Real-time Motion Analysis Research Articles

New method of on-line quantification of regional wall motion with automated segmental motion analysis

We have recently developed an automated segmental motion analysis (A-SMA) system, based on an automatic “blood-tissue interface” detection technique, to provide real-time and on-line objective echocardiographic segmental wall motion analysis. To assess the feasibility of A-SMA in detecting regional left ventricular (LV) wall motion abnormalities, we performed 2-dimensional echocardiography with A-SMA in 13 healthy subjects, 22 patients with prior myocardial infarction (MI), and 9 with dilated cardiomyopathy (DCM). Midpapillary parasternal short-axis and apical 2- and 4-chamber views were obtained to clearly trace the blood-tissue interface. The LV cavity was then divided into 6 wedge-shaped segments by A-SMA. The area of each segment was calculated automatically throughout a cardiac cycle, and the area changes of each segment were displayed as bar graphs or time-area curves. The systolic fractional area change (FAC), peak ejection rate (PER), and filling rate (PFR) were also calculated with the use of A-SMA. In the control group, a uniform FAC was observed in real time among 6 segments in the short-axis view (60% ± 10% to 78% ± 9%), or among 5 segments in either the 2-chamber (59% ± 12% to 75% ± 16%) or 4-chamber view (58% ± 13% to 72% ± 12%). The variations of FAC, PER, and PFR were obviously decreased in infarct-related regions in the MI group and were globally decreased in the DCM group. We conclude that A-SMA is an objective and time-saving method for assessing regional wall motion abnormalities in real time. This method is a reliable new tool that provides on-line quantification of regional wall motion. (J Am Soc Echocardiogr 2001;14:892-901.)

New methods and algorithms for the accurate, real-time motion analysis of the left ventricle with MRI-tagging

Despite its tremendous advantages, magnetic resonance tagging remains unserviceable in clinical conditions due to very tedious image pre-processing tasks. We present here a novel algorithm, fully automatic, real-time and extremely accurate, to perform the tagging pattern extraction. We then address the problem of motion computation and analysis using a novel kinetic deformation class. Very accurate registrations enable to perform automatic ventricle segmentation propagation and a highly sharp motion analysis of the walls. Our work mainly focuses on the CSPAMM protocol, which is briefly recalled. Experiments on acquisitions from 15 healthy volunteers are shown.

Real-Time Motion Analysis with Linear Programming

A method to compute motion models in real time from point-to-line correspondences using linear programming is presented. Point-to-line correspondences are the most reliable measurements for image motion given the aperture effect, and it is shown how they can approximate other motion measurements as well. An error measure for image alignment using the L1 metric and based on point-to-line correspondences achieves results which are more robust than those for the commonly used L2 metric. The L1 error measure is minimized using linear programming. While estimators based on L1 are not robust in the breakdown point sense, experiments show that the proposed method is robust enough to allow accurate motion recovery over hundreds of consecutive frames. The L1 solution is compared to standard M-estimators and Least Median of Squares (LMedS) and it is shown that the L1 metric provides a reasonable and efficient compromise for various scenarios. The entire computation is performed in real-time on a PC without special hardware.

Robust real-time periodic motion detection, analysis, and applications

We describe new techniques to detect and analyze periodic motion as seen from both a static and a moving camera. By tracking objects of interest, we compute an object's self-similarity as it evolves in time. For periodic motion, the self-similarity measure is also periodic and we apply time-frequency analysis to detect and characterize the periodic motion. The periodicity is also analyzed robustly using the 2D lattice structures inherent in similarity matrices. A real-time system has been implemented to track and classify objects using periodicity. Examples of object classification (people, running dogs, vehicles), person counting, and nonstationary periodicity are provided.

