Motion analysis of a robotic assisted surgery and microsurgery system - experimental verification

Motion analysis of a parallel robot assisted minimally invasive surgery/microsurgery system (PRAMiSS) and the control structures enabling it to achieve milli/micromanipulations under the constraint of moving through a fixed penetration point or so-called remote centre-of-motion (RCM) are presented in this article. Two control algorithms are proposed suitable for minimally invasive surgery (MIS) with submillimeter accuracy and for minimally invasive micro-surgery (MIMS) with submicrometer accuracy. The RCM constraint is performed without having any mechanical constraint. Control algorithms also apply orientation constraint preventing the tip to orient relative to the soft tissues due to the robot movements. Experiments were conducted to verify accuracy and effectiveness of the proposed control algorithms for MIS and MIMS operations. The experimental results demonstrate accuracy and performance of the proposed position control algorithms.

Resting toucher: a time and motion analysis of elite lawn bowls

Whilst numerous investigations have explored the physical demands placed upon competitive sportspeople from a wide array of sports little is known about the physical demands placed on lawn bowlers. The purpose of this study was to ascertain the movement activities of Australian representative singles and pairs players and to determine the frequency and duration of these activities. One match each of two male and two female players (one singles and one pairs player per gender) were videotaped during an international tournament. During playback of the videotaped matches (n = 4), a single observer coded the players’ activities into five distinct categories (waiting, walking forward, walking backward, jogging and bowling) using a computerised video editing system (Gamebreaker™ Digital Video Analysis System). Field calibration of players over 30m for forward motions and 15m for the backward motion was performed to allow for the estimation of total distance covered during the match. Heart rate was monitored during each match. The duration of a match was found to be (mean ± SD) 1hr 28 ± 15mins. The total distance covered during each match was 2093 ± 276m. The mean percentage of match time spent in each motion was: waiting, 61.8 ± 9.3%; walking forward, 22.3 ± 5.6%; walking backward, 2.0 ± 0.4%; jogging, 1.1 ± 0.5%; and bowling, 8.5 ± 4.2%. Average heart rate was found to be 57 ± 7% of age-predicted HRmax with a maximum of 78 ± 9% of age-predicted HRmax. The results of this study suggest that playing lawn bowls at an international level requires light-moderate intensity activity similar to that reported for golf.

Development of motion analysis protocols based on inertial sensors

The aim of this thesis was to describe the development of motion analysis protocols for applications on upper and lower limb extremities, by using inertial sensors-based systems. Inertial sensors-based systems are relatively recent. Knowledge and development of methods and algorithms for the use of such systems for clinical purposes is therefore limited if compared with stereophotogrammetry. However, their advantages in terms of low cost, portability, small size, are a valid reason to follow this direction. When developing motion analysis protocols based on inertial sensors, attention must be given to several aspects, like the accuracy of inertial sensors-based systems and their reliability. The need to develop specific algorithms/methods and software for using these systems for specific applications, is as much important as the development of motion analysis protocols based on them. For this reason, the goal of the 3-years research project described in this thesis was achieved first of all trying to correctly design the protocols based on inertial sensors, in terms of exploring and developing which features were suitable for the specific application of the protocols. The use of optoelectronic systems was necessary because they provided a gold standard and accurate measurement, which was used as a reference for the validation of the protocols based on inertial sensors. The protocols described in this thesis can be particularly helpful for rehabilitation centers in which the high cost of instrumentation or the limited working areas do not allow the use of stereophotogrammetry. Moreover, many applications requiring upper and lower limb motion analysis to be performed outside the laboratories will benefit from these protocols, for example performing gait analysis along the corridors. Out of the buildings, the condition of steady-state walking or the behavior of the prosthetic devices when encountering slopes or obstacles during walking can also be assessed. The application of inertial sensors on lower limb amputees presents conditions which are challenging for magnetometer-based systems, due to ferromagnetic material commonly adopted for the construction of idraulic components or motors. INAIL Prostheses Centre stimulated and, together with Xsens Technologies B.V. supported the development of additional methods for improving the accuracy of MTx in measuring the 3D kinematics for lower limb prostheses, with the results provided in this thesis. In the author’s opinion, this thesis and the motion analysis protocols based on inertial sensors here described, are a demonstration of how a strict collaboration between the industry, the clinical centers, the research laboratories, can improve the knowledge, exchange know-how, with the common goal to develop new application-oriented systems.

