Assessment of Gait Symmetry and Gait Normality Using Inertial Sensors: In-Lab and In-Situ Evaluation

Sant'Anna, Anita Pinheiro; Wickström, Nicholas; Eklund, Helene; Zügner, Roland; Tranberg, Roy

doi:10.1007/978-3-642-38256-7_16

Cited by 14 publications

(6 citation statements)

References 33 publications

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“…Additionally, force sensors, extensometers, goniometers, active markers, and electromyography are utilized to capture the signals that characterize the gait [17]. Sant'Anna et al [18] developed a system with inertial sensors to quantify gait symmetry and gait normality. The evaluation was performed in the laboratory, as opposed to the 3D kinematic measurements, and in situ, contrary to the clinical assessments of patients undergoing hip replacement.…”

Section: Discussionmentioning

confidence: 99%

Determining the Most Appropriate Assistive Walking Device Using the Inertial Measurement Unit-Based Gait Analysis System in Disabled Patients

et al. 2020

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Objective To evaluate the gait pattern of patients with gait disturbances without consideration of defilades due to assistive devices. This study focuses on gait analysis using the inertial measurement unit (IMU) system, which can also be used to determine the most appropriate assistive device for patients with gait disturbances.Methods Records of 18 disabled patients who visited the Department of Rehabilitation from May 2018 to June 2018 were selected. Patients’ gait patterns were analyzed using the IMU system with different assistive devices to determine the most appropriate device depending on the patient’s condition. Evaluation was performed using two or more devices, and the appropriate device was selected by comparing the 14 parameters of gait evaluation. The device showing measurements nearer or the nearest to the normative value was selected for rehabilitation.Results The result of the gait evaluation in all 18 patients was analyzed using the IMU system. According to the records, the patients were evaluated using various assistive devices without consideration of defilades. Moreover, this gait analysis was effective in determining the most appropriate device for each patient. Increased gait cycle time and swing phase and decreased stance phase were observed in devices requiring significant assistance.Conclusion The IMU-based gait analysis system is beneficial in evaluating gait in clinical fields. Specifically, it is useful in evaluating patients with gait disturbances who require assistive devices. Furthermore, it allows the establishment of an evidence-based decision for the most appropriate assistive walking devices for patients with gait disturbances.

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Section: Discussionmentioning

confidence: 99%

Determining the Most Appropriate Assistive Walking Device Using the Inertial Measurement Unit-Based Gait Analysis System in Disabled Patients

et al. 2020

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“…It is based on inertial/magnetic sensor modules in which micro electro-mechanical systems (MEMS) sensors are used, which make it possible to track orientation in real time [49]. Sant'Anna et al (2013) developed a system with inertial sensors to quantify gait symmetry and gait normality with subject's velocity, acceleration, orientation, and gravitational forces [58].…”

Section: Inertial Sensorsmentioning

confidence: 99%

Biomechanics of running: An overview on gait cycle

Kapri

Mehta

Kiran

2021

Int. J. Phys. Educ. Fit. Sports

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This review article summarized the literature regarding running gait. It describes characteristics of running gait and running gait cycle, explains running anatomy in relation to lower and upper body mechanism; contribution of muscles, and joint running gait cycle. The concept of running kinematics and kinetics has described motion characteristics such as position, velocity, acceleration, and force applied during the running cycle. Running gait analysis techniques has discussed such as motion analysis, force plate analysis, and electromyography.

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“…These parameters can be extracted from the time or frequency domain [42]. Commonly used time domain gait features include local extrema [43,44], adaptive thresholds (or zero) crossings [23,45,46], and gait symmetry indexes [47]. Common frequency domain features include FFT (Fast Fourier Transformation) coefficients [42,48] and wavelet transforms [49].…”

Section: Estimation Of Gait Patternsmentioning

confidence: 99%

An Overview of Smart Shoes in the Internet of Health Things: Gait and Mobility Assessment in Health Promotion and Disease Monitoring

et al. 2017

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New smart technologies and the internet of things increasingly play a key role in healthcare and wellness, contributing to the development of novel healthcare concepts. These technologies enable a comprehensive view of an individual's movement and mobility, potentially supporting healthy living as well as complementing medical diagnostics and the monitoring of therapeutic outcomes. This overview article specifically addresses smart shoes, which are becoming one such smart technology within the future internet of health things, since the ability to walk defines large aspects of quality of life in a wide range of health and disease conditions. Smart shoes offer the possibility to support prevention, diagnostic work-up, therapeutic decisions, and individual disease monitoring with a continuous assessment of gait and mobility. This overview article provides the technological as well as medical aspects of smart shoes within this rising area of digital health applications, and is designed especially for the novel reader in this specific field. It also stresses the need for closer interdisciplinary interactions between technological and medical experts to bridge the gap between research and practice. Smart shoes can be envisioned to serve as pervasive wearable computing systems that enable innovative solutions and services for the promotion of healthy living and the transformation of health care.

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Assessment of Gait Symmetry and Gait Normality Using Inertial Sensors: In-Lab and In-Situ Evaluation

Cited by 14 publications

References 33 publications

Determining the Most Appropriate Assistive Walking Device Using the Inertial Measurement Unit-Based Gait Analysis System in Disabled Patients

Determining the Most Appropriate Assistive Walking Device Using the Inertial Measurement Unit-Based Gait Analysis System in Disabled Patients

Biomechanics of running: An overview on gait cycle

An Overview of Smart Shoes in the Internet of Health Things: Gait and Mobility Assessment in Health Promotion and Disease Monitoring

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