Accuracy assessment of Tri-plane B-mode ultrasound for non-invasive 3D kinematic analysis of knee joints

BACKGROUND Currently the clinical standard for measuring the motion of the bones in knee joints with sufficient precision involves implanting tantalum beads into the bones. These beads appear as high intensity features in radiographs and can be used for precise kinematic measurements. This procedure imposes a strong coupling between accuracy and invasiveness. In this paper, a tri-plane B-mode ultrasound (US) based non-invasive approach is proposed for use in kinematic analysis of knee joints in 3D space. METHODS The 3D analysis is performed using image processing procedures on the 2D US slices. The novelty of the proposed procedure and its applicability to the unconstrained 3D kinematic analysis of knee joints is outlined. An error analysis for establishing the method's feasibility is included for different artificial compositions of a knee joint phantom. Some in-vivo and in-vitro scans are presented to demonstrate that US scans reveal enough anatomical details, which further supports the experimental setup used using knee bone phantoms. RESULTS The error between the displacements measured by the registration of the US image slices and the true displacements of the respective slices measured using the precision mechanical stages on the experimental apparatus is evaluated for translation and rotation in two simulated environments. The mean and standard deviation of errors are shown in tabular form. This method provides an average measurement precision of less than 0.1 mm and 0.1 degrees, respectively. CONCLUSION In this paper, we have presented a novel non-invasive approach to measuring the motion of the bones in a knee using tri-plane B-mode ultrasound and image registration. In our study, the image registration method determines the position of bony landmarks relative to a B-mode ultrasound sensor array with sub-pixel accuracy. The advantages of our proposed system over previous techniques are that it is non-invasive, does not require the use of ionizing radiation and can be used conveniently if miniaturized.This work has been supported by School of Engineering & IT, UNSW Canberra, under Research Publication Fellowship

Accuracy assessment of Tri-plane B-mode ultrasound for non-invasive 3D kinematic analysis of knee joints

Background: Currently the clinical standard for measuring the motion of the bones in knee joints with sufficient precision involves implanting tantalum beads into the bones. These beads appear as high intensity features in radiographs and can be used for precise kinematic measurements. This procedure imposes a strong coupling between accuracy and invasiveness. In this paper, a tri-plane B-mode ultrasound (US) based non-invasive approach is proposed for use in kinematic analysis of knee joints in 3D space.Methods: The 3D analysis is performed using image processing procedures on the 2D US slices. The novelty of the proposed procedure and its applicability to the unconstrained 3D kinematic analysis of knee joints is outlined. An error analysis for establishing the method's feasibility is included for different artificial compositions of a knee joint phantom. Some in-vivo and in-vitro scans are presented to demonstrate that US scans reveal enough anatomical details, which further supports the experimental setup used using knee bone phantoms.Results: The error between the displacements measured by the registration of the US image slices and the true displacements of the respective slices measured using the precision mechanical stages on the experimental apparatus is evaluated for translation and rotation in two simulated environments. The mean and standard deviation of errors are shown in tabular form. This method provides an average measurement precision of less than 0.1 mm and 0.1 degrees, respectively.Conclusion: In this paper, we have presented a novel non-invasive approach to measuring the motion of the bones in a knee using tri-plane B-mode ultrasound and image registration. In our study, the image registration method determines the position of bony landmarks relative to a B-mode ultrasound sensor array with sub-pixel accuracy. The advantages of our proposed system over previous techniques are that it is non-invasive, does not require the use of ionizing radiation and can be used conveniently if miniaturized

Measuring skeletal kinematics with accelerometers on the skin surface

The most common motion analysis method uses cameras to track the position of markers on bodily surfaces over time. Although each species has a common skeletal frame to reference recorded motions, the soft tissue covering each is not rigid. Markers, therefore, experience motion relative to the bone and do not accurately portray underlying bone activity. This limits clinical use of motion studies and the understanding of joint motion. Use of MEMS accelerometers for removing soft tissue artifact, motion relative to the bone, from surface measurements and determining the position of the underlying bone was investigated. An animal limb was modeled experimentally as a double pendulum with soft tissue as sprung masses with motions perpendicular to the pendulums. Horizontal motion was cycled at the top joint with a 25 cm stroke. Position data obtained from the mass with a Codamotion™ system and integrated accelerometer data were combined in a Kalman filter to determine global position. Acceleration data in the sensor coordinate system determined tissue artifact and were compared to measurements using CODA markers on the mass and pendulum. Removing artifact from mass position estimated pendulum position over time. In determining mass position, integrated accelerometer data experienced drift, deviating from reasonable values and were determined impractical for Kalman filter input. This led to using only the CODA-determined position as the true position. Accelerometer artifacts resulted in mean differences with the CODA markers of less than 1 mm over 3 cm displacements excluding a mass with mechanical difficulties. The largest mean difference across four tests was 0.66 mm, which is 96.17 percent accurate. Mean differences between base positions collected from accelerometers and CODA markers were found for the global x and y directions. Maximum deviations were 1.64 mm and 4.45 mm, respectively, which are 99.56 and 99.63 percent accurate. Results show the effectiveness of this procedure in calculating the location of the bases of sprung masses in two dimensions. The basis of this research contributes to the determination of bone position over time that will increase the potential of understanding fundamental, rigid body and joint motions in a clinical setting using noninvasive methods

