Instrumented gait analysis defines the walking signature of CACNA1A disorders

Abstract Background Gait disturbances are a frequent symptom in CACNA1A disorders. Even though, data about their severity and progression are lacking and no CACNA1A-specific scale or assessment for gait is available. Methods We applied a gait assessment protocol in 20 ambulatory patients with genetically confirmed CACNA1A disorders and 39 matched healthy controls. An instrumented gait analysis (IGA) was performed by means of wearable sensors in basal condition and after a treadmill/cycloergometer challenge in selected cases. Results CACNA1A patients displayed lower gait speed, shorter steps with increased step length variability, a reduced landing acceleration as well as a reduced range of ankle motion compared to controls. Furthermore, gait-width in patients with episodic CACNA1A disorders was narrower as compared to controls. In one patient experiencing mild episodic symptoms after the treadmill challenge, the IGA was able to detect a deterioration over all gait parameters. Conclusions In CACNA1A patients, the IGA with wearable sensors unravels specific gait signatures which are not detectable at naked eye. These features (narrow-based gait, lower landing acceleration) distinguish these patients from other ataxic disorders and may be target of focused rehabilitative interventions. IGA can potentially be applied to monitor the neurological fluctuations associated with CACNA1A disorders.

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Development and Validation of 2D-LiDAR-Based Gait Analysis Instrument and Algorithm

Sensors ◽

10.3390/s21020414 ◽

2021 ◽

Vol 21 (2) ◽

pp. 414

Author(s):

Seongjun Yoon ◽

Hee-Won Jung ◽

Heeyoune Jung ◽

Keewon Kim ◽

Suk-Koo Hong ◽

...

Keyword(s):

Gait Analysis ◽

Motion Capture ◽

Step Length ◽

Analysis Tool ◽

Motion Capture System ◽

Neurocognitive Performance ◽

Lidar System ◽

Camera System ◽

Stereo Camera ◽

Gait Parameters

Acquiring gait parameters from usual walking is important to predict clinical outcomes including life expectancy, risk of fall, and neurocognitive performance in older people. We developed a novel gait analysis tool that is small, less-intrusive and is based on two-dimensional light detection and ranging (2D-LiDAR) technology. Using an object-tracking algorithm, we conducted a validation study of the spatiotemporal tracking of ankle locations of young, healthy participants (n = 4) by comparing our tool and a stereo camera with the motion capture system as a gold standard modality. We also assessed parameters including step length, step width, cadence, and gait speed. The 2D-LiDAR system showed a much better accuracy than that of a stereo camera system, where mean absolute errors were 46.2 ± 17.8 mm and 116.3 ± 69.6 mm, respectively. Gait parameters from the 2D-LiDAR system were in good agreement with those from the motion capture system (r = 0.955 for step length, r = 0.911 for cadence). Simultaneous tracking of multiple targets by the 2D-LiDAR system was also demonstrated. The novel system might be useful in space and resource constrained clinical practice for older adults.

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Fall-related functional impairments in patients with neurological gait disorder

Scientific Reports ◽

10.1038/s41598-020-77973-4 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Angela Ehrhardt ◽

Pascal Hostettler ◽

Lucas Widmer ◽

Katja Reuter ◽

Jens Alexander Petersen ◽

...

Keyword(s):

