Detection of Movement Events of Long-Track Speed Skating Using Wearable Inertial Sensors

Inertial measurement units (IMUs) have been used increasingly to characterize long-track speed skating. We aimed to estimate the accuracy of IMUs for use in phase identification of long-track speed skating. Twelve healthy competitive athletes on a university long-track speed skating team participated in this study. Foot pressure, acceleration and knee joint angle were recorded during a 1000-m speed skating trial using the foot pressure system and IMUs. The foot contact and foot-off timing were identified using three methods (kinetic, acceleration and integrated detection) and the stance time was also calculated. Kinetic detection was used as the gold standard measure. Repeated analysis of variance, intra-class coefficients (ICCs) and Bland-Altman plots were used to estimate the extent of agreement between the detection methods. The stance time computed using the acceleration and integrated detection methods did not differ by more than 3.6% from the gold standard measure. The ICCs ranged between 0.657 and 0.927 for the acceleration detection method and 0.700 and 0.948 for the integrated detection method. The limits of agreement were between 90.1% and 96.1% for the average stance time. Phase identification using acceleration and integrated detection methods is valid for evaluating the kinematic characteristics during long-track speed skating.

Design and Experiments of a Portable Seabed Integrated Detection Sonar

The integrated observation of seabed topography, sediment geomorphology and sub-bottom profile information is very important for seabed remote sensing and mapping. To improve the efficiency of seabed detection and meet the needs of portable development of detection equipment, we developed a portable seabed feature integrated detection sonar (PSIDS) with whcih a single sonar device can simultaneously detect the above three types of seabed information. The underwater transducer is mainly composed of the following three components: a parametric emission array as the sound source, a high frequency receiving linear array for multibeam echo signal collection, and a two-dimensional vector hydrophone for receiving the low-frequency sediment echo signal. Field experiments were conducted to validate the performance of the PSIDS on 11–17 January 2018 in Jiaozhou Bay, China. (1) PSIDS could perform the functions of both multibeam sonar and sub-bottom profiler; (2) The synchronously and integrated measurement of various seabed information was achieved by alternately emitting multibeam echo-sounding and sub-bottom profiling signal using parametric source. The detection results proved the feasibility and practicability of PSIDS to achieve multiple seafloor characteristics. PSIDS provides a new idea for developing integrated seabed detection sonar. In terms of convenience and data fusion, it is a good option to use this equipment for integrated seabed detection.

An Integrated Detection Based on a Multi-Parameter Plasmonic Optical Fiber Sensor

In this paper, a multi-parameter integrated detection photonic crystal fiber (PCF) sensor based on surface plasmon resonance (SPR) is proposed for its application in detecting temperature, magnetic field, and refractive index. The air holes on both sides of the fiber core were coated with gold film and introduced to the temperature-sensitive medium (PDMS) and magnetic fluid (MF), detecting temperature and magnetic field, respectively. The graphene layer is also presented on the gold film of the D-type side polished surface to improve the sensor sensitivity. The sensor’s critical parameters’ influence on its performance is investigated using a mode solver based on the finite element method (FEM). Simulation results show when the samples refractive index (RI) detection is a range of 1.36~1.43, magnetic field detection is a range of 20~550 Oe, and the temperature detection is a range of 5~55 °C; the maximum sensor’s sensitivity obtains 76,000 nm/RIU, magnetic field intensity sensitivity produces 164.06 pm/Oe, and temperature sensitivity obtains −5001.31 pm/°C.

Algorithm for partially decentralized processing of a posteriori information in an integrated detection system

The integration of detectors can lead to an improvement in their performance. In this case, heterogeneous (radar, optoelectronic, radiotechnical) detectors can be combined. The task of integrating radar detectors is relevant for multi-positional radar stations. The construction of integrated identification systems can also be viewed as the task of combining detectors of their objects. There are three main options for combining detectors: centralized, partially decentralized, and fully decentralized. Centralized detection implements aggregation at the primary processing level, which provides potential characteristics, but it is difficult to implement such a combination in practice. Partially decentralized detection is implemented more simply, when preliminary detection decisions are made in the integrated detectors, which are then jointly processed and a final decision is formed. In joint processing of preliminary decisions, the probabilities of correct detection and false alarm of complexed detectors are usually used. The article presents an algorithm for partially decentralized combining of detectors using posterior probabilities of correct detection and false alarm. According to the results of computer simulation of the algorithm, characteristics were obtained that indicate an increase in the quality of detection relative to the best of the combined detectors. The use of the usual probabilities of correct detection and false alarm when combining does not guarantee such an increase – for certain characteristics of the detectors being combined, the effect of combining can be negative: the detection quality after combining will be lower relative to the best of the combined detectors.