The study aims to construct an inertial measuring system for the application of amputee subjects wearing a prosthesis. A new computation scheme to process inertial data by installing seven wireless inertial sensors on the lower limbs was implemented and validated by comparing it with an optical motion capture system. We applied this system to amputees to verify its performance for gait analysis. The gait parameters are evaluated to objectively assess the amputees\' prosthesis-wearing status. The Madgwick algorithm was used in the study to correct the angular velocity deviation using acceleration data and convert it to quaternion. Further, the zero-velocity update method was applied to reconstruct patients\' walking trajectories. The combination of computed walking trajectory with pelvic and lower limb joint motion enables sketching the details of motion via a stickman that helps visualize and animate the walk and gait of a test subject. Five participants with above-knee (n = 2) and below-knee (n = 3) amputations were recruited for gait analysis. Kinematic parameters were evaluated during a walking test to assess joint alignment and overall gait characteristics. Our findings support the feasibility of employing simple algorithms to achieve accurate and precise joint angle estimation and gait parameters based on wireless inertial sensor data.

Pedestrian navigation methods based on inertial sensors are commonly used to solve navigation and positioning problems when satellite signals are unavailable. To address the issue of heading angle errors accumulating over time in pedestrian navigation systems that rely solely on the Zero Velocity Update (ZUPT) algorithm, it is feasible to use the pedestrian\'s motion constraints to constrain the errors. Firstly, a human step length model is built using human kinematic data collected by the motion capture system. Secondly, we propose the bipedal constraint algorithm based on the established human step length model. Real field experiments demonstrate that, by introducing the bipedal constraint algorithm, the mean biped radial errors of the experiments are reduced by 68.16% and 50.61%, respectively. The experimental results show that the proposed algorithm effectively reduces the radial error of the navigation results and improves the accuracy of the navigation.

Cableways have been widely used in industrial areas, cities, and scenic spots due to their advantages, such as being a convenient mode of transportation, time-saving, labor-saving, and low cost, as well as offering environmental protection. To ensure the safe operation of a cableway, based on the characteristic that the velocity of the cableway bracket is approximately zero in a static deformation monitoring environment, a deformation monitoring method called zero velocity update (ZUPT)-based GNSS/IMU tightly coupled algorithm with the constraint of the Earth\'s rotation angular velocity was proposed. The proposed method can effectively solve the problem of a single GNSS being unable to output attitude, which is directly related to the status of wire ropes and cable cars. Meanwhile, ZUPT is used to restrain the Kalman filter\'s divergence when IMU is stationary. However, the improvements of ZUPT on attitude are not obvious, so the constraint of the Earth\'s rotation angular velocity was applied. The performance of the proposed method was evaluated through monitoring the cableway bracket of the Yimeng Mountain Tourism area in Shandong. Compared with the ZUPT-based GNSS/IMU tightly coupled algorithm (ZUPT-TC), the proposed method can further constrain the error accumulation of IMU while stationary and, therefore, it can provide reliable position and attitude information on cableway brackets.

Indoor positioning enables mobile machines to perform tasks (semi-)automatically, such as following an operator. However, the usefulness and safety of these applications depends on the reliability of the estimated operator localization. Thus, quantifying the accuracy of positioning at runtime is critical for the application in real-world industrial contexts. In this paper, we present a method that produces an estimate of the current positioning error for each user stride. To accomplish this, we construct a virtual stride vector from Ultra-Wideband (UWB) position measurements. The virtual vectors are then compared to stride vectors from a foot-mounted Inertial Measurement Unit (IMU). Using these independent measurements, we estimate the current reliability of the UWB measurements. Positioning errors are mitigated through loosely coupled filtering of both vector types. We evaluate our method in three environments, showing that it improves positioning accuracy, especially in challenging conditions with obstructed line of sight and sparse UWB infrastructure. Additionally, we demonstrate the mitigation of simulated spoofing attacks on UWB positioning. Our findings indicate that positioning quality can be judged at runtime by comparing user strides reconstructed from UWB and IMU measurements. Our method is independent of situation- or environment-specific parameter tuning, and as such represents a promising approach for detecting both known and unknown positioning error states.

Climbing stairs is a fundamental part of daily life, adding additional demands on the postural control system compared to level walking. Although real-world gait analysis studies likely contain stair ambulation sequences, algorithms dedicated to the analysis of such activities are still missing. Therefore, we propose a new gait analysis pipeline for foot-worn inertial sensors, which can segment, parametrize, and classify strides from continuous gait sequences that include level walking, stair ascending, and stair descending. For segmentation, an existing approach based on the hidden Markov model and a feature-based gait event detection were extended, reaching an average segmentation F1 score of 98.5% and gait event timing errors below ±10ms for all conditions. Stride types were classified with an accuracy of 98.2% using spatial features derived from a Kalman filter-based trajectory reconstruction. The evaluation was performed on a dataset of 20 healthy participants walking on three different staircases at different speeds. The entire pipeline was additionally validated end-to-end on an independent dataset of 13 Parkinson\'s disease patients. The presented work aims to extend real-world gait analysis by including stair ambulation parameters in order to gain new insights into mobility impairments that can be linked to clinically relevant conditions such as a patient\'s fall risk and disease state or progression.

