Gait analysis: determining heel-strike and toe-off events

Gait analysis has traditionally been carried out in a laboratory environment using expensive equipment, but, recently, reliable, affordable, and wearable sensors have enabled integration into clinical applications as well as use during activities of daily living. Real-time gait analysis is key to the development of gait rehabilitation techniques and assistive devices such as neuroprostheses. This article presents a systematic review of wearable sensors and techniques used in real-time gait analysis, and their application to pathological gait. From four major scientific databases, we identified 1262 articles of which 113 were analyzed in full-text. We found that heel strike and toe off are the most sought-after gait events. Inertial measurement units (IMU) are the most widely used wearable sensors and the shank and foot are the preferred placements. Insole pressure sensors are the most common sensors for ground-truth validation for IMU-based gait detection. Rule-based techniques relying on threshold or peak detection are the most widely used gait detection method. The heterogeneity of evaluation criteria prevented quantitative performance comparison of all methods. Although most studies predicted that the proposed methods would work on pathological gait, less than one third were validated on such data. Clinical applications of gait detection algorithms were considered, and we recommend a combination of IMU and rule-based methods as an optimal solution.

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Human Gait-labeling Uncertainty and a Hybrid Model for Gait Segmentation

10.36227/techrxiv.16924102.v1 ◽

2021 ◽

Author(s):

Jiaen Wu ◽

Henrik Maurenbrecher ◽

Alessandro Schaer ◽

Barna Becsek ◽

Chris Awai Easthope ◽

...

Keyword(s):

Gait Analysis ◽

Motion Capture ◽

Ground Truth ◽

Absolute Error ◽

Human Gait ◽

Heel Strike ◽

Analysis Model ◽

Flat Foot ◽

Dynamic Time ◽

Human Gait Analysis

<div><div><div><p>Motion capture systems are widely accepted as ground-truth for gait analysis and are used for the validation of other gait analysis systems.To date, their reliability and limitations in manual labeling of gait events have not been studied.</p><p><b>Objectives</b>: Evaluate human manual labeling uncertainty and introduce a new hybrid gait analysis model for long-term monitoring.</p><p><b>Methods</b>: Evaluate and estimate inter-labeler inconsistencies by computing the limits-of-agreement; develop a model based on dynamic time warping and convolutional neural network to identify a valid stride and eliminate non-stride data in walking inertial data collected by a wearable device; Gait events are detected within a valid stride region afterwards; This method makes the subsequent data computation more efficient and robust.</p><p><b>Results</b>: The limits of inter-labeler agreement for key</p><p>gait events of heel off, toe off, heel strike, and flat foot are 72 ms, 16 ms, 22 ms, and 80 ms, respectively; The hybrid model's classification accuracy for a stride and a non-stride are 95.16% and 84.48%, respectively; The mean absolute error for detected heel off, toe off, heel strike, and flat foot are 24 ms, 5 ms, 9 ms, and 13 ms, respectively.</p><p><b>Conclusions</b>: The results show the inherent label uncertainty and the limits of human gait labeling of motion capture data; The proposed hybrid-model's performance is comparable to that of human labelers and it is a valid model to reliably detect strides in human gait data.</p><p><b>Significance</b>: This work establishes the foundation for fully automated human gait analysis systems with performances comparable to human-labelers.</p></div></div></div>

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Vibration-based gait analysis via instrumented buildings

International Journal of Distributed Sensor Networks ◽

10.1177/1550147719881608 ◽

2019 ◽

Vol 15 (10) ◽

pp. 155014771988160

Author(s):

Ellis Kessler ◽

Vijaya VN Sriram Malladi ◽

Pablo A Tarazaga

Keyword(s):