Upper Limb Portable Motion Analysis System Based on Inertial Technology for Neurorehabilitation Purposes

Here an inertial sensor-based monitoring system for measuring and analyzing upper limb movements is presented. The final goal is the integration of this motion-tracking device within a portable rehabilitation system for brain injury patients. A set of four inertial sensors mounted on a special garment worn by the patient provides the quaternions representing the patient upper limb’s orientation in space. A kinematic model is built to estimate 3D upper limb motion for accurate therapeutic evaluation. The human upper limb is represented as a kinematic chain of rigid bodies with three joints and six degrees of freedom. Validation of the system has been performed by co-registration of movements with a commercial optoelectronic tracking system. Successful results are shown that exhibit a high correlation among signals provided by both devices and obtained at the Institut Guttmann Neurorehabilitation Hospital.

Technical evaluation of a third generation optical pose tracker for motion analysis and image-guided surgery

Laparoscopic instrument tracking systems are an essential component in image-guided interventions and offer new possibilities to improve and automate objective assessment methods of surgical skills. In this study we present our system design to apply a third generation optical pose tracker (Micron- Tracker®) to laparoscopic practice. A technical evaluation of this design is performed in order to analyze its accuracy in computing the laparoscopic instrument tip position. Results show a stable fluctuation error over the entire analyzed workspace. The relative position errors are 1.776±1.675 mm, 1.817±1.762 mm, 1.854±1.740 mm, 2.455±2.164 mm, 2.545±2.496 mm, 2.764±2.342 mm, 2.512±2.493 mm for distances of 50, 100, 150, 200, 250, 300, and 350 mm, respectively. The accumulated distance error increases with the measured distance. The instrument inclination covered by the system is high, from 90 to 7.5 degrees. The system reports a low positional accuracy for the instrument tip.

Comparative study of two laparoscopic instrument tracker designs for motion analysis and image-guided surgery: a technical evaluation

Laparoscopic instrument tracking systems are a key element in image-guided interventions, which requires high accuracy to be used in a real surgical scenario. In addition, these systems are a suitable option for objective assessment of laparoscopic technical skills based on instrument motion analysis. This study presents a new approach that improves the accuracy of a previously presented system, which applies an optical pose tracking system to laparoscopic practice. A design enhancement of the artificial markers placed on the laparoscopic instrument as well as an improvement of the calibration process are presented as a means to achieve more accurate results. A technical evaluation has been performed in order to compare the accuracy between the previous design and the new approach. Results show a remarkable improvement in the fluctuation error throughout the measurement platform. Moreover, the accumulated distance error and the inclination error have been improved. The tilt range covered by the system is the same for both approaches, from 90º to 7.5º. The relative position error is better for the new approach mainly at close distances to the camera system

Correlation study between motion analysis of laparoscopic instruments and a suturing checklist

Purpose: To compare assessment capabilities of a motion analysis tool against a validated checklist during laparoscopic training.

Supervised classification of minimally invasive surgery psychomotor competence based on instruments motion analysis

