scholarly journals Clinometric Gait Analysis Using Smart Insoles in Patients With Hemiplegia After Stroke: Pilot Study

10.2196/22208 ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. e22208
Author(s):  
Minseok Seo ◽  
Myung-Jun Shin ◽  
Tae Sung Park ◽  
Jong-Hwan Park
Keyword(s):  
Gait Analysis ◽  
Objective Assessment ◽  
Assessment Tools ◽  
Stroke Severity ◽  
Walking Ability ◽  
Healthy Controls ◽  
Gait Parameters ◽  
Sound Side ◽  
Smart Insole ◽  
Stance Duration

Background For effective rehabilitation after stroke, it is essential to conduct an objective assessment of the patient’s functional status. Several stroke severity scales have been used for this purpose, but such scales have various limitations. Objective Gait analysis using smart insole technology can be applied continuously, objectively, and quantitatively, thereby overcoming the shortcomings of other assessment tools. Methods To confirm the reliability of gait analysis using smart insole technology, normal healthy controls wore insoles in their shoes during the Timed Up and Go (TUG) test. The gait parameters were compared with the manually collected data. To determine the gait characteristics of patients with hemiplegia due to stroke, they were asked to wear insoles and take the TUG test; gait parameters were calculated and compared with those of control subjects. To investigate whether the gait analysis accurately reflected the patients’ clinical condition, we analyzed the relationships of 22 gait parameters on 4 stroke severity scales. Results The smart insole gait parameter data were similar to those calculated manually. Among the 18 gait parameters tested, 14 were significantly effective at distinguishing patients from healthy controls. The smart insole data revealed that the stance duration on both sides was longer in patients than controls, which has proven difficult to show using other methods. Furthermore, the sound side in patients showed a markedly longer stance duration. Regarding swing duration, that of the sound side was shorter in patients than controls, whereas that of the hemiplegic side was longer. We identified 10 significantly correlated gait parameters on the stroke severity scales. Notably, the difference in stance duration between the sound and hemiplegic sides was significantly correlated with the Fugl-Meyer Assessment (FMA) lower extremity score. Conclusions This study confirmed the feasibility and applicability of the smart insole as a device to assess the gait of patients with hemiplegia due to stroke. In addition, we demonstrated that the FMA score was significantly correlated with the smart insole data. Providing an environment where stroke patients can easily measure walking ability helps to maintain chronic functions as well as acute rehabilitation. Trial Registration UMIN Clinical Trials Registry UMIN000041646, https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047538

scholarly journals Clinometric Gait Analysis Using Smart Insoles in Patients With Hemiplegia After Stroke: Pilot Study (Preprint)

2020 ◽  
Author(s):  
Minseok Seo ◽  
Myung-Jun Shin ◽  
Tae Sung Park ◽  
Jong-Hwan Park
Keyword(s):  
Gait Analysis ◽  
Objective Assessment ◽  
Assessment Tools ◽  
Stroke Severity ◽  
Walking Ability ◽  
Healthy Controls ◽  
Gait Parameters ◽  
Sound Side ◽  
Smart Insole ◽  
Stance Duration

BACKGROUND For effective rehabilitation after stroke, it is essential to conduct an objective assessment of the patient’s functional status. Several stroke severity scales have been used for this purpose, but such scales have various limitations. OBJECTIVE Gait analysis using smart insole technology can be applied continuously, objectively, and quantitatively, thereby overcoming the shortcomings of other assessment tools. METHODS To confirm the reliability of gait analysis using smart insole technology, normal healthy controls wore insoles in their shoes during the Timed Up and Go (TUG) test. The gait parameters were compared with the manually collected data. To determine the gait characteristics of patients with hemiplegia due to stroke, they were asked to wear insoles and take the TUG test; gait parameters were calculated and compared with those of control subjects. To investigate whether the gait analysis accurately reflected the patients’ clinical condition, we analyzed the relationships of 22 gait parameters on 4 stroke severity scales. RESULTS The smart insole gait parameter data were similar to those calculated manually. Among the 18 gait parameters tested, 14 were significantly effective at distinguishing patients from healthy controls. The smart insole data revealed that the stance duration on both sides was longer in patients than controls, which has proven difficult to show using other methods. Furthermore, the sound side in patients showed a markedly longer stance duration. Regarding swing duration, that of the sound side was shorter in patients than controls, whereas that of the hemiplegic side was longer. We identified 10 significantly correlated gait parameters on the stroke severity scales. Notably, the difference in stance duration between the sound and hemiplegic sides was significantly correlated with the Fugl-Meyer Assessment (FMA) lower extremity score. CONCLUSIONS This study confirmed the feasibility and applicability of the smart insole as a device to assess the gait of patients with hemiplegia due to stroke. In addition, we demonstrated that the FMA score was significantly correlated with the smart insole data. Providing an environment where stroke patients can easily measure walking ability helps to maintain chronic functions as well as acute rehabilitation. CLINICALTRIAL UMIN Clinical Trials Registry UMIN000041646, https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047538

scholarly journals Relationship between Gait Parameters and Postural Stability in Early and Late Parkinson's Disease and Visual Feedback-Based Balance Training Effects

