Interpretation of Gait Supervising Mechanism Using Sensor Integrated Makeshift and Analysing Pattern by K-Means Clustering Algorithm

2021 ◽  
Vol 11 (10) ◽  
pp. 2598-2609
Author(s):  
J. Shanthini ◽  
P. Arunkumar ◽  
S. Karthik ◽  
N. Karthikeyan
Keyword(s):  
Clustering Algorithm ◽  
Inertial Sensors ◽  
Human Mobility ◽  
Rehabilitation Medicine ◽  
Clinical Analysis ◽  
Gait Pattern ◽  
Foot Pressure ◽  
Integrated Sensor ◽  
Post Surgery ◽  
Walking Pattern

Human mobility or walking pattern(gait) is described as the interpreter movements of the rotatory body to achieve extensive range of locomotion. Gait analysis is foremost widely used technique for identifying abnormalities in the lower extremities and gait characteristics essentially support HAT (Head, Arm & Trunk). The act of walking is unconscious when there are no dysfunctions, but for ambulated the continuous monitoring is required. The existing clinical analysis method couldn’t achieve the daily walking routine within the confinement of a room.The proposed method focuses on developing an ambulatory system on daily routines by incorporating feasible techniques for achieving the gait pattern which is not confined to a room atmosphere where all possibilities of walking pattern can’t be reached.This system has expounded an ideology, to interpret the gait parameters using an insole type shoe integrated sensor system. Here, a wearable gait system which is incorporated with force resistive sensors, piezo sensors, inertial sensors and IR sensors are interfaced to the ESP 32. The corresponding sensors extract the data of kinematic angles, kinetics, foot pressure, step count and foot stride investigations.The system proved to be efficient in finding the phases and orientation of the individual by interpreting values from the device. Acquired data can be clustered together to find the abnormal and normal values by applying K-Means clustering algorithm, later the values are utilized in biomechanics for rectifying posture or movement related problems.The device will have several applications in sports, rehabilitation medicine and post-surgery treatment.

scholarly journals Smartphone-Based Inertial Odometry for Blind Walkers

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4033
Author(s):  
Peng Ren ◽  
Fatemeh Elyasi ◽  
Roberto Manduchi
Keyword(s):  
Particle Filtering ◽  
Inertial Sensors ◽  
State Of The Art ◽  
Inertial Sensor ◽  
Mean Shift ◽  
Gait Pattern ◽  
Comparative Assessment ◽  
Pedestrian Tracking ◽  
Step Counter ◽  
Assisted Navigation

Pedestrian tracking systems implemented in regular smartphones may provide a convenient mechanism for wayfinding and backtracking for people who are blind. However, virtually all existing studies only considered sighted participants, whose gait pattern may be different from that of blind walkers using a long cane or a dog guide. In this contribution, we present a comparative assessment of several algorithms using inertial sensors for pedestrian tracking, as applied to data from WeAllWalk, the only published inertial sensor dataset collected indoors from blind walkers. We consider two situations of interest. In the first situation, a map of the building is not available, in which case we assume that users walk in a network of corridors intersecting at 45° or 90°. We propose a new two-stage turn detector that, combined with an LSTM-based step counter, can robustly reconstruct the path traversed. We compare this with RoNIN, a state-of-the-art algorithm based on deep learning. In the second situation, a map is available, which provides a strong prior on the possible trajectories. For these situations, we experiment with particle filtering, with an additional clustering stage based on mean shift. Our results highlight the importance of training and testing inertial odometry systems for assisted navigation with data from blind walkers.