Design and Control of a Knee Exoskeleton for Assistance and Power Augmentation

Thanks to the technological advancements, assistive lower limb exoskeletons are moving from laboratory settings to daily life scenarios. This dissertation makes a contribution toward the development of assistive/power augmentation knee exoskeletons with an improved wearability, ergonomics and intuitive use. In particular, the design and the control of a novel knee exoskeleton system, the iT-Knee Bipedal System, is presented. It is composed by: a novel mechanism to transmit the assistance generated by the exoskeleton to the knee joint in a more ergonomic manner; a novel method that requires limited information to estimate online the torques experienced by the ankles, knees and hips of a person wearing the exoskeleton; a novel sensor system for shoes able to track the feet orientation and monitor their full contact wrench with the ground. In particular, the iT-Knee exoskeleton, the main component of the aforementioned system, is introduced. It is a novel six degree of freedom knee exoskeleton module with under-actuated kinematics, able to assist the flexion/extension motion of the knee while all the other joint\u2019s movements are accommodated. Thanks to its mechanism, the system: solves the problem of the alignment between the joint of the user and the exoskeleton; it automatically adjusts to different users\u2019 size; reduces the undesired forces and torques exchanged between the attachment points of its structure and the user\u2019s skin. From a control point of view, a novel approach to address difficulties arising in real life scenarios (i.e. noncyclic locomotion activity, unexpected terrain or unpredicted interactions with the surroundings) is presented. It is based on a method that estimates online the torques experienced by a person at his ankles, knees and hips with the major advantage that does not rely on any information of the user\u2019s upper body (i.e. pose, weight and center of mass location) or on any interaction of the user\u2019s upper body with the environment (i.e. payload handling or pushing and pulling task). This is achieved v by monitoring the full contact wrench of the subject with the ground and applying an inverse dynamic approach to the lower body segments. To track the full contact wrench between the subject\u2019s feet and the ground, a novel add on system for shoes has been developed. The iT-Shoe is adjustable to different user\u2019s size and accommodates the plantar flexion of the foot. It tracks the interactions and the orientation of the foot thanks to two 6axis Force/Torque sensors, developed in-house, with dedicated embedded MEMS IMUs placed at the toe and heel area. Different tasks and ground conditions were tested to validate and highlight the potentiality of the proposed knee exoskeleton system. The experimental results obtained and the feedback collected confirm the validity of the research conducted toward the design of more ergonomic and intuitive to use exoskeletons

Comparison Marker-Based and Markerless Motion Capture Systems in Gait Biomechanics During Running

Background: Markerless (ML) motion capture systems have recently become available for biomechanics applications. Evidence has indicated the potential feasibility of using an ML system to analyze lower extremity kinematics. However, no research examined ML systems’ estimation of the lower extremity joint moments and powers. Objectives: This study primarily aimed to compare lower extremity joint moments and powers estimated by marker-based (MB) and ML motion capture systems during treadmill running. The secondary purpose was to investigate if movement’s speed would affect the ML’s performance. Methods: Sixteen volunteers ran on a treadmill for 120 s for each trial at the speed of 2.24, 2.91, and 3.58 m/s, respectively. The kinematic data were simultaneously recorded by 8 infrared cameras and 8 high-resolution video cameras. The force data were recorded via an instrumented treadmill. Results: Compared to the MB system, the ML system estimated greater increased hip and knee joint kinetics with faster speeds during the swing phase. Additionally, increased greater ankle joint moments with speed estimated by the ML system were observed at the early swing phase. In contrast, the greater ankle joint powers occurred at the initial stance phase. Conclusions: These observations indicated that inconsistent segment pose estimations (mainly the center of mass estimated by ML was farther away from the relevant distal joint center) might lead to systematic differences in joint moments and powers estimated by MB and ML systems. Despite the promising applications of the ML system in clinical settings, systematic ML overestimation requires extra attention

Estimation of skeletal kinematics in freely moving rodents

Forming a complete picture of the relationship between neural activity and skeletal kinematics requires quantification of skeletal joint biomechanics during free behavior; however, without detailed knowledge of the underlying skeletal motion, inferring limb kinematics using surface-tracking approaches is difficult, especially for animals where the relationship between the surface and underlying skeleton changes during motion. Here we developed a videography-based method enabling detailed three-dimensional kinematic quantification of an anatomically defined skeleton in untethered freely behaving rats and mice. This skeleton-based model was constrained using anatomical principles and joint motion limits and provided skeletal pose estimates for a range of body sizes, even when limbs were occluded. Model-inferred limb positions and joint kinematics during gait and gap-crossing behaviors were verified by direct measurement of either limb placement or limb kinematics using inertial measurement units. Together we show that complex decision-making behaviors can be accurately reconstructed at the level of skeletal kinematics using our anatomically constrained model

