A Novel Two-Axis Differential Resonant Accelerometer Based on Graphene with Transmission Beams

In this paper, a novel two-axis differential resonant accelerometer based on graphene with transmission beams is presented. This accelerometer can not only reduce the cross sensitivity, but also overcome the influence of gravity, realizing fast and accurate measurement of the direction and magnitude of acceleration on the horizontal plane. The simulation results show that the critical buckling acceleration is 460 g, the linear range is 0–89 g, while the differential sensitivity is 50,919 Hz/g, which is generally higher than that of the resonant accelerometer reported previously. Thus, the accelerometer belongs to the ultra-high sensitivity accelerometer. In addition, increasing the length and tension of graphene can obviously increase the critical linear acceleration and critical buckling acceleration with the decreasing sensitivity of the accelerometer. Additionally, the size change of the force transfer structure can significantly affect the detection performance. As the etching accuracy reaches the order of 100 nm, the critical buckling acceleration can reach up to 5 × 104 g, with a sensitivity of 250 Hz/g. To sum up, a feasible design of a biaxial graphene resonant accelerometer is proposed in this work, which provides a theoretical reference for the fabrication of a graphene accelerometer with high precision and stability.

Quantification of Head Acceleration Events in Rugby League: An Instrumented Mouthguard and Video Analysis Pilot Study

Instrumented mouthguards (iMG) were used to collect head acceleration events (HAE) in men’s professional rugby league matches. Peak linear acceleration (PLA), peak angular acceleration (PAA) and peak change in angular velocity (ΔPAV) were collected using custom-fit iMG set with a 5 g single iMG-axis recording threshold. iMG were fitted to ten male Super League players for thirty-one player matches. Video analysis was conducted on HAE to identify the contact event; impacted player; tackle stage and head loading type. A total of 1622 video-verified HAE were recorded. Approximately three-quarters of HAE (75.7%) occurred below 10 g. Most (98.2%) HAE occurred during tackles (59.3% to tackler; 40.7% to ball carrier) and the initial collision stage of the tackle (43.9%). The initial collision stage resulted in significantly greater PAA and ΔPAV than secondary contact and play the ball tackle stages (p < 0.001). Indirect HAE accounted for 29.8% of HAE and resulted in significantly greater ΔPAV (p < 0.001) than direct HAE, but significantly lower PLA (p < 0.001). Almost all HAE were sustained in the tackle, with the majority occurring during the initial collision stage, making it an area of focus for the development of player protection strategies for both ball carriers and tacklers. League-wide and community-level implementation of iMG could enable a greater understanding of head acceleration exposure between playing positions, cohorts, and levels of play.

Two Notes on the Theoretical Physics of ATP Synthase

ATP Synthase is an essential molecule in cell and molecular biology. It is responsible for the production of ATP during cellular respiration, a molecule that provides the energy required to drive a number of cellular processes. In this paper, I explore the rotational physics of ATP Synthase&rsquo;s rotor, a part of the protein that spins during the production of ATP. Firstly, I discuss some elementary rotational kinematics of the rotor. I then derive two alternate formulations for the total linear acceleration of the rotor. Finally, I derive formulas for the moment of inertia, angular momentum, net torque, and kinetic energy of the rotor. Through this, I hope to provide a theoretical and mathematical insight into the mechanics of ATP Synthase during the production of ATP.

Two Notes on the Theoretical Physics of ATP Synthase

ATP Synthase is an essential molecule in cell and molecular biology. It is responsible for the production of ATP during cellular respiration, a molecule that provides the energy required to drive a number of cellular processes. In this paper, I explore the rotational physics of ATP Synthase’s rotor, a part of the protein that spins during the production of ATP. Firstly, I discuss some elementary rotational kinematics of the rotor. I then derive two alternate formulations for the total linear acceleration of the rotor. Finally, I derive formulas for the moment of inertia, angular momentum, net torque, and kinetic energy of the rotor. Through this, I hope to provide a theoretical and mathematical insight into the mechanics of ATP Synthase during the production of ATP.

Influence of the Backward Fall Technique on the Sagittal Linear Acceleration of the Head During a Fall

(1) Background: This research aimed to determine the effect of the backward fall technique on the sagittal linear acceleration of the head in students training in different sports. (2) Methods: The study involved 41 students divided into two study groups. Group A included 19 students training in martial arts who practised falls with side aligning of the body. Group B included 22 handball players who practised falls performed in a way similar to a gymnastic backward roll. A rotating training simulator (RTS) was used to force falls, and Wiva ® Science apparatus was used to assess acceleration. (3) Results: Significant changes in head acceleration were only obtained between immediate fall tests (IFTs) and forced fall tests (FFTs) in group B. Significant differences were noted between groups for the IFT and FFT. Greater changes in head acceleration were noted in group B. (4) Conclusions: Smaller changes in head acceleration in group A students indicate a lower susceptibility to head, pelvic and cervical spine injuries in falls performed backward with side aligning of the body. This technique in group A limited the differences in head acceleration between IFTs and FFTs. Negative acceleration values obtained in group B confirmed that the head may suffer a moment of force, tilting it backwards, but then forward when the buttocks hit the ground.