Real-time three-dimensional motion analysis for patient positioning verification

Background and purpose: This paper describes the technology and methods involved in a system for automatically checking the position of patients at radiotherapy units. This is proposed for improving the accuracy in the irradiation geometrical set-up, which is a crucial factor in radiotherapy quality control. Materials and methods: The system is based on real-time opto-electronics and close-range photogrammetry and detects multiple passive markers placed on selected patient skin landmarks. Patient alignment and position monitoring is carried out by comparing the current three-dimensional positions of the markers with those of an initial reference position acquired during the simulation procedure and/or the first irradiation session. The system was used to measure the accuracy of conventional laser centering techniques for patient repositioning. Inaccuracies due to breathing and random movements were also taken into account. Professional technicians were asked to reposition three volunteer subjects carefully using a traditional laser centering procedure. Results: The results revealed significant repositioning errors even in highly controlled conditions, affecting particularly body areas relatively far from the skin reference points used for laser alignment. Conclusions: The outcome of the experimental application of this technology confirms its potential as a tool for patient repositioning and automatic detection of any errors caused by breathing or other unpredictable movements. The real-time feedback on the patient's position given by the system provides operators with appropriate visual indices and allows them to take suitable countermeasures in case of significant failures. In addition, the use of the system output for automatic position control is envisaged.

Real-Time Opto-Electronic Verification of Patient Position in Breast Cancer Radiotherapy

Objective: The clinical application of an opto-electronic system for real-tune three-dimensional (3D) control of patient position in breast cancer radiotherapy is described. The specific features of the motion analysis technology (shape recognition of passive markers) are detailed, and the outcomes of its clinical use for quantitative position control and immobility verification of the thoracic irradiation field during breast cancer treatment are reported.Materials and Methods: The position control system is based on the ELITEtM opto-electronic motion analyzer, which provides in real time the 3D coordinates of a set of passive markers (plastic hemispheres 3 mm in diameter) previously placed on selected landmarks on the patient's skin. The system-dedicated hardware performs marker recognition by means of 2D correlation of shape with a predefined marker modeling mask. This feature ensures a high accuracy, even with small marker dimensions, and successful analysis in a noisy environment (due to room light, reflexes, etc.). The patient repositioning control was based on a comparison between the current positions of the markers and a corresponding reference configuration. The resulting marker displacements were graphically displayed in real time for immediate control. This information was not provided to the operator as a repositioning tool. Instead, the kinematic data was stored for subsequent off-line analysis aimed at quantifying the different factors contributing to patient mis-positioning (initial repositioning errors, patient's breathing, and random movements) when conventional means for patient alignment (laser centering) and immobilization (casting techniques) are used.Results: Clinical application of the system revealed median 3D localization errors for the directly controlled anatomical landmarks of around 4.5 mm. This value is proposed to represent the intrinsic accuracy of conventional laser-centering techniques in breast cancer radiotherapy, including the effects of patient body deformations. When the positional inaccuracies introduced by patients' respiration were also considered, the extent of the resulting 3D mis-positioning of the control points increased to median values of up to 8 mm.Conclusions: The reported clinical trial confirms the significant role that real-time opto-electronic motion analysis based on passive markers can have in augmenting the accuracy of patient repositioning and immobility verification in the radiotherapy of a non-rigid body area while also accounting for physiological movements. Evaluation of the data collected during each irradiation session for five patients provided valuable information concerning the optimization of the efficacy of traditional methods for patient centering and immobilization.

Development of Vision-Based Vehicle Detection and Recognition System for Intelligent Vehicles

The business plan for the Intelligent Vehicles Initiative (IVI) from the U.S. Department of Transportation contains several candidate services that address collision warning and collision avoidance. Recently, a proactive crash mitigation system that would enhance the crash avoidance and survivability components of IVI has been proposed. An accurate object detection and recognition system is a prerequisite for the proactive crash mitigation system. A vision-based approach to the detection and recognition of vehicles, calculation of their motion parameters, and tracking of multiple vehicles by using a sequence of gray-scale images taken from a moving vehicle is presented. The vision-based system consists of four models: the object detection model, the object recognition model, the object information model, and the object tracking model. Object detection, recognition, and tracking are accomplished by combining the analysis of a single image frame with the analysis of consecutive image frames. In the analysis of the single image frame, the system detects the potential objects by using their shape features and recognizes the objects by using a neural network. Once the objects are recognized, they are tracked in the consecutive image frames by processing only the pertinent areas given by previous frames. The analysis of the single image frame is performed every 10 image frames. The information model will judge whether the objects are hazardous to the host vehicle by using two parameters: time to collision and its time derivative. Experimental results demonstrated a robust system in real-time vehicle recognition, vehicle tracking, and vehicle motion analysis over thousands of image frames.

