iLDM: An Interoperable Graph-Based Local Dynamic Map

Local dynamic map (LDM) is a key component in the future of autonomous and connected vehicles. An LDM serves as a local database with the necessary tools to have a common reference system for both static data (i.e., map information) and dynamic data (vehicles, pedestrians, etc.). The LDM should have a common and well-defined input system in order to be interoperable across multiple data sources such as sensor detections or V2X communications. In this work, we present an interoperable graph-based LDM (iLDM) using Neo4j as our database engine and OpenLABEL as a common data format. An analysis on data insertion and querying time to the iLDM is reported, including a vehicle discovery service function in order to test the capabilities of our work and a comparative analysis with other LDM implementations showing that our proposed iLDM outperformed in several relevant features, furthering its practical utilisation in advanced driver assistance system development.

Validity and Sensitivity of an Inertial Measurement Unit-Driven Biomechanical Model of Motor Variability for Gait

Motor variability in gait is frequently linked to fall risk, yet field-based biomechanical joint evaluations are scarce. We evaluated the validity and sensitivity of an inertial measurement unit (IMU)-driven biomechanical model of joint angle variability for gait. Fourteen healthy young adults completed seven-minute trials of treadmill gait at several speeds and arm swing amplitudes. Trunk, pelvis, and lower-limb joint kinematics were estimated by IMU- and optoelectronic-based models using OpenSim. We calculated range of motion (ROM), magnitude of variability (meanSD), local dynamic stability (λmax), persistence of ROM fluctuations (DFAα), and regularity (SaEn) of each angle over 200 continuous strides, and evaluated model accuracy (RMSD: root mean square difference), consistency (ICC2,1: intraclass correlation), biases, limits of agreement, and sensitivity to within-participant gait responses (effects of speed and swing). RMSDs of joint angles were 1.7–7.5° (pooled mean of 4.8°), excluding ankle inversion. ICCs were mostly good to excellent in the primary plane of motion for ROM and in all planes for meanSD and λmax, but were poor to moderate for DFAα and SaEn. Modelled speed and swing responses for ROM, meanSD, and λmax were similar. Results suggest that the IMU-driven model is valid and sensitive for field-based assessments of joint angle time series, ROM in the primary plane of motion, magnitude of variability, and local dynamic stability.

Local Dynamic Updating Method of Orebody Model Based on Mesh Reconstruction and Mesh Deformation

In this paper, to update the orebody model based on the given interpreted geological information, we present a local dynamic updating method of the orebody model that allows the interactive construction of the constraint deformation conditions and the dynamic updating of the mesh model. The rules for constructing deformation constraints based on the control polylines are discussed. Because only part of the model is updated, the updated mesh is effective and the overall quality is satisfactory. Our main contribution is that we propose a local dynamic updating method for the orebody model based on mesh reconstruction and mesh deformation. This method can automatically update a given 3D orebody model based on a set of unordered geological interpretation lines. Moreover, we implement a deformation neighborhood region search method based on the specified ring radius and a local constrained mesh deformation algorithm for the orebody model. Finally, we test the method and show the model update results with real geological datasets, which proves that this method is effective for the local updating of orebody models.

Aberrant global and local dynamic properties in schizophrenia with instantaneous phase method based on Hilbert transform

Background Emerging functional imaging studies suggest that schizophrenia is associated with aberrant spatiotemporal interaction which may result in aberrant global and local dynamic properties. Methods We investigated the dynamic functional connectivity (FC) by using instantaneous phase method based on Hilbert transform to detect abnormal spatiotemporal interaction in schizophrenia. Based on resting-state functional magnetic resonance imaging, two independent datasets were included, with 114 subjects from COBRE [51 schizophrenia patients (SZ) and 63 healthy controls (HCs)] and 96 from OpenfMRI (36 SZ and 60 HCs). Phase differences and instantaneous coupling matrices were firstly calculated at all time points by extracting instantaneous parameters. Global [global synchrony and intertemporal closeness (ITC)] and local dynamic features [strength of FC (sFC) and variability of FC (vFC)] were compared between two groups. Support vector machine (SVM) was used to estimate the ability to discriminate two groups by using all aberrant features. Results We found SZ had lower global synchrony and ITC than HCs on both datasets. Furthermore, SZ had a significant decrease in sFC but an increase in vFC, which were mainly located at prefrontal cortex, anterior cingulate cortex, temporal cortex and visual cortex or temporal cortex and hippocampus, forming significant dynamic subnetworks. SVM analysis revealed a high degree of balanced accuracy (85.75%) on the basis of all aberrant dynamic features. Conclusions SZ has worse overall spatiotemporal stability and extensive FC subnetwork lesions compared to HCs, which to some extent elucidates the pathophysiological mechanism of schizophrenia, providing insight into time-variation properties of patients with other mental illnesses.

Validity and sensitivity of an inertial measurement unit-driven biomechanical model of motor variability for gait

Motor variability in gait is frequently linked to fall risk, yet field-based biomechanical joint evaluations are scarce. We evaluated the validity and sensitivity of an inertial measurement unit (IMU)-driven biomechanical model of joint angle variability for gait. Fourteen healthy young adults completed seven-minute trials of treadmill gait at several speeds and arm swing amplitudes. Joint kinematics were estimated by IMU- and optoelectronic-based models using OpenSim. We calculated range of motion (ROM), magnitude of variability (meanSD), local dynamic stability (λmax), persistence of ROM fluctuations (DFAα), and regularity (SaEn) of each angle over 200 continuous strides, and evaluated model accuracy (e.g., RMSD: root mean square difference), consistency (ICC2,1: intraclass correlation), biases, limits of agreement, and sensitivity to within-participant gait responses (effects of Speed and Swing). RMSDs of joint angles were 1.7–7.5° (pooled mean of 4.8°), excluding ankle inversion. ICCs were mostly good–excellent in the primary plane of motion for ROM and in all planes for meanSD and λmax, but were poor–moderate for DFAα and SaEn. Modeled Speed and Swing responses for ROM, meanSD, and λmax were similar. Results suggest that the IMU-driven model is valid and sensitive for field-based assessments of joint angles and several motor variability features.