A critical evaluation of literature on robot path planning in dynamic environment

Robot Path Planning (RPP) in dynamic environments is a search problem based on the examination of collision-free paths in the presence of dynamic and static obstacles. Many techniques have been developed to solve this problem. Trapping in a local minima and maintaining a Real-Time performance are known as the two most important challenges that these techniques face to solve such problem. This study presents a comprehensive survey of the various techniques that have been proposed in this domain. As part of this survey, we include a classification of the approaches and identify their methods.

Genetic burden associated with varying degrees of disease severity in endometriosis

Endometriosis is primarily characterized by the presence of tissue resembling endometrium outside the uterine cavity and is usually diagnosed by laparoscopy. The most commonly used classification of disease, the revised American Fertility Society (rAFS) system to grade endometriosis into different stages based on disease severity (I to IV), has been questioned as it does not correlate well with underlying symptoms, posing issues in diagnosis and choice of treatment. Using two independent European genome-wide association (GWA) datasets and top-level classification of the endometriosis cases based on rAFS [minimal or mild (Stage A) and moderate-to-severe (Stage B) disease], we previously showed that Stage B endometriosis has greater contribution of common genetic variation to its aetiology than Stage A disease. Herein, we extend our previous analysis to four endometriosis stages [minimal (Stage I), mild (Stage II), moderate (Stage III) and severe (Stage IV) disease] based on the rAFS classification system and compared the genetic burden across stages. Our results indicate that genetic burden increases from minimal to severe endometriosis. For the minimal disease, genetic factors may contribute to a lesser extent than other disease categories. Mild and moderate endometriosis appeared genetically similar, making it difficult to tease them apart. Consistent with our previous reports, moderate and severe endometriosis showed greater genetic burden than minimal or mild disease. Overall, our results provide new insights into the genetic architecture of endometriosis and further investigation in larger samples may help to understand better the aetiology of varying degrees of endometriosis, enabling improved diagnostic and treatment modalities.

The validity of the GENEActiv wrist-worn accelerometer for measuring adult sedentary time in free living

OBJECTIVES Based on self-reported measures, sedentary time has been associated with chronic disease and mortality. This study examined the validity of the wrist-worn GENEactiv accelerometer for measuring sedentary time (i.e. sitting and lying) by posture classification, during waking hours in free living adults. DESIGN Fifty-seven participants (age=18-55 years 52% male) were recruited using convenience sampling from a large metropolitan Australian university. METHODS Participants wore a GENEActiv accelerometer on their non-dominant wrist and an activPAL device attached to their right thigh for 24-h (00:00 to 23:59:59). Pearson's Correlation Coefficient was used to examine the convergent validity of the GENEActiv and the activPAL for estimating total sedentary time during waking hours. Agreement was illustrated using Bland and Altman plots, and intra-individual agreement for posture was assessed with the Kappa statistic. RESULTS Estimates of average total sedentary time over 24-h were 623 (SD 103) min/day from the GENEActiv, and 626 (SD 123) min/day from the activPAL, with an Intraclass Correlation Coefficient of 0.80 (95% confidence intervals 0.68-0.88). Bland and Altman plots showed slight underestimation of mean total sedentary time for GENEActiv relative to activPAL (mean difference: -3.44min/day), with moderate limits of agreement (-144 to 137min/day). Mean Kappa for posture was 0.53 (SD 0.12), indicating moderate agreement for this sample at the individual level. CONCLUSIONS The estimation of sedentary time by posture classification of the wrist-worn GENEActiv accelerometer was comparable to the activPAL. The GENEActiv may provide an alternative, easy to wear device based measure for descriptive estimates of sedentary time in population samples

Combat sports analytics: Boxing punch classification using overhead depth imagery

In competitive combat sporting environments like boxing, the statistics on a boxer's performance, including the amount and type of punches thrown, provide a valuable source of data and feedback which is routinely used for coaching and performance improvement purposes. This paper presents a robust framework for the automatic classification of a boxer's punches. Overhead depth imagery is employed to alleviate challenges associated with occlusions, and robust body-part tracking is developed for the noisy time-of-flight sensors. Punch recognition is addressed through both a multi-class SVM and Random Forest classifiers. A coarse-to-fine hierarchical SVM classifier is presented based on prior knowledge of boxing punches. This framework has been applied to shadow boxing image sequences taken at the Australian Institute of Sport with 8 elite boxers. Results demonstrate the effectiveness of the proposed approach, with the hierarchical SVM classifier yielding a 96% accuracy, signifying its suitability for analysing athletes punches in boxing bouts.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Evaluating the specificity of community injury hospitalization data over time

This study identified the areas of poor specificity in national injury hospitalization data and the areas of improvement and deterioration in specificity over time. A descriptive analysis of ten years of national hospital discharge data for Australia from July 2002-June 2012 was performed. Proportions and percentage change of defined/undefined codes over time was examined. At the intent block level, accidents and assault were the most poorly defined with over 11% undefined in each block. The mechanism blocks for accidents showed a significant deterioration in specificity over time with up to 20% more undefined codes in some mechanisms. Place and activity were poorly defined at the broad block level (43% and 72% undefined respectively). Private hospitals and hospitals in very remote locations recorded the highest proportion of undefined codes. Those aged over 60 years and females had the higher proportion of undefined code usage. This study has identified significant, and worsening, deficiencies in the specificity of coded injury data in several areas. Focal attention is needed to improve the quality of injury data, especially on those identified in this study, to provide the evidence base needed to address the significant burden of injury in the Australian community.