2017 ◽  
Vol 5 (2) ◽  
pp. 207-214 ◽  
Author(s):  
Mohieldin M. Ahmed ◽  
Douaa M. Mosalem ◽  
Aziz K. Alfeeli ◽  
Ayyoub B. Baqer ◽  
Doaa Youssry Soliman
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Gait Analysis ◽  
Postural Stability ◽  
Walking Speed ◽  
Balance Training ◽  
Assessment Tools ◽  
Dynamic Posturography ◽  
Gait Parameters ◽  
Group B

BACKGROUND: Gait disorders or postural instability has been done before. However, lack of reviews has addressed the relation between gait and postural stability in Parkinson's disease (PD).AIM: The aim was to evaluate the relation between gait parameters and postural stability in early and late stages of PD.MATERIALS AND METHODS: The forty-one idiopathic PD patients were divided into two groups into a group (A) considered as early PD and group (B) considered as late ambulant PD. They were evaluated for postural stability by computerised dynamic posturography (CDP) device and gait analysis using an 8 m-camera Vicon 612 data capturing system set.RESULTS: There was a statistically significant improvement of composite equilibrium score, the composite latency of motor response, walking speed and cadence after treatment as compared to before training (p < 0.05) in early PD. However, in the late PD, there was a non-significant change of previous parameters after treatment as compared to before training (p > 0.05).There was a significant correlation between UPDRS motor part score, walking speed and composite equilibrium score after training in early PD (p > 0.05).CONCLUSIONS: Both gait analysis and CDP are important quantitative assessment tools of gait and posture instability.

CHILDREN WITH CEREBRAL PALSY USING A TRI-AXIAL ACCELEROMETER

2020 ◽  
Vol 18 (4) ◽  
pp. 465-476
Author(s):  
Zmnako Jamal Amen ◽  
Omer Ali Rafiq Barawi ◽  
Shirwan Hamasalh Omer
Keyword(s):  
Cerebral Palsy ◽  
Gait Analysis ◽  
Muscle Tone ◽  
Service Planning ◽  
Motor Dysfunction ◽  
Walking Ability ◽  
Clinical Utilization ◽  
Gait Parameters ◽  
Children With Cerebral Palsy ◽  
Analysis System

Worldwide children’s walking disabilities that are caused mainly by cerebral palsy display multiple conditions of both permanent and non-developing motor dysfunction that in turn upsets posture, mobility, or muscle tone in general. In order to estimate the influence of instrumented gait analysis on the walking ability in cerebral palsied children the Dynaport Minimod, based on a triaxial accelerometer was employed. A Dynaport Minimod was used for collecting the spatial and temporal gait data. An evaluation of the gait data carried out via online services application for 80 children with cerebral palsies from April 1 st , 2018 to October 30 th , 2019. The Dynaport Minimod is capable of capturing most of the spatiotemporal gait parameters which indicate that this technique is quite cooperative and objective in the detection of gait changes and the evaluation of consequences, respectively. The most useful practice for the managing of children with cerebral palsy is a gait analysis system in which its clinical utilization is considered to be a developing technology especially in providing guidance to service planning centres and hospitals.

scholarly journals Analysis of Gait Characteristics Using Hip-Knee Cyclograms in Patients with Hemiplegic Stroke

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7685
Author(s):  
Ho Seok Lee ◽  
Hokyoung Ryu ◽  
Shi-Uk Lee ◽  
Jae-sung Cho ◽  
Sungmin You ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Gait Variability ◽  
Measurement Unit ◽  
Stroke Severity ◽  
Healthy Controls ◽  
Stroke Patients ◽  
Joint Coordination ◽  
Gait Characteristics ◽  
Clinically Significant ◽  
Analysis System