Gait Analysis ◽

Neurological Disorders ◽

Binary Logistic Regression ◽

Step Length ◽

Binary Logistic Regression Analysis ◽

Functional Impairments ◽

Gait Characteristics ◽

Gait Parameters ◽

Neurological Patients ◽

Spatio Temporal

AbstractFalls are common in patients with neurological disorders and are a primary cause of injuries. Nonetheless, fall-associated gait characteristics are poorly understood in these patients. Objective, quantitative gait analysis is an important tool to identify the principal fall-related motor characteristics and to advance fall prevention in patients with neurological disorders. Fall incidence was assessed in 60 subjects with different neurological disorders. Patients underwent a comprehensive set of functional assessments including instrumented gait analysis, computerized postural assessments and clinical walking tests. Determinants of falls were assessed by binary logistic regression analysis and receiver operator characteristics (ROC). The best single determinant of fallers was a step length reduction at slow walking speed reaching an accuracy of 67.2% (ROC AUC: 0.669; p = 0.027). The combination of 4 spatio-temporal gait parameters including step length and parameters of variability and asymmetry were able to classify fallers and non-fallers with an accuracy of 81.0% (ROC AUC: 0.882; p < 0.001). These findings suggest significant differences in specific spatio-temporal gait parameters between fallers and non-fallers among neurological patients. Fall-related impairments were mainly identified for spatio-temporal gait characteristics, suggesting that instrumented, objective gait analysis is an important tool to estimate patients' fall risk. Our results highlight pivotal fall-related walking deficits that might be targeted by future rehabilitative interventions that aim at attenuating falls.

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Wearable Sensors Technology as a Tool for Discriminating Frailty Levels During Instrumented Gait Analysis

10.21203/rs.3.rs-33024/v1 ◽

2020 ◽

Author(s):

Andrius Apsega ◽

Liudvikas Petrauskas ◽

Vidmantas Alekna ◽

Kristina Daunoraviciene ◽

Viktorija Sevcenko ◽

...

Keyword(s):

Gait Analysis ◽

Gait Speed ◽

Stance Phase ◽

Wearable Sensors ◽

Logistic Models ◽

Stride Time ◽

Double Support ◽

Phase Time ◽

Gait Assessment ◽

Gait Parameters

Abstract Background: One of the greatest challenges facing the healthcare of the aging population is frailty. There is growing scientific evidence that gait assessment using wearable sensors could be used for prefrailty and frailty screening. The purpose of this study was to examine the ability of a wearable sensor-based assessment of gait to discriminate between frailty levels (robust, prefrail, and frail).Methods: 133 participants (≥ 60 years) were recruited and frailty was assessed using the Fried criteria. Gait was assessed using wireless inertial sensors attached by straps on the thighs, shins, and feet. Between-group differences in frailty were assessed using analysis of variance. Associations between frailty and gait parameters was assessed using multinomial logistic models with frailty as the dependent variable. We used receiver operating characteristic (ROC) curves to calculate the area under the curve (AUC) to estimate the predictive validity of each parameter. The cut-off values were calculated based on the Youden index.Results: Frailty was identified in 37 (28%) participants, prefrailty in 66 (50%), and no Fried criteria were found in 30 (23%) participants. Gait speed, stance phase time, swing phase time, stride time, double support time, and cadence were able to discriminate frailty from robust, and prefrail from robust. Stride time (AUC = 0.915), stance phase (AUC = 0.923), and cadence (AUC = 0.930) were the most sensitive parameters to separate frail or prefrail from robust. Other gait parameters, such as double support, had poor sensitivity. We determined the value of stride time (1.19s), stance phase time (0.68s), and cadence (101 steps/min) to identify individuals with prefrailty or frailty with sufficient sensitivity and specificity.Conclusions: The results of our study show that gait analysis using wearable sensors could discriminate between frailty levels. We were able to identify several gait indicators apart from gait speed that distinguish frail or prefrail from robust with sufficient sensitivity and specificity. If improved and adapted for everyday use, gait assessment technologies could contribute to frailty screening and monitoring.

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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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Wearable Sensors Technology as a Tool for Discriminating Frailty Levels During Instrumented Gait Analysis

Applied Sciences ◽

10.3390/app10238451 ◽

2020 ◽

Vol 10 (23) ◽

pp. 8451

Author(s):

Andrius Apsega ◽

Liudvikas Petrauskas ◽

Vidmantas Alekna ◽

Kristina Daunoraviciene ◽

Viktorija Sevcenko ◽

...