Gait Analysis ◽

Heel Strike ◽

Vertical Acceleration ◽

Signal Energy ◽

Measurement Systems ◽

Gait Parameters ◽

Invaluable Tool ◽

Diagnostic Approaches ◽

Instrumented Buildings

Gait analysis is an invaluable tool in diagnosing and monitoring human health. Current techniques often rely on specialists or expensive gait measurement systems. There is a clear space in the field for a simple, inexpensive, quantitative way to measure various gait parameters. This study investigates if useful quantitative gait parameters can be extracted from floor acceleration measurements produced by the input of foot falls. A total of 17 participants walked along a 115-ft-long hallway while underfloor mounted accelerometers measured the vertical acceleration of the floor. Signal-energy-based algorithms detect the heel strike of each step during trials. From the detected footsteps, gait parameters such as the average stride length, the time between steps, and the step signal energy were calculated. In this study, a single accelerometer was shown to be enough to detect steps over a 115-ft corridor. Distributions for all gait parameters measured were generated for each participant, showing a normal distribution with low standard deviation. The success of gait analysis using underfloor accelerometers presents possibilities in the widespread adaptation of gait measurements. The ease of installation and operation offers an opportunity to gather long-term gait measurements. Such data will augment current gait diagnostic approaches by filling the gaps between specialist visits.

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What Is the Impact of a CAM Impingement on the Gait Cycle in Patients with Progressive Osteoarthritis of the Hip?

Applied Sciences ◽

10.3390/app11136024 ◽

2021 ◽

Vol 11 (13) ◽

pp. 6024

Author(s):

Eike Franken ◽

Thilo Floerkemeier ◽

Eike Jakubowitz ◽

Alexander Derksen ◽

Stefan Budde ◽

...

Keyword(s):

Gait Analysis ◽

Internal Rotation ◽

Gait Cycle ◽

Hip Osteoarthritis ◽

Gait Pattern ◽

Heel Strike ◽

Cam Impingement ◽

End Stage ◽

The Impact ◽

Cam Morphology

(1) Background: The femoroacetabular impingement (FAI) type cam leads to a conflict between the acetabular rim and a bony thickening of the femoral neck junction. While maximal excursions in flexion, adduction and internal rotation provoke pain, the aim of this study was to analyze if a cam morphology shows an impact on gait pattern. (2) Methods: Fifty-five patients with end-stage hip osteoarthritis performed gait analysis before hip replacement as well as three, six and 12 months postoperatively. Thirty-three (60%) of them presented an FAI type cam. An ANOVA was used to compare the hip angles in sagittal, frontal and transversal planes between patients with a FAI type cam (group “+cam”) and without (group “−cam”). (3) Results: Before surgery the patients of the +cam-group showed a tendency towards a reduced flexion and internal rotation at the heel strike (p > 0.05). Over time, the differences were adjusted by total hip arthroplasty. (4) Conclusions: We did not find any differences in the gait analysis of patients with a FAI type cam compared to patients without.

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Gait Changes with the Use of Heelys

Journal of the American Podiatric Medical Association ◽

10.7547/0980247 ◽

2009 ◽

Vol 99 (3) ◽

pp. 247-250

Author(s):

Nathan Norem ◽

Catherine Feuerstein ◽

Vincent Traverso ◽

Nancy Zomaya ◽

Ryan Crews ◽

...

Keyword(s):

Gait Analysis ◽

Heel Strike ◽

Single Subject ◽

System A ◽

The Subject

Heelys shoes are a novel athletic shoe with a concealed wheel. They have been popular among youths since their introduction in 2000. This case study serves as a first look into the biomechanical implications of Heelys shoes on gait. Pressure readings of the forefoot, midfoot, and rearfoot during ambulation in regular athletic-shoe walking, Heelys without the wheel walking, Heelys with the wheel walking, and Heelys skating with the wheel were recorded on a single subject using the Pedar X System. A visual gait analysis was also performed on the subject. The resulting data show increased forefoot and rearfoot pressure while walking with the Heelys with the wheel. The visual gait analysis showed a diminished heel strike and a more rapid forefoot loading. These results demonstrate that Heelys do in fact affect the biomechanics of gait. (J Am Podiatr Med Assoc 99(3): 247–250, 2009)

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Experimental Gait Analysis to Study Stress Distribution of the Human Foot

Journal of Medical Engineering ◽

10.1155/2017/3432074 ◽

2017 ◽

Vol 2017 ◽

pp. 1-13 ◽

Cited By ~ 10

Author(s):

Vidya K. Nandikolla ◽

Robin Bochen ◽

Steven Meza ◽

Allan Garcia

Keyword(s):