Gait disturbance is a common sequela of stroke. Conventional gait analysis has limitations in simultaneously assessing multiple joints. Therefore, we investigated the gait characteristics in stroke patients using hip-knee cyclograms, which have the advantage of simultaneously visualizing the gait kinematics of multiple joints. Stroke patients (n = 47) were categorized into two groups according to stroke severity, and healthy controls (n = 32) were recruited. An inertial measurement unit sensor-based gait analysis system, which requires placing seven sensors on the dorsum of both feet, the shafts of both tibias, the middle of both femurs, and the lower abdomen, was used for the gait analysis. Then, the hip-knee cyclogram parameters (range of motion, perimeter, and area) were obtained from the collected data. The coefficient of variance of the cyclogram parameters was obtained to evaluate gait variability. The cyclogram parameters differed between the stroke patients and healthy controls, and differences according to stroke severity were also observed. The gait variability parameters mainly differed in patients with more severe stroke, and specific visualized gait patterns of stroke patients were obtained through cyclograms. In conclusion, the hip-knee cyclograms, which show inter-joint coordination and visualized gait cycle in stroke patients, are clinically significant.

scholarly journals A Novel Tool for Gait Analysis: Validation Study of the Smart Insole PODOSmart®

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5972
Author(s):  
Efthymios Ziagkas ◽  
Andreas Loukovitis ◽  
Dimitrios Xypolias Zekakos ◽  
Thomas Duc-Phu Chau ◽  
Alexandros Petrelis ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Intraclass Correlation ◽  
Real Life ◽  
Correlation Coefficients ◽  
Analysis Tool ◽  
Intraclass Correlation Coefficients ◽  
System Validation ◽  
Gait Parameters ◽  
Stride Duration ◽  
Smart Insole

The new smart insole PODOSmart®, is introduced as a new tool for gait analysis against high cost laboratory based equipment. PODOSmart® system measures walking profile and gait variables in real life conditions. PODOSmart® insoles consists of wireless sensors, can be fitted into any shoe and offer the ability to measure spatial, temporal, and kinematic gait parameters. The intelligent insoles feature several sensors that detect and capture foot movements and a microprocessor that calculates gait related biomechanical data. Gait analysis results are presented in PODOSmart® platform. This study aims to present the characteristics of this tool and to validate it comparing with a stereophotogrammetry-based system. Validation was performed by gait analysis for eleven healthy individuals on a six-meters walkway using both PODOSmart® and Vicon system. Intraclass correlation coefficients (ICC) were calculated for gait parameters. ICC for the validation ranged from 0.313 to 0.990 in gait parameters. The highest ICC was observed in cadence, circumduction, walking speed, stride length and stride duration. PODOSmart® is a valid tool for gait analysis compared to the gold standard Vicon. As PODOSmart®, is a portable gait analysis tool with an affordable cost it can be a useful novel tool for gait analysis in healthy and pathological population.

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

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.

scholarly journals The Utility of Gait Deviation Index (GDI) and Gait Variability Index (GVI) in Detecting Gait Changes in Spastic Hemiplegic Cerebral Palsy Children Using Ankle–Foot Orthoses (AFO)

Children ◽  
2020 ◽  
Vol 7 (10) ◽  
pp. 149
Author(s):  
Majewska Joanna ◽  
Szczepanik Magdalena ◽  
Bazarnik-Mucha Katarzyna ◽  
Szymczyk Daniel ◽  
Lenart-Domka Ewa
Keyword(s):  
Cerebral Palsy ◽  
Gait Analysis ◽  
Gait Variability ◽  
Therapeutic Interventions ◽  
Walking Ability ◽  
Deviation Index ◽  
Gait Parameters ◽  
Gait Deviation Index ◽  
Variability Index ◽  
Spatio Temporal

Background: Cerebral palsy (CP) children present complex and heterogeneous motor disorders that cause gait deviations. Clinical gait analysis (CGA) is used to identify, understand and support the management of gait deviations in CP. Children with CP often use ankle–foot orthosis (AFO) to facilitate and optimize their walking ability. The aim of this study was to assess whether the gait deviation index (GDI) and the gait variability index (GVI) results can reflect the changes of spatio-temporal and kinematic gait parameters in spastic hemiplegic CP children wearing AFO. Method: The study group consisted of 37 CP children with hemiparesis. All had undergone a comprehensive, instrumented gait analysis while walking, both barefoot and with their AFO, during the same CGA session. Kinematic and spatio-temporal data were collected and GVI and GDI gait indexes were calculated. Results: Significant differences were found between the barefoot condition and the AFO conditions for selected spatio-temporal and kinematic gait parameters. Changes in GVI and GDI were also statistically significant. Conclusions: The use of AFO in hemiplegic CP children caused a statistically significant improvement in spatio-temporal and kinematic gait parameters. It was found that these changes were also reflected by GVI and GDI. These findings might suggest that gait indices, such as GDI and GVI, as clinical outcome measures, may reflect the effects of specific therapeutic interventions in CP children.