Keyword(s):

Gait Analysis ◽

Sensitivity And Specificity ◽

Gait Speed ◽

Stance Phase ◽

Wearable Sensors ◽

Stride Time ◽

Double Support ◽

Phase Time ◽

Gait Assessment ◽

Gait Parameters

Background and objectives: One of the greatest challenges facing the healthcare of the aging population is frailty. There is growing scientific evidence that gait assessment using wearable sensors could be used for prefrailty and frailty screening. The purpose of this study was to examine the ability of a wearable sensor-based assessment of gait to discriminate between frailty levels (robust, prefrail, and frail). Materials and methods: 133 participants (≥60 years) were recruited and frailty was assessed using the Fried criteria. Gait was assessed using wireless inertial sensors attached by straps on the thighs, shins, and feet. Between-group differences in frailty were assessed using analysis of variance. Associations between frailty and gait parameters were assessed using multinomial logistic models with frailty as the dependent variable. We used receiver operating characteristic (ROC) curves to calculate the area under the curve (AUC) to estimate the predictive validity of each parameter. The cut-off values were calculated based on the Youden index. Results: Frailty was identified in 37 (28%) participants, prefrailty in 66 (50%), and no Fried criteria were found in 30 (23%) participants. Gait speed, stance phase time, swing phase time, stride time, double support time, and cadence were able to discriminate frailty from robust, and prefrail from robust. Stride time (AUC = 0.915), stance phase (AUC = 0.923), and cadence (AUC = 0.930) were the most sensitive parameters to separate frail or prefrail from robust. Other gait parameters, such as double support, had poor sensitivity. We determined the value of stride time (1.19 s), stance phase time (0.68 s), and cadence (101 steps/min) to identify individuals with prefrailty or frailty with sufficient sensitivity and specificity. Conclusions: The results of our study show that gait analysis using wearable sensors could discriminate between frailty levels. We were able to identify several gait indicators apart from gait speed that distinguish frail or prefrail from robust with sufficient sensitivity and specificity. If improved and adapted for everyday use, gait assessment technologies could contribute to frailty screening and monitoring.

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Concurrent Validity, Test-Retest Reliability, and Sensitivity to Change of a Single Body-Fixed Sensor for Gait Analysis during Rollator-Assisted Walking in Acute Geriatric Patients

Sensors ◽

10.3390/s20174866 ◽

2020 ◽

Vol 20 (17) ◽

pp. 4866

Author(s):

Christian Werner ◽

Patrick Heldmann ◽

Saskia Hummel ◽

Laura Bauknecht ◽

Jürgen M. Bauer ◽

...

Keyword(s):

Gait Analysis ◽

Gait Speed ◽

Concurrent Validity ◽

Geriatric Patients ◽

Step Length ◽

Sensitivity To Change ◽

Retest Reliability ◽

Gait Parameters ◽

Walk Ratio ◽

Test Retest Reliability

Body-fixed sensor (BFS) technology offers portable, low-cost and easy-to-use alternatives to laboratory-bound equipment for analyzing an individual’s gait. Psychometric properties of single BFS systems for gait analysis in older adults who require a rollator for walking are, however, unknown. The study’s aim was to evaluate the concurrent validity, test-retest-reliability, and sensitivity to change of a BFS (DynaPort MoveTest; McRoberts B.V., The Hague, The Netherlands) for measuring gait parameters during rollator-assisted walking. Fifty-eight acutely hospitalized older patients equipped with the BFS at the lower back completed a 10 m walkway using a rollator. Concurrent validity was assessed against the Mobility Lab (APDM Inc.; Portland, OR, USA), test-retest reliability over two trials within a 15 min period, and sensitivity to change in patients with improved, stable and worsened 4 m usual gait speed over hospital stay. Bland–Altman plots and intraclass correlation coefficients (ICC) for gait speed, cadence, step length, step time, and walk ratio indicate good to excellent agreement between the BFS and the Mobility Lab (ICC2,1 = 0.87–0.99) and the repeated trials (ICC2,1 = 0.83–0.92). Moderate to large standardized response means were observed in improved (gait speed, cadence, step length, walk ratio: 0.62–0.99) and worsened patients (gait speed, cadence, step time: −0.52 to −0.85), while those in stable patients were trivial to small (all gait parameters: −0.04–0.40). The BFS appears to be a valid, reliable and sensitive instrument for measuring spatio-temporal gait parameters during rollator-assisted walking in geriatric patients.