Background Objective assessment of psychomotor skills has become an important challenge in the training of minimally invasive surgical (MIS) techniques. Currently, no gold standard defining surgical competence exists for classifying residents according to their surgical skills. Supervised classification has been proposed as a means for objectively establishing competence thresholds in psychomotor skills evaluation. This report presents a study comparing three classification methods for establishing their validity in a set of tasks for basic skills’ assessment. Methods Linear discriminant analysis (LDA), support vector machines (SVM), and adaptive neuro-fuzzy inference systems (ANFIS) were used. A total of 42 participants, divided into an experienced group (4 expert surgeons and 14 residents with >10 laparoscopic surgeries performed) and a nonexperienced group (16 students and 8 residents with <10 laparoscopic surgeries performed), performed three box trainer tasks validated for assessment of MIS psychomotor skills. Instrument movements were captured using the TrEndo tracking system, and nine motion analysis parameters (MAPs) were analyzed. The performance of the classifiers was measured by leave-one-out cross-validation using the scores obtained by the participants. Results The mean accuracy performances of the classifiers were 71 % (LDA), 78.2 % (SVM), and 71.7 % (ANFIS). No statistically significant differences in the performance were identified between the classifiers. Conclusions The three proposed classifiers showed good performance in the discrimination of skills, especially when information from all MAPs and tasks combined were considered. A correlation between the surgeons’ previous experience and their execution of the tasks could be ascertained from results. However, misclassifications across all the classifiers could imply the existence of other factors influencing psychomotor competence.

Time-motion analysis on Chinese male field hockey players

The aim of the study was to evaluate the match work-rate of Chinese field hockey players by analyzing the distance covered at different intensities pooled by specific positions during different periods of matches. Thirty-eight players from twenty-four male field hockey matches at the 11th Chinese National Games were filmed and analyzed.

Time-motion analysis on Chinese male field hockey players

The aim of the study was to evaluate the match work-rate of Chinese field hockey players by analyzing the distance covered at different intensities pooled by specific positions during different periods of matches. Thirty-eight players from twenty-four male field hockey matches at the 11th Chinese National Games were filmed and analyzed.mas

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Time-motion analysis in women’s team handball: importance of aerobic performance

Women’s handball is a sport, which has seen an accelerated development over the last decade. Data on movement patterns in combination with physiological demands are nearly nonexistent in the literature. The aim of this study was twofold: first, to analyze the horizontal movement pattern, including the sprint acceleration profiles, of individual female elite handball players and the corresponding heart rates (HRs) during a match and secondly to determine underlying correlations with individual aerobic performance. Players from one German First League team (n = 11) and the Norwegian National Team (n = 14) were studied during one match using the Sagit system for movement analysis and Polar HR monitoring for analysis of physiological demands. Mean HR during the match was 86 % of maximum HR (HRmax). With the exception of the goalkeepers (GKs, 78 % of HRmax), no position-specific differences could be detected. Total distance covered during the match was 4614 m (2066 m in GKs and 5251 m in field players (FPs)). Total distance consisted of 9.2 % sprinting, 26.7 % fast running, 28.8 % slow running, and 35.5 % walking. Mean velocity varied between 1.9 km/h (0.52 m/s) (GKs) and 4.2 km/h (1.17 m/s) (FPs, no position effect). Field players with a higher level of maximum oxygen uptake (V̇O2max) executed run activities with a higher velocity but comparable percentage of HRmax as compared to players with lower aerobic performance, independent of FP position. Acceleration profile depended on aerobic performance and the field player’s position. In conclusion, a high V̇O2max appears to be important in top-level international women’s handball. Sprint and endurance training should be conducted according to the specific demands of the player’s position.

High speed film motion analysis system. Final report.

Mode of access: Internet.

Time motion analysis of 2001 and 2002 super 12 rugby

The aim of this study was to quantify movements of Super 12 rugby players in competition because information on elite rugby players' movements is unavailable. Players were categorized into forwards [front (n = 16) and back row (n = 15)] and backs [inside (n = 9) and outside backs (n = 7)] and their movements analysed by video-based time motion analysis. Movements were classified as rest (standing, walking and jogging) and work (striding, sprinting, static exertion, jumping, lifting or tackling). The total time, number and duration of individual activities were assessed, with differences between groups evaluated using independent sample t-tests (unequal variances), while differences between halves were assessed with paired sample t-tests. Forwards had 7:47 min:s (95% confidence limits: 6:39 to 8:55 min:s, P