scholarly journals Development of a Self-Powered Piezo-Resistive Smart Insole Equipped with Low-Power BLE Connectivity for Remote Gait Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4539
Author(s):  
Roberto de Fazio ◽  
Elisa Perrone ◽  
Ramiro Velázquez ◽  
Massimo De Vittorio ◽  
Paolo Visconti
Keyword(s):  
Low Power ◽  
Smart Materials ◽  
Applied Pressure ◽  
Pressure Sensors ◽  
Complete Characterization ◽  
Electric Signal ◽  
Sensing Matrix ◽  
Capacitive Accelerometer ◽  
Gait Parameters ◽  
Smart Insole

The evolution of low power electronics and the availability of new smart materials are opening new frontiers to develop wearable systems for medical applications, lifestyle monitoring, and performance detection. This paper presents the development and realization of a novel smart insole for monitoring the plantar pressure distribution and gait parameters; indeed, it includes a piezoresistive sensing matrix based on a Velostat layer for transducing applied pressure into an electric signal. At first, an accurate and complete characterization of Velostat-based pressure sensors is reported as a function of sizes, support material, and pressure trend. The realization and testing of a low-cost and reliable piezoresistive sensing matrix based on a sandwich structure are discussed. This last is interfaced with a low power conditioning and processing section based on an Arduino Lilypad board and an analog multiplexer for acquiring the pressure data. The insole includes a 3-axis capacitive accelerometer for detecting the gait parameters (swing time and stance phase time) featuring the walking. A Bluetooth Low Energy (BLE) 5.0 module is included for transmitting in real-time the acquired data toward a PC, tablet or smartphone, for displaying and processing them using a custom Processing® application. Moreover, the smart insole is equipped with a piezoelectric harvesting section for scavenging energy from walking. The onfield tests indicate that for a walking speed higher than 1 ms−1, the device’s power requirements (i.e., ) was fulfilled. However, more than 9 days of autonomy are guaranteed by the integrated 380-mAh Lipo battery in the total absence of energy contributions from the harvesting section.

scholarly journals Independent and sensitive gait parameters for objective evaluation in knee and hip osteoarthritis using wearable sensors

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ramon J. Boekesteijn ◽  
José M. H. Smolders ◽  
Vincent J. J. F. Busch ◽  
Alexander C. H. Geurts ◽  
Katrijn Smulders
Keyword(s):  
Dual Task ◽  
Wearable Sensors ◽  
Body Motion ◽  
Effect Sizes ◽  
Upper Body ◽  
Healthy Controls ◽  
Gait Parameters ◽  
Dual Task Cost ◽  
Dual Task Performance ◽  
Spatiotemporal Parameters

Abstract Background Although it is well-established that osteoarthritis (OA) impairs daily-life gait, objective gait assessments are not part of routine clinical evaluation. Wearable inertial sensors provide an easily accessible and fast way to routinely evaluate gait quality in clinical settings. However, during these assessments, more complex and meaningful aspects of daily-life gait, including turning, dual-task performance, and upper body motion, are often overlooked. The aim of this study was therefore to investigate turning, dual-task performance, and upper body motion in individuals with knee or hip OA in addition to more commonly assessed spatiotemporal gait parameters using wearable sensors. Methods Gait was compared between individuals with unilateral knee (n = 25) or hip OA (n = 26) scheduled for joint replacement, and healthy controls (n = 27). For 2 min, participants walked back and forth along a 6-m trajectory making 180° turns, with and without a secondary cognitive task. Gait parameters were collected using 4 inertial measurement units on the feet and trunk. To test if dual-task gait, turning, and upper body motion had added value above spatiotemporal parameters, a factor analysis was conducted. Effect sizes were computed as standardized mean difference between OA groups and healthy controls to identify parameters from these gait domains that were sensitive to knee or hip OA. Results Four independent domains of gait were obtained: speed-spatial, speed-temporal, dual-task cost, and upper body motion. Turning parameters constituted a gait domain together with cadence. From the domains that were obtained, stride length (speed-spatial) and cadence (speed-temporal) had the strongest effect sizes for both knee and hip OA. Upper body motion (lumbar sagittal range of motion), showed a strong effect size when comparing hip OA with healthy controls. Parameters reflecting dual-task cost were not sensitive to knee or hip OA. Conclusions Besides more commonly reported spatiotemporal parameters, only upper body motion provided non-redundant and sensitive parameters representing gait adaptations in individuals with hip OA. Turning parameters were sensitive to knee and hip OA, but were not independent from speed-related gait parameters. Dual-task parameters had limited additional value for evaluating gait in knee and hip OA, although dual-task cost constituted a separate gait domain. Future steps should include testing responsiveness of these gait domains to interventions aiming to improve mobility.

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