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.

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 Effects of Auditory Cueing on Cadence and Gait Pattern

2020 ◽  
Vol 64 (1) ◽  
pp. 1233-1237
Author(s):  
Andrei Carballo ◽  
Matthew Chang ◽  
Brian Hirmiz ◽  
Nicolette Lambright ◽  
Vivian Lee ◽  
...  
Keyword(s):  
Fall Risk ◽  
Stride Length ◽  
Step Length ◽  
Gait Pattern ◽  
Stride Time ◽  
Auditory Cues ◽  
Gait Patterns ◽  
Swing Time ◽  
Stance Time ◽  
Auditory Cueing

A large portion of the population participate in gait rehabilitation, especially those with conditions such as increased fall risk such as stroke, or Parkinson’s Disease. Some studies have shown that auditory cues help improve gait and reduce fall risk, but relationship with gait patterns is missing. In this study, eight participants walked at their preferred cadence and at increased and reduced cadence by 20%. We found that step length and step width were not significantly different in all walking conditions. Decreased cadence resulted in an increase of swing time, stance time, stride time, and stance to swing ratio, and a decrease in stride length. Increased cadence resulted in a decrease in stance time, stride time, swing time, and stance to swing ratio, and an increase in stride length. The results suggest there is a strong correlation between auditory cues and gait patterns that can improve rehabilitative processes in the future.

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 Characterization of gait variability in multiple system atrophy and Parkinson’s disease

2020 ◽  
Author(s):  
Victoria Sidoroff ◽  
Cecilia Raccagni ◽  
Christine Kaindlstorfer ◽  
Sabine Eschlboeck ◽  
Alessandra Fanciulli ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Multiple System Atrophy ◽  
Stride Length ◽  
Gait Variability ◽  
Postural Instability ◽  
Gait Velocity ◽  
Control Group ◽  
Stride Time ◽  
Stance Time

Abstract Background Gait impairment is a pivotal feature of parkinsonian syndromes and increased gait variability is associated with postural instability and a higher risk of falls. Objectives We compared gait variability at different walking velocities between and within groups of patients with Parkinson-variant multiple system atrophy, idiopathic Parkinson’s disease, and a control group of older adults. Methods Gait metrics were recorded in 11 multiple system atrophy, 12 Parkinson’s disease patients, and 18 controls using sensor-based gait analysis. Gait variability was analyzed for stride, swing and stance time, stride length and gait velocity. Values were compared between and within the groups at self-paced comfortable, fast and slow walking speed. Results Multiple system atrophy patients displayed higher gait variability except for stride time at all velocities compared with controls, while Parkinson’s patients did not. Compared with Parkinson’s disease, multiple system atrophy patients displayed higher variability of swing time, stride length and gait velocity at comfortable speed and at slow speed for swing and stance time, stride length and gait velocity (all P < 0.05). Stride time variability was significantly higher in slow compared to comfortable walking in patients with multiple system atrophy (P = 0.014). Variability parameters significantly correlated with the postural instability/gait difficulty subscore in both disease groups. Conversely, significant correlations between variability parameters and MDS-UPDRS III score was observed only for multiple system atrophy patients. Conclusion This analysis suggests that gait variability parameters reflect the major axial impairment and postural instability displayed by multiple system atrophy patients compared with Parkinson’s disease patients and controls.

scholarly journals A Hybrid Framework for Mitigating Heading Drift for a Wearable Pedestrian Navigation System through Adaptive Fusion of Inertial and Magnetic Measurements

2021 ◽  
Vol 11 (4) ◽  
pp. 1902
Author(s):  
Liqiang Zhang ◽  
Yu Liu ◽  
Jinglin Sun
Keyword(s):  
Magnetic Measurements ◽  
Inertial Sensor ◽  
Angular Rate ◽  
Human Motion ◽  
Navigation Systems ◽  
Pedestrian Navigation ◽  
Hybrid Framework ◽  
Outdoor Environments ◽  
Adaptive Fusion ◽  
Indoor And Outdoor Environments

