Integrity monitoring for undifferenced and uncombined PPP under the local environment

Integrity monitoring of precise point positioning (PPP) can provide tightly guaranteed absolute position error bounds for safety-critical applications. However, complex local environment makes PPP integrity monitoring much more challenging, such as urban canyons. Significant prone multipaths and low observation redundancy are main difficulties to the accuracy and the reliability of PPP. Therefore, we proposed a solution separation-based integrity monitoring algorithm, which is based on a single and dual frequency-mixed undifferenced and uncombined PPP model considering compensation for the multipath error distortion by Gaussian overbounding. Both the static and the kinematic data are utilized to test the proposed algorithm. The results show that the proposed algorithm can produce adequate protection level in horizontal and vertical directions. Furthermore, the proposed algorithm can obtain smoother protection level and positioning error under the dynamic local environment, and effectively suppress the misleading information.

Detection of a 100,000 M ⊙ black hole in M31's Most Massive Globular Cluster: A Tidally Stripped Nucleus

We investigate the presence of a central black hole (BH) in B023-G078, M31's most massive globular cluster. We present high-resolution, adaptive-optics assisted, integral-field spectroscopic kinematics from Gemini/NIFS that show a strong rotation (∼20 km s−1) and a velocity dispersion rise toward the center (37 km s−1). We combine the kinematic data with a mass model based on a two-component fit to HST ACS/HRC data of the cluster to estimate the mass of a putative BH. Our dynamical modeling suggests a >3σ detection of a BH component of 9.1 − 2.8 + 2.6 × 10 4 M ⊙ (1σ uncertainties). The inferred stellar mass of the cluster is 6.22 − 0.05 + 0.03 × 10 6 M ⊙ , consistent with previous estimates, thus the BH makes up 1.5% of its mass. We examine whether the observed kinematics are caused by a collection of stellar mass BHs by modeling an extended dark mass as a Plummer profile. The upper limit on the size scale of the extended mass is 0.56 pc (95% confidence), which does not rule out an extended mass. There is compelling evidence that B023-G078 is the tidally stripped nucleus of a galaxy with a stellar mass >109 M ⊙, including its high-mass, two-component luminosity profile, color, metallicity gradient, and spread in metallicity. Given the emerging evidence that the central BH occupation fraction of >109 M ⊙ galaxies is high, the most plausible interpretation of the kinematic data is that B023-G078 hosts a central BH. This makes it the strongest BH detection in a lower-mass (<107 M ⊙) stripped nucleus, and one of the few dynamically detected intermediate-mass BHs.

Real-Time Driving Behavior Identification Based on Multi-Source Data Fusion

Real-time driving behavior identification has a wide range of applications in monitoring driver states and predicting driving risks. In contrast to the traditional approaches that were mostly based on a single data source with poor identification capabilities, this paper innovatively integrates driver expression into driving behavior identification. First, 12-day online car-hailing driving data were collected in a non-intrusive manner. Then, with vehicle kinematic data and driver expression data as inputs, a stacked Long Short-Term Memory (S-LSTM) network was constructed to identify five kinds of driving behaviors, namely, lane keeping, acceleration, deceleration, turning, and lane changing. The Artificial Neural Network (ANN) and XGBoost algorithms were also employed as a comparison. Additionally, ten sliding time windows of different lengths were introduced to generate driving behavior identification samples. The results show that, using all sources of data yields better results than using the kinematic data only, with the average F1 value improved by 0.041, while the S-LSTM algorithm is better than the ANN and XGBoost algorithms. Furthermore, the optimal time window length is 3.5 s, with an average F1 of 0.877. This study provides an effective method for real-time driving behavior identification, and thereby supports the driving pattern analysis and Advanced Driving Assistance System.

Retrospective Robot-Measured Upper Limb Kinematic Data From Stroke Patients Are Novel Biomarkers

Background: The efficacy of upper-limb Robot-assisted Therapy (ulRT) in stroke subjects is well-established. The robot-measured kinematic data can assess the biomechanical changes induced by ulRT and the progress of patient over time. However, literature on the analysis of pre-treatment kinematic parameters as predictive biomarkers of upper limb recovery is limited.Objective: The aim of this study was to calculate pre-treatment kinematic parameters from point-to-point reaching movements in different directions and to identify biomarkers of upper-limb motor recovery in subacute stroke subjects after ulRT.Methods: An observational retrospective study was conducted on 66 subacute stroke subjects who underwent ulRT with an end-effector robot. Kinematic parameters were calculated from the robot-measured trajectories during movements in different directions. A Generalized Linear Model (GLM) was applied considering the post-treatment Upper Limb Motricity Index and the kinematic parameters (from demanding directions of movement) as dependent variables, and the pre-treatment kinematic parameters as independent variables.Results: A subset of kinematic parameters significantly predicted the motor impairment after ulRT: the accuracy in adduction and internal rotation movements of the shoulder was the major predictor of post-treatment Upper Limb Motricity Index. The post-treatment kinematic parameters of the most demanding directions of movement significantly depended on the ability to execute elbow flexion-extension and abduction and external rotation movements of the shoulder at baseline.Conclusions: The multidirectional analysis of robot-measured kinematic data predicts motor recovery in subacute stroke survivors and paves the way in identifying subjects who may benefit more from ulRT.

