1,651 research outputs found
Gait Analysis Using Wearable Sensors
Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a clinical tool applied in the rehabilitation and diagnosis of medical conditions and sport activities, gait analysis using wearable sensors shows great prospects. The current paper reviews available wearable sensors and ambulatory gait analysis methods based on the various wearable sensors. After an introduction of the gait phases, the principles and features of wearable sensors used in gait analysis are provided. The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography. Studies on the current methods are reviewed, and applications in sports, rehabilitation, and clinical diagnosis are summarized separately. With the development of sensor technology and the analysis method, gait analysis using wearable sensors is expected to play an increasingly important role in clinical applications
Development and validation of biomechanical models to quantify horse back forces at the walk in three horse breeds
Therapeutic horseback riding is a common component of physical therapy programs. Quantification of the horse back forces will provide vital information to match therapeutic riders with equine partners. To meet this medical need, a model to quantify the horse back forces from ground reaction forces was developed to test the hypothesis that the forces transferred to a static weight on the horse’s back can be predicted given horse breed and weight. Simultaneous, real time kinetic, kinematic, and back force data on a static weight were collected from 7 adult horses: 3 thoroughbreds, 3 quarter horses, and 1 paso fino. An integrated system consisting of a force platform, an active motion detection system and wireless force transducers were used. Data was collected from a minimum of four successful trials from all horses at a walk (1.3-2.0 m/s). Inverse dynamic analysis was used to calculate the fore and hind limb joint forces to the shoulder and hip, taking into consideration all 4 limbs’ motion per stride cycle. Virtual segments were created to model the equine back as a series of springs and dampers and joined to the limbs. Calculated forces from the inverse dynamics analysis were then input to the spring-damper model sequentially and at the same frequency as data collection. The energy absorption coefficients were derived by aligning the model output forces of the fore- and hind limb data with measured back forces. Horse back forces were simulated with different coefficients for each breed, and specifically for each horse. . Simulated results had a significant positive correlation (r = 0.81±0.04, p \u3c0.001) with forces measured directly on the back. The data from this investigation will contribute to mechanisms to predict forces experienced by the rider during horse motion to advance the science of therapeutic riding
Kinematic, kinetic and electromyographic response to customized foot orthoses in patients with tibialis posterior tenosynovitis, pes plano valgus and rheumatoid arthritis
Objective. To describe the effect of customized foot orthoses (FOs) on the kinematic, kinetic and EMG features in patients with RA, tibialis posterior (TP) tenosynovitis and associated pes plano valgus.<p></p>
Methods. Patients with RA and US-confirmed tenosynovitis of TP underwent gait analysis, including three-dimensional (3D) kinematics, kinetics, intramuscular EMG of TP and surface EMG of tibialis anterior, peroneus longus, soleus and medial gastrocnemius. Findings were compared between barefoot and shod with customized FO conditions.<p></p>
Results. Ten patients with RA with a median (range) disease duration of 3 (1–18) years were recruited. Moderate levels of foot pain and foot-related impairment and disability were present with moderately active disease states. Altered timing of the soleus (P = 0.05) and medial gastrocnemius (P = 0.02) and increased magnitude of tibialis anterior (P = 0.03) were noted when barefoot was compared with shod with FO. Trends were noted for reduced TP activity in the contact period (P = 0.09), but this did not achieve statistical significance. Differences in foot motion characteristics were recorded for peak rearfoot eversion (P = 0.01), peak rearfoot plantarflexion (P < 0.001) and peak forefoot abduction (P = 0.02) in the shod with FOs compared with barefoot conditions. No differences in kinetic variables were recorded.<p></p>
Conclusion. This study has demonstrated, for the first time, alterations in muscle activation profiles and foot motion characteristics in patients with RA, pes plano valgus and US-confirmed TP tenosynovitis in response to customized FOs. Complex adaptations were evident in this cohort and further work is required to determine whether these functional alterations lead to improvements in patient symptoms.<p></p>
Sensor-Based Adaptive Control and Optimization of Lower-Limb Prosthesis.
Recent developments in prosthetics have enabled the development of powered prosthetic ankles (PPA). The advent of such technologies drastically improved impaired gait by increasing balance and reducing metabolic energy consumption by providing net positive power. However, control challenges limit performance and feasibility of today’s devices. With addition of sensors and motors, PPA systems should continuously make control decisions and adapt the system by manipulating control parameters of the prostheses. There are multiple challenges in optimization and control of PPAs. A prominent challenge is the objective setup of the system and calibration parameters to fit each subject. Another is whether it is possible to detect changes in intention and terrain before prosthetic use and how the system should react and adapt to it.
In the first part of this study, a model for energy expenditure was proposed using electromyogram (EMG) signals from the residual lower-limbs PPA users. The proposed model was optimized to minimize energy expenditure. Optimization was performed using a modified Nelder-Mead approach with a Latin Hypercube sampling. Results of the proposed method were compared to expert values and it was shown to be a feasible alternative for tuning in a shorter time.
