Adaptive step length estimation algorithm using optimal parameters and movement status awareness

Shin, S. H.; Park, Chan Gook

doi:10.1016/j.medengphy.2011.04.009

Cited by 85 publications

(99 citation statements)

References 19 publications

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“…For this reason, here, a structured set of thresholds for reliability assessment is proposed, starting from the general accepted value of 5% [16,[27][28][29][30]. A gradual scale of reliability evaluation based on quantitative criteria for each spatiotemporal parameter and step number is used as acceptability criteria to evaluate the results (Table 11).…”

Section: Discussionmentioning

confidence: 99%

Method for Wearable Kinematic Gait Analysis Using a Harmonic Oscillator Applied to the Center of Mass

2018

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A model based on a harmonic oscillator describing human walking and balance with the sinusoidal trajectory of the center of mass of a subject during gait is presented. This model allows overcoming the traditional drift due to the double integration of raw acceleration data. The protocol uses a single 3D accelerometer worn at the pelvis level. The system computes the spatiotemporal gait and balance parameters when the subject is walking with or without aids. An incremental methodological approach is proposed and followed in the implementation and accuracy assessment. Eleven healthy subjects have participated to the study performing 6 trials over a fixed linear walking path at a self-selected speed. For reference, the protocol has imposed the execution of 52 steps whose length has been fixed at 60 cm. Different processing methods have been implemented and tested. The model identifies steps, walking time, and stepping frequency with an excellent reliability (absolute percentage accuracy error < 5%). When the information about the expected step length is given to the model, the percentage error in the measure of walking distance and speed is 3.25%. Without this input, this error rises to 4.95%, while for the anthropometric method is 3.68%.

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Section: Discussionmentioning

confidence: 99%

Method for Wearable Kinematic Gait Analysis Using a Harmonic Oscillator Applied to the Center of Mass

2018

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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%

“…Other applications also address gait signature analysis. For example, IMMUs are used to determine joint stress in barefoot running [64], landing patterns [30] and vertical loading [29,30,35,45,[65][66][67][68], loading while running barefoot [69], the effects of a high-heeled gait [70], the effects of rollover footwear [71], and the influence of the long-term wearing of unstable shoes [67].…”

Section: Sports and Healthy Living Applicationsmentioning

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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“…The relationship between the step length and walking speed has been researched in [30,31].These studies indicate that the step length became larger unconsciously when the walking speed was intended to be faster [31]. The following three-parameter linear model [30] is used to compute the step length via the following equation [32]:…”

Section: Pdr Based On Inertial Measurementmentioning

confidence: 99%

An Improved WiFi/PDR Integrated System Using an Adaptive and Robust Filter for Indoor Localization

Liu

Gao

et al. 2016

IJGI

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Location-based services (LBS) are services offered through a mobile device that take into account a device's geographical location. To provide position information for these services, location is a key process. GNSS (Global Navigation Satellite System) can provide sub-meter accuracy in open-sky areas using satellite signals. However, for indoor and dense urban environments, the accuracy deteriorates significantly because of weak signals and dense multipaths. The situation becomes worse in indoor environments where the GNSS signals are unreliable or totally blocked. To improve the accuracy of indoor positioning for location-based services, an improved WiFi/Pedestrian Dead Reckoning (PDR) integrated positioning and navigation system using an adaptive and robust filter is presented. The adaptive filter is based on scenario and motion state recognition and the robust filter is based on the Mahalanobis distance. They are combined and used in the WiFi/PDR integrated system to weaken the effect of gross errors on the dynamic and observation models. To validate their performance in the WiFi/PDR integrated system, a real indoor localization experiment is conducted. The results indicate that the adaptive filter is better able to adapt to the circumstances of the dynamic model by adjusting the covariance of the process noise and the robust Kalman filter is able to mitigate the harmful effect of gross errors from the WiFi positioning.

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Adaptive step length estimation algorithm using optimal parameters and movement status awareness

Cited by 85 publications

References 19 publications

Method for Wearable Kinematic Gait Analysis Using a Harmonic Oscillator Applied to the Center of Mass

Method for Wearable Kinematic Gait Analysis Using a Harmonic Oscillator Applied to the Center of Mass

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

An Improved WiFi/PDR Integrated System Using an Adaptive and Robust Filter for Indoor Localization

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