Step detection

Abstract: The article provides arguments in favor of an alternative approach that uses splines, which is equally justifiable on a theoretical basis, and which offers many practical advantages. To reassure the reader who may be afraid to enter new territory, it is emphasized that one is not losing anything because the traditional theory is retained as a particular case (i.e., a spline of infinite degree). The basic computational tools are also familiar to a signal processing audience (filters and recursive algorithms), even though their use in the present context is less conventional. The article also brings out the connection with the multiresolution theory of the wavelet transform. This article attempts to fulfil three goals. The first is to provide a tutorial on splines that is geared to a signal processing audience. The second is to gather all their important properties and provide an overview of the mathematical and computational tools available; i.e., a road map for the practitioner with references to the appropriate literature. The third goal is to give a review of the primary applications of splines in signal and image processing.

Abstract: Human localization is a very valuable information for smart environments. State-of-the-art Local Positioning Systems (LPS) require a complex sensor-network infrastructure to locate with enough accuracy and coverage. Alternatively, Inertial Measuring Units (IMU) can be used to estimate the movement of a person, by detecting steps, estimating stride lengths and the directions of motion; a methodology that is called Pedestrian Dead-Reckoning (PDR). In this paper, we use low-performance Micro-Electro-Mechanical (MEMS) inertial sensors attached to the foot of a person. This sensor has triaxial orthogonal accelerometers, gyroscopes and magnetometers. We describe, implement and compare several of the most relevant algorithms for step detection, stride length, heading and position estimation. The challenge using MEMS is to provide location estimations with enough accuracy and a limited drift. Several tests were conducted outdoors and indoors, and we found that the stride length estimation errors were about 1%. The positioning errors were almost always below 5% of the total travelled distance. The main source of positioning errors are the absolute orientation estimation.

Abstract: This textbook provides a comprehensive and current understanding of signal detection and estimation, including problems and solutions for each chapter. Signal detection plays an important role in fields such as radar, sonar, digital communications, image processing, and failure detection. The book explores both Gaussian detection and detection of Markov chains, presenting a unified treatment of coding and modulation topics. Addresses asymptotic of tests with the theory of large deviations, and robust detection. This textis appropriate for students of Electrical Engineering in graduate courses in Signal Detection and Estimation.

Abstract: Recently, several simple and cost-effective pedestrian navigation systems (PNS) have been introduced. These systems utilized accelerometers and gyros in order to determine step, stride and heading. The performance of the PNS depends on not only the accuracy of the sensors but also the measurement processing methods. In most PNS, a vertical impact is measured to detect a step. A step is counted when the measured vertical impact is larger than the given threshold. The numbers of steps are miscounted sometimes since the vertical impacts are not correctly measured due to inclination of the foot. Because the stride is not constant and changes with speed, the step length parameter must be determined continuously during the walk in order to get the accurate travelled distance. Also, to get the accurate heading, it is required to overcome drawbacks of low grade gyro and magnetic compass. This paper proposes new step, stride and heading determination methods for the pedestrian navigation system: A new reliable step determination method based on pattern recognition is proposed from the analysis of the vertical and horizontal acceleration of the foot during one step of the walking. A simple and robust stride determination method is also obtained by analyzing the relationship between stride, step period and acceleration. Furthermore, a new integration method of gyroscope and magnetic compass gives a reliable heading. The walking test is preformed using the implemented system consists of a 1-axis accelerometer, a 1-axis gyroscope, a magnetic compass and 16-bit microprocessor. The results of walking test confirmed the proposed method.