Gait Analysis ◽

Measurement System ◽

Healthy Subjects ◽

Force Measurement ◽

Metatarsophalangeal Joint ◽

The Body ◽

Heel Strike ◽

Human Foot ◽

Running Activity ◽

Pressure Peak

Researchers and clinicians are increasingly using plantar pressure and force measurement system to evaluate foot functions. This research evaluates the quality and reliability of a Tekscan HR mat to study the plantar pressures and forces acting during walking, running, jumping, and standing of healthy subjects. The following regions of the foot were investigated: heel, mid foot, metatarsophalangeal joint, hallux, and the toes. The arches of both feet of the three healthy subjects in the gait analysis were presented which addresses the balancing issues of the body during locomotion. The results indicated that the peaks at the big toe (79.4 ± 8.5 N/cm2, p = 0.0001) were the maximum compared to forefoot (40.3 ± 3.3 N/cm2, p = 0.001), to midfoot (7.5 ± 1.3 N/cm2, p = 0.001), and to heel (27.8 ± 3.9 N/cm2, p = 0.0002) for jump activity. The running activity demonstrated similar results as jump where the maximum peak pressures were absorbed at the big toe region. The heel region during running (86.3 ± 12.6 N/cm2, p = 0.001) showed three times the pressure peak compared to the jump land (27.8 ± 3.9 N/cm2, p = 0.0002) activity. The measurement system proved to be highly capable of detecting heel strike and toe-off moments.

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The effect of footwear mass on the gait patterns of unilateral below-knee amputees

Prosthetics and Orthotics International ◽

10.3109/03093648909079422 ◽

1989 ◽

Vol 13 (3) ◽

pp. 140-144 ◽

Cited By ~ 18

Author(s):

J. M. Donn ◽

D. Porter ◽

V. C. Roberts

Keyword(s):

Gait Analysis ◽

Body Mass ◽

Patellar Tendon ◽

Swing Phase ◽

Heel Strike ◽

Gait Patterns ◽

Maximum Flexion ◽

Time Symmetry ◽

Swing Time

This study reports an investigation into the effect of shoe mass on the gait patterns of below-knee (BK) amputees. Ten established unilateral BK, patellar-tendon-bearing prosthesis wearers were assessed using a VICON system of gait analysis. Incremental masses of 50g (up to 200g) were added to the subjects' shoes and data captured as they walked along a 15m measurement field. Coefficients of symmetry of various parameters of the swing phase (knee frequency symmetry, swing time symmetry, maximum flexion to heel strike time symmetry) were measured and their correlation was tested with the patient's preferrerd shoe mass and also their own shoe mass, all expressed as a proportion of body mass. The subjects' ‘preferred’ shoe mass (139-318g) showed the greatest symmetry in all the parameters examined (correlations 0.78-0.81 p<0.01 and <0.005), whereas there was no correlation between the subjects' own shoe mass (121-325g) and the symmetry coefficients measured.

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Validation of a Sensor-Based Gait Analysis System with a Gold-Standard Motion Capture System in Patients with Parkinson’s Disease

Sensors ◽

10.3390/s21227680 ◽

2021 ◽

Vol 21 (22) ◽

pp. 7680

Author(s):

Verena Jakob ◽

Arne Küderle ◽

Felix Kluge ◽

Jochen Klucken ◽

Bjoern M. Eskofier ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Gait Analysis ◽

Motion Capture ◽

Gold Standard ◽

Wearable Sensors ◽

Heel Strike ◽

Motion Capture System ◽

Gait Parameters ◽

Analysis System

Digital technologies provide the opportunity to analyze gait patterns in patients with Parkinson’s Disease using wearable sensors in clinical settings and a home environment. Confirming the technical validity of inertial sensors with a 3D motion capture system is a necessary step for the clinical application of sensor-based gait analysis. Therefore, the objective of this study was to compare gait parameters measured by a mobile sensor-based gait analysis system and a motion capture system as the gold standard. Gait parameters of 37 patients were compared between both systems after performing a standardized 5 × 10 m walking test by reliability analysis using intra-class correlation and Bland–Altman plots. Additionally, gait parameters of an age-matched healthy control group (n = 14) were compared to the Parkinson cohort. Gait parameters representing bradykinesia and short steps showed excellent reliability (ICC > 0.96). Shuffling gait parameters reached ICC > 0.82. In a stridewise synchronization, no differences were observed for gait speed, stride length, stride time, relative stance and swing time (p > 0.05). In contrast, heel strike, toe off and toe clearance significantly differed between both systems (p < 0.01). Both gait analysis systems distinguish Parkinson patients from controls. Our results indicate that wearable sensors generate valid gait parameters compared to the motion capture system and can consequently be used for clinically relevant gait recordings in flexible environments.