In the second part of the study, the control challenges regarding lack of adaptivity for PPAs was investigated. The current PPA system used is enhanced with impedance-controlled parameters that allow the system to provide different assistance. However, current systems are set to a fixed value and fail to acknowledge various terrain and intentions throughout the day. In this study, a pseudo-real-time adaptive control system was proposed to predict the changes in the gait and provide a smoother gait. The proposed control system used physiological, kinetic, and kinematic data and fused them to predict the change. The prediction was done using machine learning-based methods. Results of the study showed an accuracy of up to 89.7 percent for prediction of change for four different cases
Exploring the role of wearable technology in sport kinematics and kinetics: a systematic review
The aim of this review was to understand the use of wearable technology in sport in order to enhance performance and prevent injury. Understanding sports biomechanics is important for injury prevention and performance enhancement and is traditionally assessed using optical motion capture. However, such approaches are limited by capture volume restricting assessment to a laboratory environment, a factor that can be overcome by wearable technology. A systematic search was carried out across seven databases where wearable technology was employed to assess kinetic and kinematic variables in sport. Articles were excluded if they focused on sensor design and did not measure kinetic or kinematic variables or apply the technology on targeted participants. A total of 33 articles were included for full-text analysis where participants took part in a sport and performed dynamic movements relating to performance monitored by wearable technologies. Inertial measurement units, flex sensors and magnetic field and angular rate sensors were among the devices used in over 15 sports to quantify motion. Wearable technology usage is still in an exploratory phase, but there is potential for this technology to positively influence coaching practice and athletes’ technique
Master of Science
thesisAbnormal gait caused by stroke or other pathological reasons can greatly impact the life of an individual. Being able to measure and analyze that gait is often critical for rehabilitation. Motion analysis labs and many current methods of gait analysis are expensive and inaccessible to most individuals. The low cost, wearable, and wireless insole-based gait analysis system in this study provides kinetic measurements of gait by using low cost force sensitive resistors. This thesis describes the design and fabrication of two insoles and their evaluation with 10 control subjects and eight hemiplegic stroke subjects. The first insole used 32 force sensitive resistors and was used to determine the ideal locations of 12 sensors in the second insole. Linear regression was used on training data for each subject testing the second insole to determine ground reaction force, ankle dorsiflexion / plantarflexion moment, knee flexion / extension moment, and knee abduction / adduction moment. Comparison with data collected simultaneously from a clinical motion analysis laboratory demonstrated that the insole results for ground reaction force and ankle moment were highly correlated (all > 0.95) for all subjects, while the two knee moments were less strongly correlated (generally > 0.80). This provides a means of cost effective and efficient healthcare delivery of mobile gait analysis that can be used anywhere from large clinics to an individual's home. The two insoles also provide the means for further testing of force sensitive resistors in different applications
Quantifying Antalgic Gait Knee Function Using Inertial Sensor Technology
The use of body-fixed inertial sensors to analyze human movement may prove useful in the medical field. Improving orthopaedic device design, diagnosing musculoskeletal disorders, and rehabilitation assessment could all benefit from a mobile gait analysis system based on inertial sensors. More specifically, patients recovering from lower limb corrective surgeries tend to adjust gait patterns to accommodate pain, a condition referred to as antalgic gait. Currently there is no quantitative method available to assess recovery for this patient population during post-operative management. A comparison of the inertial sensor system with the camera-based industry standard has confirmed it as a viable method for lower limb motion analysis during normal gait. The inertial sensors consist of multiple accelerometers, gyroscopes and magnetometers used to obtain raw data, which is manipulated to calculate dynamic parameters. By comparing kinematic parameters between affected and unaffected limbs, it is possible to deduce a set of unique knee functionality ratios for recovering fracture patients. A control population was used to verify no significant difference (p \u3e 0.05) of seven kinematic parameters between limbs during normal gait. Parameters included peak knee flexion-extension angles at 15±5% and 75±5% gait cycle. These parameters were then analyzed in a group of patients recovering from lower limb fractures, using the unaffected limb as a control/reference. The goal of this project is to use inertial sensor technology to pinpoint specific kinematic parameters of the lower limb that are clinically appropriate in assessing knee function of lower limb fracture patients during the post-operative time span critical in normal gait recovery
An Embedded Gait Analysis System for CNS Injury Patients
Clinical evaluation of CNS injury patients before and after treatment is an essential step in gait rehabilitation. Medical care of gait disturbance for stroke patients is based on different treatments based on clinical and functional evaluations. Evaluation of gait aims at characterizing the motor performance to provide clinicians with information on the patient’s organizational or performance status and to allow them to consider the most appropriate treatment options. A 3D instrumented gait analysis system allows quantification of several parameters at each instant of walking but does not represent gait in daily life conditions. The absence of devices usable in daily life situation constitutes a lack pointed out by clinical practitioners and is at the origin of this work. In the following are described the design and implementation of a wireless embedded system for the collection of spatiotemporal parameters of pathological gait in everyday life. Algorithms estimate joint angles, step length, and gait events and automatically partition data into gait cycles. Experiments have been carried out to accurately evaluate the joint angles, the precision of sensor synchronization, the precision of gait event detection, and the robustness in the case of pathological walk. Comparisons with references given by the 3D instrumented gait analysis system are detailed
ASSESSING TENNIS PLAYER INTERACTIONS WITH TENNIS COURTS
Different types of tennis injury have been associated with play on different court surfaces and current knowledge of tennis player and court interactions is limited. This paper provides a brief overview of tennis injury incidence, player movements and the
biomechanics of slips. The discussion proposes a new direction for assessing tennis player-surface interactions and outlines current work. It is envisaged that current work will contribute to the understanding of tennis player-surface interactions and be of practical use in the future regulation of tennis courts
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