Regression Models for Estimating Kinematic Gait Parameters with Instrumented Footwear

Zhang, Huanghe; Tay, Mey Olivares; Suar, Zeynep M.; Kurt, Mehmet; Zanotto, Damiano

doi:10.1109/biorob.2018.8487972

Cited by 9 publications

(4 citation statements)

References 36 publications

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“…The contributions of this work are: (i) a new, minimally obtrusive WBS and (ii) a new closed-loop vibrotactile stimulation method to induce a desired walking speed in the wearer during overground walking tasks. The WBS, built upon our previous work on instrumented footwear [ 37 , 38 , 39 , 40 , 41 , 42 ], is capable of measuring the stride velocity and phase of the gait cycle in real-time during overground walking tasks. These are used as inputs to a closed-loop biofeedback engine that leverages the effects of sensory reafferences’ modulation to elicit desired changes in the wearer’s gait velocity.…”

Section: Introductionmentioning

confidence: 99%

Wearable Biofeedback System to Induce Desired Walking Speed in Overground Gait Training

Zhang

Yin

Chen

et al. 2020

Sensors

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Biofeedback systems have been extensively used in walking exercises for gait improvement. Past research has focused on modulating the wearer’s cadence, gait variability, or symmetry, but none of the previous works has addressed the problem of inducing a desired walking speed in the wearer. In this paper, we present a new, minimally obtrusive wearable biofeedback system (WBS) that uses closed-loop vibrotactile control to elicit desired changes in the wearer’s walking speed, based on the predicted user response to anticipatory and delayed feedback. The performance of the proposed control was compared to conventional open-loop rhythmic vibrotactile stimulation with N = 10 healthy individuals who were asked to complete a set of walking tasks along an oval path. The closed-loop vibrotactile control consistently demonstrated better performance than the open-loop control in inducing desired changes in the wearer’s walking speed, both with constant and with time-varying target walking speeds. Neither open-loop nor closed-loop stimuli affected natural gait significantly, when the target walking speed was set to the individual’s preferred walking speed. Given the importance of walking speed as a summary indicator of health and physical performance, the closed-loop vibrotactile control can pave the way for new technology-enhanced protocols for gait rehabilitation.

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Section: Introductionmentioning

confidence: 99%

Wearable Biofeedback System to Induce Desired Walking Speed in Overground Gait Training

Zhang

Yin

Chen

et al. 2020

Sensors

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“…ξ and ξ * are slack variables, bounding regression errors that are tolerated. Based on our previous work [37]- [39], Gaussian radial basis function (RBF) was selected as the type of kernel function, and the sets of candidate values for the hyperparameters were restricted to the following: C ∈ [1 2 5 10 100], ε ∈ [0.1 0.2 0.5 0.8 1 1.2 1.5 2 2.5 3].…”

Section: Support Vector Regression (Svr)mentioning

confidence: 99%

“…Building upon our previous works on SVR models for ambulatory gait analysis [37]- [40], this paper introduces the following new contributions: (i) a novel transductive learning framework to improve validity and reliability of instrumented footwear in estimating spatiotemporal gait parameters, without the need for subject-specific labelled data; (ii) the validation of the proposed method against gold-standard instrumentation, in relation to conventional data processing techniques and to our previous SVR models, with a cohort of elderly residents of assisted living facilities; (iii) a study of the sensitivity of the proposed transductive models to different levels of gait impairment (as measured by a standardized clinical assessment) and to the use of mobility aids; and (iv) a feature analysis for the proposed models. The rest of the paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

Transductive Learning Models for Accurate Ambulatory Gait Analysis in Elderly Residents of Assisted Living Facilities

Zhang

Duong

Rao

et al. 2022

IEEE Trans. Neural Syst. Rehabil. Eng.

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Instrumented footwear represents a promising technology for spatiotemporal gait analysis in out-of-the-lab conditions. However, moderate accuracy impacts this technology's ability to capture subtle, but clinically meaningful, changes in gait patterns that may indicate adverse outcomes or underlying neurological conditions. This limitation hampers the use of instrumented footwear to aid functional assessments and clinical decision making. This paper introduces new transductivelearning inference models that substantially reduce measurement errors relative to conventional data processing techniques, without requiring subject-specific labelled data. The proposed models use subject-optimized input features and hyperparameters to adjust the spatiotemporal gait metrics (i.e., stride time, length, and velocity, swing time, and double support time) obtained with conventional techniques, resulting in computationally simpler models compared to end-to-end machine learning approaches. Model validity and reliability were evaluated against a goldstandard electronic walkway during a clinical gait performance test (6-minute walk test) administered to N=95 senior residents of assisted living facilities with diverse levels of gait and balance impairments. Average reductions in absolute errors relative to conventional techniques were −42.0% and −33.5% for spatial and gait-phase parameters, respectively, indicating the potential of transductive learning models for improving the accuracy of instrumented footwear for ambulatory gait analysis.

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“…However, it is worth noting that Yongbin Qi et al [33] validated their system against an ultrasound system, which is more prone to error compared to an optical motion capture system. Zhang et al [25] have struck a good balance between portability, performance, and complexity. They used an instrumented footwear unit called SoleSound that can be inserted into the shoe as a sole and collected the data via a single IMU.…”

Section: Performance Complexity and Portabilitymentioning

confidence: 99%

A Scoping Review on Minimum Foot Clearance Measurement: Sensing Modalities

Delfi

Bochi

Dutta

2021

IJERPH

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Background: Falls are a major public health issue and tripping is the most common self-reported cause of outdoor falls. Minimum foot clearance (MFC) is a key parameter for identifying the probability of tripping. Optical motion capture systems are commonly used to measure MFC values; however, there is a need to identify alternative modalities that are better suited to collecting data in real-world settings. Objective: This is the first of a two-part scoping review. The objective of this paper is to identify and evaluate alternative measurement modalities to optical motion capture systems for measuring level-ground MFC. A companion paper identifies conditions that impact MFC and the range of MFC values individuals that these conditions exhibit. Methods: We searched four electronic databases, where peer-reviewed journals and conference papers reporting level-ground MFC characteristics were identified. The papers were screened by two independent reviewers for inclusion. The reporting was done in keeping with the PRISMA-ScR reporting guidelines. Results: From an initial search of 1571 papers, 17 papers were included in this paper. The identified technologies were inertial measurement units (IMUs) (n = 10), ultrasonic sensors (n = 2), infrared sensors (IR) (n = 2), optical proximity sensors (OPS) (n = 1), laser ranging sensors (n = 1), and ultra-wideband sensors (n = 1). From the papers, we extracted the sensor type, the analysis methods, the properties of the proposed system, and its accuracy and validation methods. Conclusions: The two most commonly used alternative modalities were IMUs and OPS. There was a lack of standardization among studies utilizing the same measurement modalities, as well as discrepancies in the methods used to assess performance. We provide a list of recommendations for future work to allow for more meaningful comparison between modalities as well as future research directions.

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Regression Models for Estimating Kinematic Gait Parameters with Instrumented Footwear

Cited by 9 publications

References 36 publications

Wearable Biofeedback System to Induce Desired Walking Speed in Overground Gait Training

Wearable Biofeedback System to Induce Desired Walking Speed in Overground Gait Training

Transductive Learning Models for Accurate Ambulatory Gait Analysis in Elderly Residents of Assisted Living Facilities

A Scoping Review on Minimum Foot Clearance Measurement: Sensing Modalities

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