scholarly journals Estimation of Walking Speed and Its Spatiotemporal Determinants Using a Single Inertial Sensor Worn on the Thigh: From Healthy to Hemiparetic Walking

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 6976
Author(s):  
Dheepak Arumukhom Revi ◽  
Stefano M. M. De Rossi ◽  
Conor J. Walsh ◽  
Louis N. Awad
Keyword(s):  
Stride Length ◽  
Walking Speed ◽  
Inertial Sensor ◽  
Angular Position ◽  
Ground Truth ◽  
Phase Portraits ◽  
Measurement Unit ◽  
Camera Motion ◽  
Stride Time ◽  
Post Stroke

We present the use of a single inertial measurement unit (IMU) worn on the thigh to produce stride-by-stride estimates of walking speed and its spatiotemporal determinants (i.e., stride time and stride length). Ten healthy and eight post-stroke individuals completed a 6-min walk test with an 18-camera motion capture system used for ground truth measurements. Subject-specific estimation models were trained to estimate walking speed using the polar radius extracted from phase portraits produced from the IMU-measured thigh angular position and velocity. Consecutive flexion peaks in the thigh angular position data were used to define each stride and compute stride times. Stride-by-stride estimates of walking speed and stride time were then used to compute stride length. In both the healthy and post-stroke cohorts, low error and high consistency were observed for the IMU estimates of walking speed (MAE < 0.035 m/s; ICC > 0.98), stride time (MAE < 30 ms; ICC > 0.97), and stride length (MAE < 0.037 m; ICC > 0.96). This study advances the use of a single wearable sensor to accurately estimate walking speed and its spatiotemporal determinants during both healthy and hemiparetic walking.

scholarly journals Effectiveness of an ankle–foot orthosis on walking in patients with stroke: a systematic review and meta-analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yoo Jin Choo ◽  
Min Cheol Chang
Keyword(s):  
Stride Length ◽  
Walking Speed ◽  
Sagittal Plane ◽  
Meta Analysis ◽  
Step Length ◽  
Stride Time ◽  
Plane Angle ◽  
Ankle Foot Orthosis ◽  
Biomechanical Parameters ◽  
Foot Orthosis

AbstractWe conducted a meta-analysis to investigate the effectiveness of ankle–foot orthosis (AFO) use in improving gait biomechanical parameters such as walking speed, mobility, and kinematics in patients with stroke with gait disturbance. We searched the MEDLINE (Medical Literature Analysis and Retrieval System Online), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Cochrane, Embase, and Scopus databases and retrieved studies published until June 2021. Experimental and prospective studies were included that evaluated biomechanics or kinematic parameters with or without AFO in patients with stroke. We analyzed gait biomechanical parameters, including walking speed, mobility, balance, and kinematic variables, in studies involving patients with and without AFO use. The criteria of the Cochrane Handbook for Systematic Reviews of Interventions were used to evaluate the methodological quality of the studies, and the level of evidence was evaluated using the Research Pyramid model. Funnel plot analysis and Egger’s test were performed to confirm publication bias. A total of 19 studies including 434 participants that reported on the immediate or short-term effectiveness of AFO use were included in the analysis. Significant improvements in walking speed (standardized mean difference [SMD], 0.50; 95% CI 0.34–0.66; P < 0.00001; I2, 0%), cadence (SMD, 0.42; 95% CI 0.22–0.62; P < 0.0001; I2, 0%), step length (SMD, 0.41; 95% CI 0.18–0.63; P = 0.0003; I2, 2%), stride length (SMD, 0.43; 95% CI 0.15–0.71; P = 0.003; I2, 7%), Timed up-and-go test (SMD, − 0.30; 95% CI − 0.54 to − 0.07; P = 0.01; I2, 0%), functional ambulation category (FAC) score (SMD, 1.61; 95% CI 1.19–2.02; P < 0.00001; I2, 0%), ankle sagittal plane angle at initial contact (SMD, 0.66; 95% CI 0.34–0.98; P < 0.0001; I2, 0%), and knee sagittal plane angle at toe-off (SMD, 0.39; 95% CI 0.04–0.73; P = 0.03; I2, 46%) were observed when the patients wore AFOs. Stride time, body sway, and hip sagittal plane angle at toe-off were not significantly improved (p = 0.74, p = 0.07, p = 0.07, respectively). Among these results, the FAC score showed the most significant improvement, and stride time showed the lowest improvement. AFO improves walking speed, cadence, step length, and stride length, particularly in patients with stroke. AFO is considered beneficial in enhancing gait stability and ambulatory ability.

scholarly journals Validation of Spatiotemporal and Kinematic Measures in Functional Exercises Using a Minimal Modeling Inertial Sensor Methodology

