Wearable Inertial Sensors to Assess Gait during the 6-Minute Walk Test: A Systematic Review

Storm, Fabio; Cesareo, Ambra; Reni, Gianluigi; Biffi, Emilia

doi:10.3390/s20092660

Cited by 62 publications

(51 citation statements)

References 90 publications

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“…However, a wide variety of such methods and tools have been developed for the measurement of human movement in a cheap, fast and as efficient way as possible. Wearable sensor systems can perform gait analysis by providing spatiotemporal parameters useful for investigating the progression of gait problems in patients with various neurological problems such as diabetic neuropathy, without the need for a specialized laboratory for motion analysis, and measurements can be performed even in the domestic context of the patients [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Wearable Sensor for Assessing Gait and Postural Alterations in Patients with Diabetes: A Scoping Review

et al. 2021

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Background and Objectives: Diabetes mellitus is considered a serious public health problem due to its high prevalence and related complications, including gait and posture impairments due to neuropathy and vascular alterations and the subsequent increased risk of falls. The gait of patients with diabetes is characterized by alterations of the main spatiotemporal gait parameters such as gait velocity, cadence, stride time and length, which are also known to worsen with disease course. Wearable sensor systems can be used for gait analysis by providing spatiotemporal parameters and postural control (evaluated from the perspective of body sway), useful for investigating the disease progression. Thanks to their small size and low cost of their components, inertial measurement units (IMUs) are easy to wear and are cheap tools for movement analysis. Materials and Methods: The aim of this study is to review articles published in the last 21 years (from 2000 to 2021) concerning the application of wearable sensors to assess spatiotemporal parameters of gait and body postural alterations in patients with diabetes mellitus. Relevant articles were searched in the Medline database using PubMed, Ovid and Cochrane libraries. Results: One hundred and four articles were initially identified while searching the scientific literature on this topic. Thirteen were selected and analysed in this review. Wearable motion sensors are useful, noninvasive, low-cost, and objective tools for performing gait and posture analysis in diabetic patients. The IMUs can be worn at the lumber levels, tibias or feet, and different spatiotemporal parameters of movement and static posture can be assessed. Conclusions: Future research should focus on standardizing the measurement setup and selecting the most informative spatiotemporal parameters for gait and posture analysis.

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Section: Introductionmentioning

confidence: 99%

Wearable Sensor for Assessing Gait and Postural Alterations in Patients with Diabetes: A Scoping Review

et al. 2021

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“…The 6-minute walk test (6MWT), for instance, being a popular clinical tool that evaluates a variety of physiological functionalities, is generally limited to the standardized outcome of 6MWT distance. Gait patterns and other kinematic parameters are frequently not considered in the test [55]. As such, it would be practicable to conduct gait evaluation such as the 6MWT that measures body segment orientation or joint angles using the NARX which does not require dedicated space while providing comprehensive data to analyze specific functional status in the clinical environment.…”

Section: Discussionmentioning

confidence: 99%

Biomechanical Ambulatory Assessment of 3D Knee Angle Using Novel Inertial Sensor-Based Technique

et al. 2021

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Three-dimensional (3D) knee angle measurement is one of the key measures in human gait analysis. Inertial sensor capable of measuring joint motion under unconstrained conditions is a practical tool for clinical evaluation and rehabilitation. An inertial measurement unit (IMU) consisting of accelerometer and gyroscope allows orientation measurement in 3D with an additional sensor (i.e., magnetometer). However, ferromagnetic interference negatively affects the performance of magnetometer and thus reduces measurement accuracy. In this study, a technique based on nonlinear autoregressive neural network with exogenous inputs (NARX) is presented to measure 3D segmental orientation during gait without the use of magnetometer. With IMUs attached to the thigh and shank, 3D knee angles in long-distance treadmill walking were computed and validated against an optical motion analysis system as the gold standard. Pseudo-integrator (PI) was also compared to the reference system for benchmarking. The learning capability of NARX was further assessed with the comparison of complementary filter (CF) to the reference system. The proposed NARX model was shown to outperform PI with biases between-3.5°and-0.2°, and root mean square errors between 4.5°and 2.5°. Results demonstrated the capability of NARX in providing accurate estimates of 3D knee joint angle while avoiding interference as encountered in systems incorporating magnetometer, suggesting that NARX is feasible to computing long-term ambulatory measurements of body segment orientation and 3D joint angles. INDEX TERMS 3D knee angle, gait analysis, NARX network, pseudo-integration, segmental orientation.

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“…First, there are two review papers concerning sensor-to-segment calibration [2] and the use of inertial sensors for 6-min walk test quantification [3].…”

Section: Contributionsmentioning

confidence: 99%

“…The second systematic review [3] focuses on the use of inertial sensors to monitor the 6-min walk test (6MWT). This exercise is one of the clinical tests to quantify the general health status of a subject.…”

Section: Contributionsmentioning

confidence: 99%

Human and Animal Motion Tracking Using Inertial Sensors

Marin

2020

Sensors

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Motion is key to health and wellbeing, something we are particularly aware of in times of lockdowns and restrictions on movement. Considering the motion of humans and animals as a biomarker of the performance of the neuro-musculoskeletal system, its analysis covers a large array of research fields, such as sports, equine science and clinical applications, but also innovative methods and workplace analysis. In this Special Issue of Sensors, we focused on human and animal motion-tracking using inertial sensors. Ten research and two review papers, mainly on human movement, but also on the locomotion of the horse, were selected. The selection of articles in this Special Issue aims to display current innovative approaches exploring hardware and software solutions deriving from inertial sensors related to motion capture and analysis. The selected sample shows that the versatility and pervasiveness of inertial sensors has great potential for the years to come, as, for now, limitations and room for improvement still remain.

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Wearable Inertial Sensors to Assess Gait during the 6-Minute Walk Test: A Systematic Review

Cited by 62 publications

References 90 publications

Wearable Sensor for Assessing Gait and Postural Alterations in Patients with Diabetes: A Scoping Review

Wearable Sensor for Assessing Gait and Postural Alterations in Patients with Diabetes: A Scoping Review

Biomechanical Ambulatory Assessment of 3D Knee Angle Using Novel Inertial Sensor-Based Technique

Human and Animal Motion Tracking Using Inertial Sensors

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