Real-Time Tracking of Human Neck Postures and Movements

Improper neck postures and movements are the major causes of human neck-related musculoskeletal disorders. To monitor, quantify, analyze, and detect the movements, remote and non-invasive based methods are being developed for prevention and rehabilitation. The purpose of this research is to provide a digital platform for analyzing the impact of human neck movements on the neck musculoskeletal system. The secondary objective is to design a rehabilitation monitoring system that brings accountability in the treatment prescribed, which is shown in the use-case model. To record neck movements effectively, a Smart Neckband integrated with the Inertial Measurement Unit (IMU) was designed. The initial task was to find a suitable position to locate the sensors embedded in the Smart Neckband. IMU-based real-world kinematic data were captured from eight research subjects and were used to extract kinetic data from the OpenSim simulation platform. A Random Forest algorithm was trained using the kinetic data to predict the neck movements. The results obtained correlated with the novel idea proposed in this paper of using the hyoid muscles to accurately detect neck postures and movements. The innovative approach of integrating kinematic data and kinetic data for analyzing neck postures and movements has been successfully demonstrated through the efficient application in a rehabilitation use case with about 95% accuracy. This research study presents a robust digital platform for the integration of kinematic and kinetic data that has enabled the design of a context-aware neckband for the support in the treatment of neck musculoskeletal disorders.

Motion Analysis Focusing on Rotational Movements of Professional Female Baseball Pitchers: Comparison with Male University Baseball Pitchers

Purpose: The purpose of this study was to compare pitching motion of the professional female baseball pitchers with the male university baseball pitchers focused on the pelvic and thoracic movements. Subjects and methods: The participants were 15 healthy professional female baseball pitchers (11 right-handers and 4 left-handers; age, 21.7 ± 3.2 years; height, 162.5 ± 5.1 cm; weight, 59.0 ± 6.6 kg) and 14 healthy male university baseball pitchers (12 right-handers and 2 left-handers; age, 19.9 ± 0.8 years; height, 176.4 ± 3.0 cm; body mass, 73.1 ± 3.0 kg). Throwing motion was captured by three-dimensional motion analysis system. Kinematic data of the lead hip, pelvis, thorax, and dominant shoulder were collected and the joint angle at maximum external rotation phase and ball release phase were compared. Results: The female baseball pitchers rotated pelvis and thorax more than the male at the maximum external rotation phase and ball release phase (p < 0.05). At the same, the pelvis and thorax of the female baseball pitchers were tilted significantly closer to horizontal plane than the male (p < 0.05). The pelvis and thorax of the male baseball pitchers was tilted to non-dominant lateral side. Conclusions: The results of this study indicate that the pelvic and thoracic movements of the professional female baseball pitchers was different from male university pitchers.

Increased Attentional Focus on Walking by Older Adults Limits Maximum Speed and Is Related to Dynamic Stability

<b><i>Background and Purpose:</i></b> Older adults with lower balance confidence demonstrate a reduced willingness to experience instability as the task of walking becomes more challenging (i.e., walking with a faster speed). However, the specific reason why is not known. The purpose of this study was to investigate the extent to which capacity of increasing walking speeds relates to the attentional requirements (i.e., automaticity) of walking. <b><i>Methods:</i></b> Sixteen young (31 ± 5.85 years) and 15 older participants (69 ± 3.04 years) began walking on a treadmill at 0.4 m/s, and speed was increased by 0.2 m/s until the participant either chose to stop or reached a speed of 2.0 m/s. Sixty steps were collected at steady-state speed for each walking trial. Kinematic data were collected, and the margin of stability in the anterior direction (MOS_AP) at heelstrike was quantified for each step. The timed up and go (TUG) and TUG dual (TUG_dual) task were performed, from which an automaticity index (TUG/TUG_dual × 100) was calculated. Older individuals were grouped based on whether they did or did not complete all walking speeds (i.e., completers [<i>n</i> = 9] or noncompleters [<i>n</i> = 6]). The fastest walking speed attempted (FSA), automaticity index, and MOS_AP were compared, and correlations were assessed between the FSA/MOS_AP and the automaticity index. <b><i>Results:</i></b> A significant difference was identified in an average MOS_AP at heelstrike between older completer and noncompleter groups (<i>p</i> &#x3c; 0.001). Further, older adults with lower automaticity index choose to stop walking at lower speeds (<i>p</i> = 0.001). The FSA was positively correlated with the automaticity index (ρ = 0.81, <i>p</i> &#x3c; 0.001). Finally, the average MOS_AP at FSA and the automaticity index were also negatively correlated (<i>r</i> = −0.85, <i>p</i> &#x3c; 0.001). <b><i>Conclusion:</i></b> Older adults with lower automaticity of walking choose to stop walking at speeds before they completed all walking speeds, which may relate with increased attentional demands required to maintain dynamic stability at higher walking speeds. Given that these were otherwise healthy adults, the combination of FSA and an automaticity of walking may help to identify individuals who should be considered for an assessment to identify walking problems.