Pedestrian navigation systems could serve as a good supplement for other navigation methods or for extending navigation into areas where other navigation systems are invalid. Due to the accumulation of inertial sensing errors, foot-mounted inertial-sensor-based pedestrian navigation systems (PNSs) suffer from drift, especially heading drift. To mitigate heading drift, considering the complexity of human motion and the environment, we introduce a novel hybrid framework that integrates a foot-state classifier that triggers the zero-velocity update (ZUPT) algorithm, zero-angular-rate update (ZARU) algorithm, and a state lock, a magnetic disturbance detector, a human-motion-classifier-aided adaptive fusion module (AFM) that outputs an adaptive heading error measurement by fusing heuristic and magnetic algorithms rather than simply switching them, and an error-state Kalman filter (ESKF) that estimates the optimal systematic error. The validation datasets include a Vicon loop dataset that spans 324.3 m in a single room for approximately 300 s and challenging walking datasets that cover large indoor and outdoor environments with a total distance of 12.98 km. A total of five different frameworks with different heading drift correction methods, including the proposed framework, were validated on these datasets, which demonstrated that our proposed ZUPT–ZARU–AFM–ESKF-aided PNS outperforms other frameworks and clearly mitigates heading drift.

Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane

2022 ◽  
pp. 095441192110729
Author(s):  
Gunjan Patel ◽  
Rajani Mullerpatan ◽  
Bela Agarwal ◽  
Triveni Shetty ◽  
Rajdeep Ojha ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Motion Analysis ◽  
Motion Capture ◽  
Inertial Sensor ◽  
Joint Kinematics ◽  
Percentage Error ◽  
Motion Capture System ◽  
Spatiotemporal Parameters ◽  
Analysis System ◽  
Motion Capture Systems

Wearable inertial sensor-based motion analysis systems are promising alternatives to standard camera-based motion capture systems for the measurement of gait parameters and joint kinematics. These wearable sensors, unlike camera-based gold standard systems, find usefulness in outdoor natural environment along with confined indoor laboratory-based environment due to miniature size and wireless data transmission. This study reports validation of our developed (i-Sens) wearable motion analysis system against standard motion capture system. Gait analysis was performed at self-selected speed on non-disabled volunteers in indoor ( n = 15) and outdoor ( n = 8) environments. Two i-Sens units were placed at the level of knee and hip along with passive markers (for indoor study only) for simultaneous 3D motion capture using a motion capture system. Mean absolute percentage error (MAPE) was computed for spatiotemporal parameters from the i-Sens system versus the motion capture system as a true reference. Mean and standard deviation of kinematic data for a gait cycle were plotted for both systems against normative data. Joint kinematics data were analyzed to compute the root mean squared error (RMSE) and Pearson’s correlation coefficient. Kinematic plots indicate a high degree of accuracy of the i-Sens system with the reference system. Excellent positive correlation was observed between the two systems in terms of hip and knee joint angles (Indoor: hip 3.98° ± 1.03°, knee 6.48° ± 1.91°, Outdoor: hip 3.94° ± 0.78°, knee 5.82° ± 0.99°) with low RMSE. Reliability characteristics (defined using standard statistical thresholds of MAPE) of stride length, cadence, walking speed in both outdoor and indoor environment were well within the “Good” category. The i-Sens system has emerged as a potentially cost-effective, valid, accurate, and reliable alternative to expensive, standard motion capture systems for gait analysis. Further clinical trials using the i-Sens system are warranted on participants across different age groups.

scholarly journals Reliability and Agreement of 3D Trunk and Lower Extremity Movement Analysis by Means of Inertial Sensor Technology for Unipodal and Bipodal Tasks