MODIFICATION IN FOOT PRESSURE AND GAIT PATTERN AFTER ARTHROSCOPIC CARTILAGE REGENERATION FACILITATING PROCEDURES (ACRFP) IN PATIENTS WITH OSTEOARTHRITIS OF KNEE

2019 ◽  
Vol 19 (02) ◽  
pp. 1940026
Author(s):  
TSUNG-CHIAO WU ◽  
CHUAN-HSIN YEN ◽  
SHAW-RUEY LYU ◽  
SHUO-SUEI HUNG
Keyword(s):  
Knee Injury ◽  
Cartilage Regeneration ◽  
Gait Pattern ◽  
Knee Joints ◽  
Knee Adduction Moment ◽  
Control Group ◽  
Lateral Side ◽  
Foot Pressure ◽  
Chronic Knee Pain ◽  
Gait Parameters

Arthroscopic cartilage regeneration facilitating procedure (ACRFP) has been reported with satisfactory results, yet there is limited research on the biomechanics in these patients. The purpose of this study is to assess the change on the biomechanics after ACRFP, in terms of foot pressure and gait pattern. Patients with chronic knee pain due to osteoarthritis and received ACRFP were recruited, and the knee joints in each patient were divided into either study or control group according to radiographical or symptomatic severity. Assessments were done with Knee injury and Osteoarthritis Outcome Score (KOOS) and dynamic foot pressure at the time before surgery, three months and six months postoperatively. A total of 24 patients completed the study. Significant improvement was found of KOOS, at both three and six months postoperatively. No much change in the gait parameters was noted, but there was a significant decrease of foot pressure over lateral side of hindfoot at six months postoperatively. In conclusion, significant clinical improvements could be achieved with surgical results of ACRFP, and shifting of the foot pressure medially may be related to decrease in the knee adduction moment, which is more favorable for the knee joints.

scholarly journals Online Biped Walking Pattern Generation with Contact Consistency

2015 ◽  
Vol 4 (1) ◽  
pp. 19
Author(s):  
Wenqi Hou ◽  
Jian Wang ◽  
Jianwen Wang ◽  
Hongxu Ma
Keyword(s):  
Biped Robot ◽  
Gait Pattern ◽  
Pattern Generation ◽  
Task Space ◽  
Biped Walking ◽  
Foot Placement ◽  
Walking Gait ◽  
Walking Pattern ◽  
Generating Method ◽  
Stable Periodic

In this paper, a novel online biped walking gait pattern generating method with contact consistency is proposed. Generally, it’s desirable that there is no foot-ground slipping during biped walking. By treating the hip of the biped robot as a linear inverted pendulum (LIP), a foot placement controller that takes the contact consistency into account is proposed to tracking the desired orbit energy. By selecting the hip’s horizontal locomotion as the parameter, the trajectories in task space for walking are planned. A task space controller without calculating the inversion of inertial matrix is presented. Simulation experiments are implemented on a virtual 5-link point foot biped robot. The results show the effectiveness of the walking pattern generating method which can realize a stable periodic gait cycle without slipping and falling even suffering a sudden disturbance.

Calibration of a micro-electro mechanical system-based accelerometer for vehicle navigation

2018 ◽  
Vol 233 (2) ◽  
pp. 554-560 ◽  
Author(s):  
A Ghaffari ◽  
A Khodayari ◽  
S Nosoudi ◽  
S Arefnezhad
Keyword(s):  
Mechanical System ◽  
Clustering Algorithm ◽  
Moving Objects ◽  
Inertial Sensors ◽  
Low Cost ◽  
Micro Electro Mechanical System ◽  
Subtractive Clustering ◽  
Measured Velocity ◽  
Preliminary Model ◽  
Dynamic Errors

Micro-electro mechanical system-based inertial sensors have broad applications in moving objects including in vehicles for navigation purposes. The low-cost micro-electro mechanical system sensors are normally subject to high dynamic errors such as linear or nonlinear bias, misalignment errors and random noises. In the class of low cost sensors, keeping the accuracy at a reasonable range has always been challenging for engineers. In this paper, a novel method for calibrating low-cost micro-electro mechanical system accelerometers is presented based on soft computing approaches. The method consists of two steps. In the first step, a preliminary model for error sources is presented based on fuzzy subtractive clustering algorithm. This model is then improved using adaptive neuro-fuzzy systems. A Kalman filter is also used to calculate the vehicle velocity and its position based on calibrated measured acceleration. The performance of the presented approach has been validated in the simulated and real experimental driving scenarios. The results show that this method can improve the accuracy of the accelerometer output, measured velocity and position of the vehicle by 79.11%, 97.63% and 99.28%, in the experimental test, respectively. The presented procedure can be used in collision avoidance and emergency brake assist systems.