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Validity Analysis of WalkerViewTM Instrumented Treadmill for Measuring Spatiotemporal and Kinematic Gait Parameters

Sensors ◽

10.3390/s21144795 ◽

2021 ◽

Vol 21 (14) ◽

pp. 4795

Author(s):

Marco Bravi ◽

Carlo Massaroni ◽

Fabio Santacaterina ◽

Joshua Di Tocco ◽

Emiliano Schena ◽

...

Keyword(s):

Gait Analysis ◽

Excellent Agreement ◽

Intraclass Correlation ◽

Step Length ◽

Mean Value ◽

Altman Analysis ◽

Bland Altman Analysis ◽

Gait Parameters ◽

Spatiotemporal Parameters ◽

Walking Speeds

The detection of gait abnormalities is essential for professionals involved in the rehabilitation of walking disorders. Instrumented treadmills are spreading as an alternative to overground gait analysis. To date, the use of these instruments for recording kinematic gait parameters is still limited in clinical practice due to the lack of validation studies. This study aims to investigate the performance of a multi-sensor instrumented treadmill (i.e., WalkerViewTM, WV) for performing gait analysis. Seventeen participants performed a single gait test on the WV at three different speeds (i.e., 3 km/h, 5 km/h, and 6.6 km/h). In each trial, spatiotemporal and kinematic parameters were recorded simultaneously by the WV and by a motion capture system used as the reference. Intraclass correlation coefficient (ICC) of spatiotemporal parameters showed fair to excellent agreement at the three walking speeds for steps time, cadence, and step length (range 0.502–0.996); weaker levels of agreement were found for stance and swing time at all the tested walking speeds. Bland–Altman analysis of spatiotemporal parameters showed a mean of difference (MOD) maximum value of 0.04 s for swing/stance time and WV underestimation of 2.16 cm for step length. As for kinematic variables, ICC showed fair to excellent agreement (ICC > 0.5) for total range of motion (ROM) of hip at 3 km/h (range 0.579–0.735); weaker levels of ICC were found at 5 km/h and 6.6 km/h (range 0.219–0.447). ICC values of total knee ROM showed poor levels of agreement at all the tested walking speeds. Bland–Altman analysis of hip ROM revealed a higher MOD value at higher speeds up to 3.91°; the MOD values of the knee ROM were always higher than 7.67° with a 60° mean value of ROM. We demonstrated that the WV is a valid tool for analyzing the spatiotemporal parameters of walking and assessing the hip’s total ROM. Knee total ROM and all kinematic peak values should be carefully evaluated, having shown lower levels of agreement.

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Gait Analysis in the 6-Minute Walk Test in Patients with COPD

Reabilitacijos mokslai slauga kineziterapija ergoterapija ◽

10.33607/rmske.v1i8.855 ◽

2020 ◽

Vol 1 (8) ◽

Author(s):

Jan Szczegielniak ◽

Sebastian Rutkowski ◽

Anna Wdowiak ◽

Katarzyna Bogacz ◽

Jacek Luniewski

Keyword(s):

Gait Analysis ◽

Active Surface ◽

Step Length ◽

Walk Test ◽

Professional Literature ◽

Physical Effort ◽

Gait Parameters ◽

Step Duration ◽

6 Minute Walk Test ◽

Minute Walk

Professional literature provides various studies discussing gait pathologies depending on the type of nervous system and skeletomuscular system. There are, however, no complex studies discussing aspects of gait, such as walking pace, step length or step duration during the 6-minute walk test in patients with COPD. The objective of this work was, therefore, to analyse the gait of patients with COPD during the 6-minute walk test. It attempted to answer the question how gait parameters change during physical effort in case of patients with COPD. The research included 33 in-patients with COPD (27 males and 6 females), with median age of 65.7 ± 10.4, treated in MSWiA Hospital in Glucholazy. For the purposes of gait analysis, the GaitRite mat was used to measure walking pace, step length and step duration. The mat was 4 meters in length and the active surface consisted of 14 thousand sensors. Pearson’s correlation index and t test were used to calculate the relationships between the tested parameters. The analysis of the results showed that as the distance covered in the 6-minute walk test increased, the pace of walking decreased and the step duration and length significantly increased (p < 0.05). High correlations between the values of gait parameters and distance covered were observed. The research showed statistically significant differences in the values of parameters indicating walk pace, step duration and step length between the first and the last tests.Keywords: gait analysis, 6MWT, COPD.

