gait.…”

Section: Introductionmentioning

confidence: 99%

Kinematic Analysis of Human Gait in Healthy Young Adults Using IMU Sensors: Exploring Relevant Machine Learning Features for Clinical Applications

Marimon,

Mengual,

López-de-Celis

et al. 2024

Bioengineering

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Background: Gait is the manner or style of walking, involving motor control and coordination to adapt to the surrounding environment. Knowing the kinesthetic markers of normal gait is essential for the diagnosis of certain pathologies or the generation of intelligent ortho-prostheses for the treatment or prevention of gait disorders. The aim of the present study was to identify the key features of normal human gait using inertial unit (IMU) recordings in a walking test. Methods: Gait analysis was conducted on 32 healthy participants (age range 19–29 years) at speeds of 2 km/h and 4 km/h using a treadmill. Dynamic data were obtained using a microcontroller (Arduino Nano 33 BLE Sense Rev2) with IMU sensors (BMI270). The collected data were processed and analyzed using a custom script (MATLAB 2022b), including the labeling of the four relevant gait phases and events (Stance, Toe-Off, Swing, and Heel Strike), computation of statistical features (64 features), and application of machine learning techniques for classification (8 classifiers). Results: Spider plot analysis revealed significant differences in the four events created by the most relevant statistical features. Among the different classifiers tested, the Support Vector Machine (SVM) model using a Cubic kernel achieved an accuracy rate of 92.4% when differentiating between gait events using the computed statistical features. Conclusions: This study identifies the optimal features of acceleration and gyroscope data during normal gait. The findings suggest potential applications for injury prevention and performance optimization in individuals engaged in activities involving normal gait. The creation of spider plots is proposed to obtain a personalised fingerprint of each patient’s gait fingerprint that could be used as a diagnostic tool. A deviation from a normal gait pattern can be used to identify human gait disorders. Moving forward, this information has potential for use in clinical applications in the diagnosis of gait-related disorders and developing novel orthoses and prosthetics to prevent falls and ankle sprains.

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Examining the validity of smart glasses in measuring spatiotemporal parameters of gait among people with Parkinson’s disease

Fang,

Pahwa,

Lyons

et al. 2024

Gait & Posture

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Reliability and Validity of a Wearable Inertial Sensor System for Gait Assessment in Healthy Young Adults

Cited by 8 publications

References 14 publications

The variability of dual‐task walking parameters using in‐shoe inertial sensors in nonconcussed individuals: A randomized within‐subject repeated measures design

The variability of dual‐task walking parameters using in‐shoe inertial sensors in nonconcussed individuals: A randomized within‐subject repeated measures design

Kinematic Analysis of Human Gait in Healthy Young Adults Using IMU Sensors: Exploring Relevant Machine Learning Features for Clinical Applications

Examining the validity of smart glasses in measuring spatiotemporal parameters of gait among people with Parkinson’s disease

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