Concept and Design of a Hand-held Mobile Robot System for Craniotomy

This work demonstrates a highly intuitive robot for Surgical Craniotomy Procedures. Utilising a wheeled hand-held robot, to navigate the Craniotomy Drill over a patient\u27s skull, the system does not remove the surgeons from the procedure, but supports them during this critical phase of the operation

Non-Intrusive Gait Recognition Employing Ultra Wideband Signal Detection

A self-regulating and non-contact impulse radio ultra wideband (IR-UWB) based 3D human gait analysis prototype has been modeled and developed with the help of supervised machine learning (SML) for this application for the first time. The work intends to provide a rewarding assistive biomedical application which would help doctors and clinicians monitor human gait trait and abnormalities with less human intervention in the fields of physiological examinations, physiotherapy, home assistance, rehabilitation success determination and health diagnostics, etc. The research comprises IR-UWB data gathered from a number of male and female participants in both anechoic chamber and multi-path environments. In total twenty four individuals have been recruited, where twenty individuals were said to have normal gait and four persons complained of knee pain that resulted in compensated spastic walking patterns. A 3D postural model of human movements has been created from the backscattering property of the radar pulses employing understanding of spherical trigonometry and vector fields. This subjective data (height of the body areas from the ground) of an individual have been recorded and implemented to extract the gait trait from associated biomechanical activity and differentiates the lower limb movement patterns from other body areas. Initially, a 2D postural model of human gait is presented from IR-UWB sensing phenomena employing spherical co-ordinate and trigonometry where only two dimensions such as, distance from radar and height of reflection have been determined. There are five pivotal gait parameters; step frequency, cadence, step length, walking speed, total covered distance, and body orientation which have all been measured employing radar principles and short term Fourier transformation (STFT). Subsequently, the proposed gait identification and parameter characterization has been analysed, tested and validated against popularly accepted smartphone applications with resulting variations of less than 5%. Subsequently, the spherical trigonometric model has been elevated to a 3D postural model where the prototype can determine width of motion, distance from radar, and height of reflection. Vector algebra has been incorporated with this 3D model to measure knee angles and hip angles from the extension and flexion of lower limbs to understand the gait behavior throughout the entire range of bipedal locomotion. Simultaneously, the Microsoft Kinect Xbox One has been employed during the experiment to assist in the validation process. The same vector mathematics have been implemented to the skeleton data obtained from Kinect to determine both the hip and knee angles. The outcomes have been compared by statistical graphical approach Bland and Altman (B&A) analysis. Further, the changes of knee angles obtained from the normal gaits have been used to train popular SMLs such as, k-nearest neighbour (kNN) and support vector machines (SVM). The trained model has subsequently been tested with the new data (knee angles extracted from both normal and abnormal gait) to assess the prediction ability of gait abnormality recognition. The outcomes have been validated through standard and wellknown statistical performance metrics with promising results found. The outcomes prove the acceptability of the proposed non-contact IR-UWB gait recognition to detect gait

Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview

A quantitative evaluation of kinetic parameters, the joint’s range of motion, heart rate, and breathing rate, can be employed in sports performance tracking and rehabilitation monitoring following injuries or surgical operations. However, many of the current detection systems are expensive and designed for clinical use, requiring the presence of a physician and medical staff to assist users in the device’s positioning and measurements. The goal of wearable sensors is to overcome the limitations of current devices, enabling the acquisition of a user’s vital signs directly from the body in an accurate and non–invasive way. In sports activities, wearable sensors allow athletes to monitor performance and body movements objectively, going beyond the coach’s subjective evaluation limits. The main goal of this review paper is to provide a comprehensive overview of wearable technologies and sensing systems to detect and monitor the physiological parameters of patients during post–operative rehabilitation and athletes’ training, and to present evidence that supports the efficacy of this technology for healthcare applications. First, a classification of the human physiological parameters acquired from the human body by sensors attached to sensitive skin locations or worn as a part of garments is introduced, carrying important feedback on the user’s health status. Then, a detailed description of the electromechanical transduction mechanisms allows a comparison of the technologies used in wearable applications to monitor sports and rehabilitation activities. This paves the way for an analysis of wearable technologies, providing a comprehensive comparison of the current state of the art of available sensors and systems. Comparative and statistical analyses are provided to point out useful insights for defining the best technologies and solutions for monitoring body movements. Lastly, the presented review is compared with similar ones reported in the literature to highlight its strengths and novelties

Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

This eBook provides a comprehensive treatise on modern biomechatronic systems centred around human applications. A particular emphasis is given to exoskeleton designs for assistance and training with advanced interfaces in human-machine interaction. Some of these designs are validated with experimental results which the reader will find very informative as building-blocks for designing such systems. This eBook will be ideally suited to those researching in biomechatronic area with bio-feedback applications or those who are involved in high-end research on manmachine interfaces. This may also serve as a textbook for biomechatronic design at post-graduate level