The Influence of Mathematical Definitions on Patellar Kinematics Representations

A correlation between patellar kinematics and anterior knee pain is widely accepted. However, there is no consensus on how they are connected or what profile of patellar kinematics would minimize anterior knee pain. Nevertheless, answering this question by merging existing studies is further complicated by the variety of ways to describe patellar kinematics. Therefore, this study describes the most frequently used conventions for defining patellar kinematics, focusing on the rotations. The similarities and differences between the Cardan sequences and angles calculated by projecting axes are analyzed. Additionally, a tool is provided to enable the conversion of kinematic data between definitions in different studies. The choice of convention has a considerable impact on the absolute values and the clinical characteristics of the patello-femoral angles. In fact, the angles that result from using different mathematical conventions to describe a given patello-femoral rotation from our analyses differ up to a Root Mean Squared Error of 111.49° for patellar flexion, 55.72° for patellar spin and 35.39° for patellar tilt. To compare clinical kinematic patello-femoral results, every dataset must follow the same convention. Furthermore, researchers should be aware of the used convention’s implications to ensure reproducibility when interpreting and comparing such data.

Biomechanical Effects on Lower Extremities in Human-Robot Collaborative Agricultural Tasks

The present study pertains to a key aspect of human-robot collaborative systems which is usually underestimated, namely occupational health prolepsis. The aim of this investigation was to assess the biomechanical effects of manual symmetric load lifting related to a synergistic agricultural task that utilizes an unmanned ground vehicle to undertake the carriage of loads. Towards that goal, kinetic and kinematic data were collected from the lower extremities of thirteen experienced workers, by testing three different deposit heights (70, 80, 90 cm) corresponding to possible adjustments of the available agricultural robot. Moreover, the muscle activation levels of three lower extremity muscles and one trunk muscle were evaluated via a wireless electromyography system. Overall, the experimental findings revealed that the lower examined load height was associated with larger knee flexion moments and hip extension moments. Nevertheless, this height was related to lower activation mainly of the erectus spinae muscles. Finally, insignificant alterations were observed for the ankle joint as well as the activation levels of the other muscles. Consequently, a height equal to 90 cm is suggested, however, by avoiding extreme lumbar postures. The current results can be exploited for possible ergonomic interventions concerning the optimal deposit height of a robotic platform when a similar case is designed.

The Relationship of Trunk Muscle Activation and Core Stability: A Biomechanical Analysis of Pilates-Based Stabilization Exercise

Pilates is an effective exercise method for rehabilitating musculoskeletal disorders as its principles are based on the activation of local muscles. This study aimed to compare the subjects with and without Pilates experience to find out the effect of the experience on the core muscle activity and muscle co-contraction, and to examine the relationship between the core muscle activation level and the kinematic data. This study involved 32 subjects, including 16 experienced Pilates practitioners and 16 non-experienced subjects. The knee stretch on the reformer was performed in three different positions: flat back with a neutral pelvis, round back with posteriorly tilted pelvis (RPP), and extended back anteriorly tilted pelvis (EAP). The electromyography of the internal oblique (IO), rectus abdominis (RA), multifidus (MU), and iliocostalis lumborum (IL) muscles were measured, as well as kinematic data from a 3D motion analysis system. Compared to the non-experienced subjects, the experienced subjects activated the IO muscles more than the RA muscles, and the most significant difference was seen in the RPP position (p < 0.05). The experienced patients activated the MU muscles more often than the IL muscles, with the most significant difference observed in the RPP position and the least significant in the EAP position (p < 0.05). All kinematic data and muscle activity (IO, IO/RA ratio, MU/IL ratio) showed significant differences between the experienced and non-experienced subjects (p < 0.05). The subjects presented a moderate correlation between muscle activation and core stability. It was confirmed that the experienced Pilates practitioners activated the abdominal and low back core muscles effectively, and the stability of the pelvis and trunk were better than that of the non-experienced participants. In addition, the better the trunk stability was maintained, the larger and more accurate movement of the mobility segment was observed.