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Human Gait-labeling Uncertainty and a Hybrid Model for Gait Segmentation

10.36227/techrxiv.16924102 ◽

2021 ◽

Author(s):

Jiaen Wu ◽

Henrik Maurenbrecher ◽

Alessandro Schaer ◽

Barna Becsek ◽

Chris Awai Easthope ◽

...

Keyword(s):

Gait Analysis ◽

Motion Capture ◽

Ground Truth ◽

Absolute Error ◽

Human Gait ◽

Heel Strike ◽

Analysis Model ◽

Flat Foot ◽

Dynamic Time ◽

Human Gait Analysis

<div><div><div><p>Motion capture systems are widely accepted as ground-truth for gait analysis and are used for the validation of other gait analysis systems.To date, their reliability and limitations in manual labeling of gait events have not been studied.</p><p><b>Objectives</b>: Evaluate human manual labeling uncertainty and introduce a new hybrid gait analysis model for long-term monitoring.</p><p><b>Methods</b>: Evaluate and estimate inter-labeler inconsistencies by computing the limits-of-agreement; develop a model based on dynamic time warping and convolutional neural network to identify a valid stride and eliminate non-stride data in walking inertial data collected by a wearable device; Gait events are detected within a valid stride region afterwards; This method makes the subsequent data computation more efficient and robust.</p><p><b>Results</b>: The limits of inter-labeler agreement for key</p><p>gait events of heel off, toe off, heel strike, and flat foot are 72 ms, 16 ms, 22 ms, and 80 ms, respectively; The hybrid model's classification accuracy for a stride and a non-stride are 95.16% and 84.48%, respectively; The mean absolute error for detected heel off, toe off, heel strike, and flat foot are 24 ms, 5 ms, 9 ms, and 13 ms, respectively.</p><p><b>Conclusions</b>: The results show the inherent label uncertainty and the limits of human gait labeling of motion capture data; The proposed hybrid-model's performance is comparable to that of human labelers and it is a valid model to reliably detect strides in human gait data.</p><p><b>Significance</b>: This work establishes the foundation for fully automated human gait analysis systems with performances comparable to human-labelers.</p></div></div></div>

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Low-cost piezoelectric footswitch system for measuring temporal parameters during walking

International Journal of Engineering & Technology ◽

10.14419/ijet.v3i1.1733 ◽

2014 ◽

Vol 3 (1) ◽

pp. 75 ◽

Cited By ~ 1

Author(s):

Gustavo Balbinot ◽

Clarissa Pedrini Schuch ◽

Milton Antonio Zaro ◽

Marco Aur�lio Vaz

Keyword(s):

Gait Analysis ◽

Healthy Subjects ◽

Low Cost ◽

Heel Strike ◽

Altman Analysis ◽

Limits Of Agreement ◽

Validation Data ◽

Temporal Parameters ◽

Gait Parameters ◽

Emerging And Developing Countries

Human walking is one of the most investigated biomechanical events, and gait analysis depends on accurate measurement of heel strike (HS) and toe off (TO). The purpose of this study was to construct and validate a low-cost footswitch system for the measurement of temporal gait parameters. Ten young healthy subjects participated of the validation and test of the footswitch system with two different footwear, Bland-Altman analysis showed 98% and 95% of validation data within the limits of agreement, for HS and TO respectively (mean difference of 16ms1ms and 20ms9ms) and the temporal parameters measured during treadmill walking at a speed of 4.5km.h-1 showed results similar to those found in the literature for normal walking. The outcomes confirm low CoVs for the instrumented athletic and instability shoe, respectively: (1.520.61)% and (1.900.73)% for contact time, (2.170.95)% and (2.570.95)% for balance time, (0.840.28)% and (1.120.53)% for stride time. The low-cost footswitch system described and validated in the present study has an important practical applicability, mostly for emerging and developing countries biomechanics labs. Keywords: Footswitch System, Gait Analysis, Locomotion, Low-Cost, Walk.

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