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4586
Author(s):  
Benjamin R. Hindle ◽  
Justin W.L. Keogh ◽  
Anna V. Lorimer
Keyword(s):  
Excellent Agreement ◽  
Stride Length ◽  
Sagittal Plane ◽  
Inertial Sensor ◽  
Angular Rate ◽  
Percentage Error ◽  
Functional Fitness ◽  
Stride Time ◽  
Stance Time ◽  
Kinematic Measures

This study proposes a minimal modeling magnetic, angular rate and gravity (MARG) methodology for assessing spatiotemporal and kinematic measures of functional fitness exercises. Thirteen healthy persons performed repetitions of the squat, box squat, sandbag pickup, shuffle-walk, and bear crawl. Sagittal plane hip, knee, and ankle range of motion (ROM) and stride length, stride time, and stance time measures were compared for the MARG method and an optical motion capture (OMC) system. The root mean square error (RMSE), mean absolute percentage error (MAPE), and Bland–Altman plots and limits of agreement were used to assess agreement between methods. Hip and knee ROM showed good to excellent agreement with the OMC system during the squat, box squat, and sandbag pickup (RMSE: 4.4–9.8°), while ankle ROM agreement ranged from good to unacceptable (RMSE: 2.7–7.2°). Unacceptable hip and knee ROM agreement was observed for the shuffle-walk and bear crawl (RMSE: 3.3–8.6°). The stride length, stride time, and stance time showed good to excellent agreement between methods (MAPE: (3.2 ± 2.8)%–(8.2 ± 7.9)%). Although the proposed MARG-based method is a valid means of assessing spatiotemporal and kinematic measures during various exercises, further development is required to assess the joint kinematics of small ROM, high velocity movements.

Comparison of an Inertial Measurement Unit System and Baropodometric Platform for Measuring Spatiotemporal Parameters and Walking Speed in Healthy Adults

Motor Control ◽  
2021 ◽  
Vol 25 (1) ◽  
pp. 89-99
Author(s):  
Luca Correale ◽  
Vittoria Carnevale Pellino ◽  
Luca Marin ◽  
Massimiliano Febbi ◽  
Matteo Vandoni
Keyword(s):  
Inertial Measurement Unit ◽  
Stride Length ◽  
Walking Speed ◽  
Healthy Adults ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Therapy Program ◽  
Spatiotemporal Parameters ◽  
High Level ◽  
Level Of Agreement

Spatiotemporal parameters of walking are used to identify gait impairments and provide a tailored therapy program. Baropodometric platforms are not often used for measuring spatiotemporal parameters and walking speed and it is required to determine accuracy. The aim of this study was to compare FreeMed® Platform gait outcomes with a validated inertial measurement unit. There were 40 healthy adults without walking impairments enrolled. Each subject walked along a 15-m walkway at self and slow self-selected speed wearing an inertial measurement unit on the FreeMed® Platform. Stride length and time, right and left stance, swing time, and walking speed were recorded. Walking speed, stride length, and step time showed a very high level of agreement at slow walking speed and a high and moderate level of agreement at normal walking speed. FreeMed® Platform is useful to assess gait outcomes and could improve the exercise prescription.

scholarly journals Agreement between the GAITRite® System and the Wearable Sensor BTS G-Walk® for measurement of gait parameters in healthy adults and Parkinson’s disease patients

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8835 ◽  
Author(s):  
Slávka Vítečková ◽  
Hana Horáková ◽  
Kamila Poláková ◽  
Radim Krupička ◽  
Evžen Růžička ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Systematic Error ◽  
Stride Length ◽  
Walking Speed ◽  
Inertial Sensor ◽  
Pressure Sensors ◽  
Double Support ◽  
Gait Parameters ◽  
Stride Duration

Background Nowadays, the most widely used types of wearable sensors in gait analysis are inertial sensors. The aim of the study was to assess the agreement between two different systems for measuring gait parameters (inertial sensor vs. electronic walkway) on healthy control subjects (HC) and patients with Parkinson’s disease (PD). Methods Forty healthy volunteers (26 men, 14 women, mean age 58.7 ± 7.7 years) participated in the study and 24 PD patients (19 men, five women, mean age 62.7 ± 9.8 years). Each participant walked across an electronic walkway, GAITRite, with embedded pressure sensors at their preferred walking speed. Concurrently a G-Walk sensor was attached with a semi-elastic belt to the L5 spinal segment of the subject. Walking speed, cadence, stride duration, stride length, stance, swing, single support and double support phase values were compared between both systems. Results The Passing-Bablock regression slope line manifested the values closest to 1.00 for cadence and stride duration (0.99 ≤ 1.00) in both groups. The slope of other parameters varied between 0.26 (double support duration in PD) and 1.74 (duration of single support for HC). The mean square error confirmed the best fit of the regression line for speed, stride duration and stride length. The y-intercepts showed higher systematic error in PD than HC for speed, stance, swing, and single support phases. Conclusions The final results of this study indicate that the G-Walk system can be used for evaluating the gait characteristics of the healthy subjects as well as the PD patients. However, the duration of the gait cycle phases should be used with caution due to the presence of a systematic error.