Optimized Motion Control of an Intelligent Cane Robot for Easing Muscular Fatigue in the Elderly During Walking

2013 ◽  
Vol 25 (6) ◽  
pp. 1070-1077 ◽  
Author(s):  
Pei Di ◽  
◽  
Jian Huang ◽  
Shotaro Nakagawa ◽  
Kosuke Sekiyama ◽  
...  
Keyword(s):  
Control Method ◽  
The Elderly ◽  
Gait Pattern ◽  
Muscular Fatigue ◽  
Walking Pattern ◽  
Load Sensor ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor ◽  
Support Phase

In previous works, an intelligent cane robot was proposed to assist the elderly or persons with conditions that slightly restrict their motion ability. The cane robot can help the elderly walk in both indoor and outdoor environments because of its miniaturized design and mobility. In the intentional direction (ITD) concept the user’s walking intention is estimated by analyzing signals from a six-axis force/torque sensor. An admittance control method controls the motion of the cane robot. In some cases, however the elderly can not walk uniformly because one leg suffers from muscular weakness. When the affected leg is in the support phase, the cane robot should stop to absorb more strain than the affected leg. When the healthy leg is in the support phase, the cane robot should move forward according to ITD. In contrast to ITD, the motion of the cane robot should be controlled considering the walking pattern characteristics of the elderly to ensure safety and effectiveness. In this paper, an optimizedmotion control of the cane robot is proposed that is based on the characteristics gait pattern (CGP). An on-shoe load sensor was used to evaluate the reduction in muscular fatigue for the user’s affected leg. The effectiveness of the proposed method was verified through experiments.

An estimation for center of foot pressure while walking using inertial sensors

2018 ◽  
Vol 2018.56 (0) ◽  
pp. 114
Author(s):  
Kenji NARIMATSU ◽  
Kyoko SHIBATA ◽  
Yoshio INOUE ◽  
Motomichi SONOBE
Keyword(s):  
Inertial Sensors ◽  
Foot Pressure ◽  
Center Of Foot Pressure

A Low Power Wireless Data Acquisition Device to Monitor Gait Patterns for Children With Toe Walking During Daily Activities

2011 ◽  
Vol 5 (2) ◽  
Author(s):  
Edmond H. M. Lou ◽  
Emma K. Brunton ◽  
Fraaz Kamal ◽  
Andreas Renggli ◽  
Kyle Kemp ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Gait Pattern ◽  
Daily Activities ◽  
Wireless Data ◽  
Normal Gait ◽  
Walking Pattern ◽  
Wireless Data Acquisition ◽  
Idiopathic Toe Walking ◽  
Clinical Gait Analysis ◽  
Toe Walking

Clinical gait analysis is the accepted “gold standard” for evaluating an individual’s walking pattern. However, in certain conditions such as idiopathic toe walking (ITW), the degree of voluntary control that a subject may elicit upon their walking pattern in a gait laboratory may not truly reflect their gait during daily activities. Therefore, a battery-powered, wireless data acquisition system was developed to record daily walking patterns to assist in the assessment of treatment outcomes in this patient population. The device was developed to be small (30×50×12 mm3), light-weight (15 g), easy to install, reliable, and consumed little power. It could be mounted across the laces of the shoe, while forces and walking activities were recorded to investigate the percentage of toe walking during the assessment. Laboratory tests were performed and preliminary clinical trials at a gait laboratory were done on six normal gait walkers. These volunteers also try to walk on their toes to simulate the toe walking at the gait laboratory. The system was able to track the gait pattern and determine the percentage of toe walking relative to normal gait. Three boys and one girl were diagnosed with ITW then participated into this study. A total of 4 sets thirty-three 10 min data sessions (5.5 h) were collected outside the laboratory. The results showed that the test subjects walked on their toes 70±4% of the total walking time, which was higher than that they performed 64±5% at the gait laboratory. This preliminary study shows promising results that the system should be able to use for clinical assessment and evaluation of children with ITW.