Implementation and application of real-time motion analysis based on passive markers.

A method for real-time motion analysis based on passive markers is presented. An opto-electronic automatic motion analyser was used as hardware platform and the real-time operation was based on the interfacing between two levels of the system architecture. True real-time acquisition, processing and representation of two-dimensional and three-dimensional kinematics data were implemented through a newly conceived data acquisition procedure and high speed optimisation of the kinematics data processing. The method allows one to operate the motion analysis system in real-time; even when the data elaboration unit is required to perform other processing functions, the only consequence is a decrease in system sampling rate. The maximum number of processed and plotted markers in three dimensions at the highest system sampling rate (100 Hz) turned out to be suitable for the implementation of analytical and visual kinematics biofeedback. An example of the achievable level of complexity in terms of marker disposition model and graphic representation is reported by describing a demonstration of the real-time representation of human face movements. A clinical application of the method for patient position definition and control at radiotherapy units is presented.

RETIMAC: REal-TIme Motion Analysis Chip

Motion estimation is relevant for applications of both motion-compensated image sequence processing and dynamic scene analysis of computer vision. Different approaches and solutions have been proposed for these two applicative fields. In some cases, parallel architectures and dedicated chips for motion estimation in real-time have been developed. In this paper, a low-cost REal-TIme Motion Analysis Chip, RETIMAC, is presented, which is suitable for dynamic scene analysis in computer vision applications. This chip is capable of estimating optical flow fields in real-time, and has been especially developed for project OFCOMP (Optical Flow for COunting Moving People) DTM 45 ESPRIT III MEPI. It can be profitably used also for autonomous navigation, tracking, surveillance, counting moving objects, measuring velocity, etc., and for several computer vision applications which require as a first processing step the estimation of the apparent velocity of each pixel in the image plane (e.g., optical flow, velocity field). RETIMAC implements a gradient-based solution which has been demonstrated to be more reliable and precise with respect to several solutions proposed in the literature.

The use of flash photolysis for a high-resolution temporal and spatial analysis of bacterial chemotactic behaviour: CheZ is not always necessary for chemotaxis.

The purpose of this work was to develop a high-resolution analysis of behaviour as an assay of the physiological consequences of mutations in the che genes and also to examine the role of CheZ in chemotaxis. Recent advances in flash photolysis have made it possible to expose cells to an unstable chemical gradient created by a square-wave increase in attractant concentration. The response of individual cells can be tracked in the order of milliseconds using real-time motion analysis. The tumble frequency of wild-type Escherichia coli exposed to photoreleased aspartate falls very quickly to smooth-swimming levels, and the swimming speed of these cells rises. As a consequence of these behavioural changes, there is an increase in the number of bacteria present in the centre of the flashed area, that is the bacteria's response to the transient gradient generated by flash photolysis was to swim into the centre of the flash area. This allowed the rapid quantitative measurement of chemotaxis. Deletion of various che genes resulted in predictable changes in chemotactic behaviour. cheZ null mutants are non-chemotactic when measured by classical techniques but demonstrate a definite chemotactic response to photoreleased attractant.

Tracking vision system for real-time motion analysis

This paper describes a high-speed motion tracking system based on full-search correlation matching. Incorporating the Advanced Correlation Processor, which computes more than 500 motion vectors per frame, the system enables the detection and tracking of moving objects at a video rate. The system is implemented on a single board and can be mounted inside a PC. Thus, it is compact and economical, and is well suited for a wide variety of applications such as automatic surveillance, traffic monitoring and sports play analysis.

Does an ulnar nerve lesion influence the motion of the index finger?

Clawing of the ring and little fingers and "rolling" during prehension grip are well-known clinical phenomena of ulnar nerve lesions. In contrast to this the index and middle fingers seem to move normally. We compared the movement of right index fingers in healthy people with the right index fingers of people with an ulnar nerve lesion. The movement was measured using a three-dimensional real time motion analysis system based on ultrasound. The angles of the joints were plotted in a rectangular coordinate system. Statistical analysis of the numerical data showed no difference between the two groups. We trained a neural-network (Learning Vector Quantization) with the data of both groups. The network was able to distinguish between people with and without lesions of the ulnar nerve. We conclude that prehension grip of the index finger is also influenced by paralysis of the ulnar nerve.