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 141 ◽  
Author(s):  
Rob Van der Straaten ◽  
Amber K. B. D. Bruijnes ◽  
Benedicte Vanwanseele ◽  
Ilse Jonkers ◽  
Liesbet De Baets ◽  
...  
Keyword(s):  
Lower Limb ◽  
Sagittal Plane ◽  
Inertial Sensor ◽  
Movement Analysis ◽  
Sensor Technology ◽  
Inertial Measurement ◽  
Sit To Stand ◽  
Movement Strategies ◽  
Measurement Units ◽  
Healthy Participants

This study evaluates the reliability and agreement of the 3D range of motion (ROM) of trunk and lower limb joints, measured by inertial measurement units (MVN BIOMECH Awinda, Xsens Technologies), during a single leg squat (SLS) and sit to stand (STS) task. Furthermore, distinction was made between movement phases, to discuss the reliability and agreement for different phases of both movement tasks. Twenty healthy participants were measured on two testing days. On day one, measurements were conducted by two operators to determine the within-session and between-operator reliability and agreement. On day two, measurements were conducted by the same operator, to determine the between-session reliability and agreement. The SLS task had lower within-session reliability and agreement compared with between-session and between-operator reliability and agreement. The reliability and agreement of the hip, knee, and ankle ROM in the sagittal plane were good for both phases of the SLS task. For both phases of STS task, within-session reliability and agreement were good, and between-session and between-operator reliability and agreement were lower in all planes. As both tasks are physically demanding, differences may be explained by inconsistent movement strategies. These results show that inertial sensor systems show promise for use in further research to investigate (mal)adaptive movement strategies.

scholarly journals Assessing the concurrent validity of a gait analysis system integrated into a smart walker in older adults with gait impairments

2019 ◽  
Vol 33 (10) ◽  
pp. 1682-1687 ◽  
Author(s):  
Christian Werner ◽  
Georgia Chalvatzaki ◽  
Xanthi S Papageorgiou ◽  
Costas S Tzafestas ◽  
Jürgen M Bauer ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Gait Speed ◽  
Concurrent Validity ◽  
Stride Length ◽  
Gait Parameters ◽  
Stance Time ◽  
Absolute Agreement ◽  
Analysis System ◽  
Smart Walker ◽  
Gait Impairments

Objective: To assess the concurrent validity of a smart walker–integrated gait analysis system with the GAITRite® system for measuring spatiotemporal gait parameters in potential users of the smart walker. Design: Criterion standard validation study. Setting: Research laboratory in a geriatric hospital. Participants: Twenty-five older adults (⩾65 years) with gait impairments (habitual rollator use and/or gait speed <0.6 m/s) and no severe cognitive impairment (Mini-Mental State Examination ⩾17). Main measures: Stride, swing and stance time; stride length; and gait speed were simultaneously recorded using the smart walker–integrated gait analysis system and the GAITRite system while participants walked along a 7.8-m walkway with the smart walker. Concurrent criterion-related validity was assessed using the Bland–Altman method, percentage errors (acceptable if <30%), and intraclass correlation coefficients for consistency (ICC3,1) and absolute agreement (ICC2,1). Results: Bias for stride, swing and stance time ranged from −0.04 to 0.04 seconds, with acceptable percentage errors (8.7%–23.0%). Stride length and gait speed showed higher bias (meanbias (SD) = 0.20 (0.11) m; 0.19 (0.13) m/s) and not acceptable percentage errors (31.3%–42.3%). Limits of agreement were considerably narrower for temporal than for spatial-related gait parameters. All gait parameters showed good-to-excellent consistency (ICC3,1 = 0.72–0.97). Absolute agreement was good-to-excellent for temporal (ICC2,1 = 0.72–0.97) but only poor-to-fair for spatial-related gait parameters (ICC2,1 = 0.37–0.52). Conclusion: The smart walker–integrated gait analysis system has good concurrent validity with the GAITRite system for measuring temporal but not spatial-related gait parameters in potential end-users of the smart walker. Stride length and gait speed can be measured with good consistency, but with only limited absolute accuracy.

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