Real-time kinematic (RTK) technique is widely used in modern society because of its high accuracy and real-time positioning. The appearance of Android P and the application of BCM47755 chipset make it possible to use single-frequency RTK and dual-frequency RTK on smartphones. The Xiaomi Mi 8 is the first dual-frequency Global Navigation Satellite System (GNSS) smartphone equipped with BCM47755 chipset. However, the performance of RTK in urban areas is much poorer compared with its performance under the open sky because the satellite signals can be blocked by the buildings and trees. RTK can\'t provide the positioning results in some specific areas such as the urban canyons and the crossings under an overpass. This paper combines RTK with an IMU-based pedestrian navigation algorithm. We utilize attitude and heading reference system (AHRS) algorithm and zero velocity update (ZUPT) algorithm based on micro electro mechanical systems (MEMS) inertial measurement unit (IMU) in smartphones to assist RTK for the sake of improving positioning performance in urban areas. Some tests are carried out to verify the performance of RTK on the Xiaomi Mi 8 and we respectively assess the performances of RTK with and without the assistance of an IMU-based pedestrian navigation algorithm in urban areas. Results on actual tests show RTK with the assistance of an IMU-based pedestrian navigation algorithm is more robust and adaptable to complex environments than that without it.

Researchers employ foot-mounted inertial measurement units (IMUs) to estimate the three-dimensional trajectory of the feet as well as a rich array of gait parameters. However, the accuracy of those estimates depends critically on the limitations of the accelerometers and angular velocity gyros embedded in the IMU design. In this study, we reveal the effects of accelerometer range, gyro range, and sampling frequency on gait parameters (e.g., distance traveled, stride length, and stride angle) estimated using the zero-velocity update (ZUPT) method. The novelty and contribution of this work are that it: (1) quantifies these effects at mean speeds commensurate with competitive distance running (up to 6.4 m/s); (2) identifies the root causes of inaccurate foot trajectory estimates obtained from the ZUPT method; and (3) offers important engineering recommendations for selecting accurate IMUs for studying human running. The results demonstrate that the accuracy of the estimated gait parameters generally degrades with increased mean running speed and with decreased accelerometer range, gyro range, and sampling frequency. In particular, the saturation of the accelerometer and/or gyro induced during running for some IMU designs may render those designs highly inaccurate for estimating gait parameters.

The zero velocity update (ZUPT) algorithm is an effective way to suppress the error growth for a foot-mounted pedestrian navigation system. To make ZUPT work properly, it is necessary to detect zero velocity intervals correctly. Existing zero velocity detection methods cannot provide good performance at high gait speeds or stair climbing. An adaptive zero velocity detection approach based on multi-sensor fusion is proposed in this paper. The measurements of an accelerometer, gyroscope and pressure sensor were employed to construct a zero-velocity detector. Then, the adaptive threshold was proposed to improve the accuracy of the detector under various motion modes. In addition, to eliminate the height drift, a stairs recognition method was developed to distinguish staircase movement from level walking. Detection performance was examined with experimental data collected at varying motion modes in real scenarios. The experimental results indicate that the proposed method can correctly detect zero velocity intervals under various motion modes.

From a research perspective, detailed knowledge about stride length (SL) is important for coaches, clinicians and researchers because together with stride rate it determines the speed of locomotion. Moreover, individual SL vectors represent the integrated output of different biomechanical determinants and as such provide valuable insight into the control of running gait. In recent years, several studies have tried to estimate SL using body-mounted inertial measurement units (IMUs) and have reported promising results. However, many studies have used systems based on multiple sensors or have only focused on estimating SL for walking. Here we test the concurrent validity of a single foot-mounted, 9-degree of freedom IMU to estimate SL for running. We employed a running-specific, Kalman filter based zero-velocity update (ZUPT) algorithm to calculate individual SL vectors with the IMU and compared the results to SLs that were simultaneously recorded by a 6-camera 3D motion capture system. The results showed that the analytical procedures were able to successfully identify all strides that were recorded by the camera system and that excellent levels of absolute agreement (ICC(3,1) = 0.955) existed between the two methods. The findings demonstrate that individual SL vectors can be accurately estimated with a single foot-mounted IMU when running in a controlled laboratory setting.

Zinc is an essential nutrient for bacterial growth. Because host cells can restrict pathogen access to zinc as an antimicrobial defense mechanism, intracellular pathogens such as Francisella must sense their environment and acquire zinc in response. In many bacteria, the conserved transcription factor Zur is a key regulator of zinc acquisition. To identify mechanisms of zinc uptake in Francisella novicida U112, transcriptome sequencing of wild-type and putative zur mutant bacteria was performed. Only three genes were confirmed as directly regulated by Zur and zinc limitation by quantitative reverse transcription-PCR. One of these genes, FTN_0879, is predicted to encode a protein with similarity to the zupT family of zinc transporters, which are not typically regulated by Zur. While a putative znuACB operon encoding a high-affinity zinc transporter was identified in U112, expression of this operon was not controlled by Zur or zinc concentration. Disruption of zupT but not znuA in U112 impaired growth under zinc limitation, suggesting that ZupT is the primary mechanism of zinc acquisition under these conditions. In the virulent Francisella tularensis subsp. tularensis Schu S4 strain, zupT is a pseudogene, and attempts to delete znuA were unsuccessful, suggesting that it is essential in this strain. A reverse TetR repression system was used to knock down the expression of znuA in Schu S4, revealing that znuA is required for growth under zinc limitation and contributes to intracellular growth within macrophages. Overall, this work identifies genes necessary for adaptation to zinc limitation and highlights nutritional differences between environmental and virulent Francisella strains.IMPORTANCEFrancisella tularensis is a tier 1 select agent with a high potential for lethality and no approved vaccine. A better understanding of Francisella virulence factors is required for the development of therapeutics. While acquisition of zinc has been shown to be required for the virulence of numerous intracellular pathogens, zinc uptake has not been characterized in Francisella This work characterizes the Zur regulon in F. novicida and identifies two transporters that contribute to bacterial growth under zinc limitation. In addition, these data identify differences in mechanisms of zinc uptake and tolerance to zinc limitation between F. tularensis and F. novicida, highlighting the role of znuA in the growth of Schu S4 under zinc limitation.