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Inertial Measurement Unit-Based Estimation of Foot Trajectory for Clinical Gait Analysis

10.1101/595496 ◽

2019 ◽

Author(s):

Yumi Ono ◽

Koyu Hori ◽

Hiroki Ora ◽

Yuki Hirobe ◽

Yufeng Mao ◽

...

Keyword(s):

Gait Analysis ◽

Motion Capture ◽

Stride Length ◽

Wearable Sensors ◽

Analysis Method ◽

Inertial Measurement ◽

Gait Parameters ◽

Stride Duration ◽

Stance Duration ◽

Foot Trajectory

AbstractGait analysis is used widely in clinical practice for the evaluation of abnormal gait caused by disease. Conventionally, medical professionals use motion capture systems or make visual observations to evaluate a patient’s gait. Recent biomedical engineering studies have proposed easy-to-use gait analysis methods involving wearable sensors with inertial measurement units (IMUs). IMUs placed on the shanks just above the ankles allow for the long-term monitoring of gait because the participant can walk with or without shoes during the analysis. As far as the authors know, there is no report of the gait analysis method that estimates stride length, gait speed, stride duration, stance duration, and swing duration at the same time. In this study, we tested a proposed gait analysis method that uses IMUs attached on the shanks to estimate foot trajectory and temporal gait parameters. We evaluated this proposed method by analyzing the gait of 10 able-bodied participants (mean age 23.1 years, nine men and one woman). Wearable sensors were attached to the participants’ shanks, and we measured three-axis acceleration and three-axis angular velocity with the sensors to estimate foot trajectory during walking. We compared gait parameters estimated from the foot trajectory obtained with the proposed method and those measured with a motion capture system. Mean accuracy (mean ± standard deviation) was –0.046 ± 0.026 m for stride length, –0.036 ± 0.026 m/s for gait speed, –0.002 ± 0.019 s for stride duration, –0.000 ± 0.016 s for stance duration, and –0.002 ± 0.022 s for swing duration. These results suggest that the proposed method is useful for evaluation of clinical gait parameters.

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EFFECT OF AGE, GENDER, AND WALKWAY LENGTH ON ACCELEROMETRY-BASED GAIT PARAMETERS FOR HEALTHY ADULT SUBJECTS

Journal of Mechanics in Medicine and Biology ◽

10.1142/s0219519416500299 ◽

2016 ◽

Vol 16 (03) ◽

pp. 1650029 ◽

Cited By ~ 4

Author(s):

MITSURU YONEYAMA ◽

HIROSHI MITOMA ◽

AKITO HAYASHI

Keyword(s):

Gait Analysis ◽

Low Cost ◽

Step Length ◽

Clinical Analysis ◽

Reference Database ◽

Gait Parameters ◽

Japanese Adults ◽

Gender And Age ◽

Acceleration Data ◽

Effect Of Age

Accelerometry is now a well-established method for monitoring human body movements, and is increasingly being used for gait analysis under nonlaboratory conditions because of its low-cost and unobtrusive nature. In order to encourage its use in the clinical setting such as for assessing functional declines due to aging or disease, an extensive database of healthy gait is needed. This paper presents reference data for 245 normal Japanese adults (126 men and 119 women aged 40–86 years) obtained from indoor walk tests by using a trunk-mounted acceleration sensor. Seven gait parameters were extracted from the acceleration data measured at fast, normal, and slow gait for 5[Formula: see text]m and 10[Formula: see text]m walkways. The effects of age on cadence, speed, and step length were consistent with those observed in previous studies. Scaled speed and acceleration were closely correlated with each other, and exhibited similar gender- and age-associated behavior, indicating that they could be used interchangeably in gait analysis. A comparison of these parameters between different walkways revealed a significant effect of walkway length. Our parameters may provide a useful reference database for the clinical analysis of not only healthy gait but also impaired gait for the 10[Formula: see text]m walkway as well as for the shorter 5[Formula: see text]m walkway.

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