scholarly journals Reference in-vitro dataset for inertial-sensor-to-bone alignment applied to the tibiofemoral joint

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ive Weygers ◽  
Manon Kok ◽  
Thomas Seel ◽  
Darshan Shah ◽  
Orçun Taylan ◽  
...  
Keyword(s):  
Inertial Sensors ◽  
Inertial Sensor ◽  
Ground Truth ◽  
Transformation Matrices ◽  
True Model ◽  
Advance Research ◽  
Manual Palpation ◽  
Visualization Tools ◽  
Inertial Measurements

AbstractSkin-attached inertial sensors are increasingly used for kinematic analysis. However, their ability to measure outside-lab can only be exploited after correctly aligning the sensor axes with the underlying anatomical axes. Emerging model-based inertial-sensor-to-bone alignment methods relate inertial measurements with a model of the joint to overcome calibration movements and sensor placement assumptions. It is unclear how good such alignment methods can identify the anatomical axes. Any misalignment results in kinematic cross-talk errors, which makes model validation and the interpretation of the resulting kinematics measurements challenging. This study provides an anatomically correct ground-truth reference dataset from dynamic motions on a cadaver. In contrast with existing references, this enables a true model evaluation that overcomes influences from soft-tissue artifacts, orientation and manual palpation errors. This dataset comprises extensive dynamic movements that are recorded with multimodal measurements including trajectories of optical and virtual (via computed tomography) anatomical markers, reference kinematics, inertial measurements, transformation matrices and visualization tools. The dataset can be used either as a ground-truth reference or to advance research in inertial-sensor-to-bone-alignment.

scholarly journals Measuring Gait Velocity and Stride Length with an Ultrawide Bandwidth Local Positioning System and an Inertial Measurement Unit

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2896
Author(s):  
Pratham Singh ◽  
Michael Esposito ◽  
Zach Barrons ◽  
Christian A. Clermont ◽  
John Wannop ◽  
...  
Keyword(s):  
Gold Standard ◽  
Gait Speed ◽  
Inertial Measurement Unit ◽  
Stride Length ◽  
Measurement Unit ◽  
Gait Velocity ◽  
Positioning System ◽  
Inertial Measurement ◽  
Measurement Systems ◽  
Local Positioning System

One possible modality to profile gait speed and stride length includes using wearable technologies. Wearable technology using global positioning system (GPS) receivers may not be a feasible means to measure gait speed. An alternative may include a local positioning system (LPS). Considering that LPS wearables are not good at determining gait events such as heel strikes, applying sensor fusion with an inertial measurement unit (IMU) may be beneficial. Speed and stride length determined from an ultrawide bandwidth LPS equipped with an IMU were compared to video motion capture (i.e., the “gold standard”) as the criterion standard. Ninety participants performed trials at three self-selected walk, run and sprint speeds. After processing location, speed and acceleration data from the measurement systems, speed between the last five meters and stride length in the last stride of the trial were analyzed. Small biases and strong positive intraclass correlations (0.9–1.0) between the LPS and “the gold standard” were found. The significance of the study is that the LPS can be a valid method to determine speed and stride length. Variability of speed and stride length can be reduced when exploring data processing methods that can better extract speed and stride length measurements.

Automatic Measurement of Walking Speed and Stride Length

1985 ◽  
Vol 14 (2) ◽  
pp. 101-106 ◽  
Author(s):  
R J Crawford ◽  
M H Sandford ◽  
G T Gillespie
Keyword(s):  
Stride Length ◽  
Walking Speed ◽  
Automatic Measurement

A longitudinal study investigating how stroke severity, disability, and physical function the first week post-stroke are associated with walking speed six months post-stroke

2017 ◽  
Vol 33 (12) ◽  
pp. 932-942 ◽  
Author(s):  
Mona Kristin Aaslund ◽  
Rolf Moe-Nilssen ◽  
Bente Bassøe Gjelsvik ◽  
Bård Bogen ◽  
Halvor Næss ◽  
...  
Keyword(s):  
Longitudinal Study ◽  
Physical Function ◽  
Walking Speed ◽  
Stroke Severity ◽  
Post Stroke
Sign in / Sign up

Export Citation Format

Share Document