Detecting Falls with Wearable Sensors Using Machine Learning Techniques

Cataloged from PDF version of article.Falls are a serious public health problem and possibly life threatening for people in fall risk groups. We develop an automated fall detection system with wearable motion sensor units fitted to the subjects' body at six different positions. Each unit comprises three tri-axial devices (accelerometer, gyroscope, and magnetometer/compass). Fourteen volunteers perform a standardized set of movements including 20 voluntary falls and 16 activities of daily living (ADLs), resulting in a large dataset with 2520 trials. To reduce the computational complexity of training and testing the classifiers, we focus on the raw data for each sensor in a 4 s time window around the point of peak total acceleration of the waist sensor, and then perform feature extraction and reduction. Most earlier studies on fall detection employ rule-based approaches that rely on simple thresholding of the sensor outputs. We successfully distinguish falls from ADLs using six machine learning techniques (classifiers): the k-nearest neighbor (k-NN) classifier, least squares method (LSM), support vector machines (SVM), Bayesian decision making (BDM), dynamic time warping (DTW), and artificial neural networks (ANNs). We compare the performance and the computational complexity of the classifiers and achieve the best results with the k-NN classifier and LSM, with sensitivity, specificity, and accuracy all above 99%. These classifiers also have acceptable computational requirements for training and testing. Our approach would be applicable in real-world scenarios where data records of indeterminate length, containing multiple activities in sequence, are recorded

The left sternalis muscle variation detected during mastectomy

The sternalis muscle variation is a well-known anatomical situation. It is present in 8.7% of women and 6.4% of men, although the incidence varies according to sex, race and ethnicity. During a left modified radical mastectomy operation on a 46-year-old female patient a sternalis muscle was detected on the pectoralis major muscle in the superficial fascia. It was in craniocaudal position and was parallel to the body of the sternum. The cylindrical muscle was approximately 8 cm in length and 2 cm in diameter. Such variations are considered to have their origin in embryological development. Awareness of muscular variations and their identification is important both for procedure through the proper dissection planes during breast surgery and in radiological examination and follow-up

Performance measures for object detection evaluation

Cataloged from PDF version of article.We propose a new procedure for quantitative evaluation of object detection algorithms. The procedure consists of a matching stage for finding correspondences between reference and output objects, an accuracy score that is sensitive to object shapes as well as boundary and fragmentation errors, and a ranking step for final ordering of the algorithms using multiple performance indicators. The procedure is illustrated on a building detection task where the resulting rankings are consistent with the visual inspection of the detection maps. (C) 2009 Elsevier B.V. All rights reserved

Geodesic motion in the space-time of a cosmic string

We study the geodesic equation in the space-time of an Abelian-Higgs string and discuss the motion of massless and massive test particles. The geodesics can be classified according to the particles energy, angular momentum and linear momentum along the string axis. We observe that bound orbits of massive particles are only possible if the Higgs boson mass is smaller than the gauge boson mass, while massless particles always move on escape orbits. Moreover, neither massive nor massless particles can ever reach the string axis for non-vanishing angular momentum. We also discuss the dependence of light deflection by a cosmic string as well as the perihelion shift of bound orbits of massive particles on the ratio between Higgs and gauge boson mass and the ratio between symmetry breaking scale and Planck mass, respectively.Comment: 20 pages including 14 figures; v2: references added, discussion on null geodesics extended, numerical results adde