scholarly journals OrthoRehab: Development of a New Methodology for the Comparison Study Between Different Types of Ankle–Foot Orthoses in Foot Dysfunction

2021 ◽  
Vol 2 ◽  
Author(s):  
Cláudia Quaresma ◽  
Barbara Lopes ◽  
Jorge Jacinto ◽  
Tiago Robalo ◽  
Mariana Matos ◽  
...  
Keyword(s):  
Plantar Flexion ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Rehabilitation Medicine ◽  
Gait Pattern ◽  
Real Problem ◽  
Foot Orthoses ◽  
Support Tool ◽  
Ankle Foot Orthoses ◽  
User Friendly

Foot dysfunction is one of the most likely consequences of rheumatoid arthritis and stroke. It is characterized by severe changes in the gait pattern due to a significant increase in the plantar flexion. Some of these dysfunctions can be compensated by using an ankle–foot orthosis. However, the clinical decision about which orthosis best suits the patient creates a real problem for physicians/therapists.Purpose: The main goal of this paper is to present a quantitative support tool that can assist the physicians/therapists in deciding which orthosis is most suitable for each subject.Methodology: In order to achieve such goal, a platform named OrthoRehab was developed, and it was tested in three conditions: without any orthosis and with two different ankle–foot orthoses. The data were acquired in the Gait Laboratory of Rehabilitation Medicine Center of Alcoitão using a VICON NEXUS 1.8.5® motion capture system that allows the capturing of kinematic and kinetic data.Results: The results reveal that OrthoRehab is a user-friendly, easy to apply tool that analyzes very relevant data for the clinical staff.Conclusion: The developed decision support tool, OrthoRehab, offers a quantitative analysis and provides insight to which orthosis achieves the best performance in comparison with the patient's gait pattern with no orthosis.

scholarly journals Using Three-Dimensional Gait Data for Foot/Ankle Orthopaedic Surgery

2009 ◽  
Vol 3 (1) ◽  
pp. 89-95 ◽  
Author(s):  
Gwyneth de Vries ◽  
Kevin Roy ◽  
Victoria Chester
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Tendon Transfer ◽  
Treatment Effectiveness ◽  
Treatment Plan ◽  
Three Dimensional ◽  
Gait Pattern ◽  
Posterior Tibial Tendon ◽  
Post Surgery ◽  
Stiff Knee

We present the case of a forty year old male who sustained a torn carotid during strenuous physical activity. This was followed by a right hemispheric stroke due to a clot associated with the carotid. Upon recovery, the patient’s gait was characterized as hemiparetic with a stiff-knee pattern, a fixed flexion deformity of the toe flexors, and a hindfoot varus. Based on clinical exams and radiographs, the surgical treatment plan was established and consisted of correction of the forefoot deformities, possible hamstrings lengthening, and tendon transfer of the posterior tibial tendon to the dorsolateral foot. To aid in surgical planning, a three-dimensional gait analysis was conducted using a state-of-the-art motion capture system. Data from this analysis provided insight into the pathomechanics of the patient’s gait pattern. A forefoot driven hindfoot varus was evident from the presurgical data and the tendon transfer procedure was deemed unnecessary. A computer was used in the OR to provide surgeons with animations of the patient’s gait and graphical results as needed. A second gait analysis was conducted 6 weeks post surgery, shortly after cast removal. Post-surgical gait data showed improved foot segment orientation and position. Motion capture data provides clinicians with detailed information on the multisegment kinematics of foot motion during gait, before and during surgery. Further, treatment effectiveness can be evaluated by repeating gait analyses after recovery.

Sign in / Sign up

Export Citation Format

Share Document