Stride segmentation of inertial sensor data using statistical methods for different walking activities

Human gait data can be collected using inertial measurement units (IMUs). An IMU is an electronic device that uses an accelerometer and gyroscope to capture three-axial linear acceleration and three-axial angular velocity. The data so collected are time series in nature. The major challenge associated with these data is the segmentation of signal samples into stride-specific information, that is, individual gait cycles. One empirical approach for stride segmentation is based on timestamps. However, timestamping is a manual technique, and it requires a timing device and a fixed laboratory set-up which usually restricts its applicability outside of the laboratory. In this study, we have proposed an automatic technique for stride segmentation of accelerometry data for three different walking activities. The autocorrelation function (ACF) is utilized for the identification of stride boundaries. Identification and extraction of stride-specific data are done by devising a concept of tuning parameter ( $t_{p}$ ) which is based on minimum standard deviation ( $\sigma$ ). Rigorous experimentation is done on human activities and postural transition and Osaka University – Institute of Scientific and Industrial Research gait inertial sensor datasets. Obtained mean stride duration for level walking, walking upstairs, and walking downstairs is 1.1, 1.19, and 1.02 s with 95% confidence interval [1.08, 1.12], [1.15, 1.22], and [0.97, 1.07], respectively, which is on par with standard findings reported in the literature. Limitations of accelerometry and ACF are also discussed. stride segmentation; human activity recognition; accelerometry; gait parameter estimation; gait cycle; inertial measurement unit; autocorrelation function; wearable sensors; IoT; edge computing; tinyML.

Laboratory assessment of a head impact sensor for youth soccer ball heading impacts using an anthropomorphic test device

Recent advances in technology have enabled the development of instrumented equipment, which estimate the head impact kinematics of athletes in vivo. One such headband-mounted impact sensor is the SIM-G (Triax Technologies, Norwalk, CT, USA), which has been previously used to investigate the biomechanics of soccer heading by human subjects. Previous studies have evaluated the accuracy of the SIM-G for pure rotation and pendulum, impulse hammer and drop rig impacts. The current study used a soccer ball heading model to evaluate the accuracy of the SIM-G. A soccer ball was projected at the head of an anthropomorphic test device (ATD) representing a 10-year-old to replicate the heading maneuver at various impact sites, angles and speeds previously identified in youth soccer. Linear regression revealed that the SIM-G sensor overestimated the peak angular velocity and linear acceleration recorded by the ATD headform by approximately 44% and 105%, respectively. Tests in which the ball directly contacted the SIM-G sensor resulted in the largest peak linear accelerations. Glancing impacts were significantly associated with a decrease in percentage error of the SIM-G sensor peak angular velocity data relative to the ATD reference data. While it may not demonstrate accuracy in estimating the magnitudes of head impacts, the SIM-G remains a useful tool to provide estimates of head impact exposure for soccer players.

The range of bicycle helmet performance at real world impact locations

In the United States, all bicycle helmets must comply with the standard created by the Consumer Product Safety Commission (CPSC). In this standard, bike helmets are only required to by tested above an established test line. Unregulated helmet performance below the test line could pose an increased risk of head injury to riders. This study quantified the impact locations of damaged bike helmets from real-world accidents and tested the most commonly impacted locations under CPSC bike helmet testing protocol. Ninety-five real-world impact locations were quantified. The most common impact locations were side-middle (31.6%), rear boss-rim (13.7%), front boss-rim (9.5%), front boss-middle (9.5%), and rear boss-middle (9.5%). The side-middle, rear boss-rim, and front boss (front boss-middle and front boss-rim regions combined) were used for testing. Two of the most commonly impacted regions were below the test line (front boss-rim and rear boss-rim). Twelve purchased helmet models were tested under CPSC protocol at each location for a total of 36 impacts. An ANOVA test showed that impact location had a strong influence on the variance of peak linear acceleration (PLA) ( p = 0.002). A Tukey HSD post hoc test determined that PLA at the side-middle (214.9 ± 20.8 g) and front boss (228.0 ± 39.6 g) locations were significantly higher than the PLA at the rear boss-rim (191.5 ± 24.2 g) location. The highest recorded PLA (318.8 g) was at the front boss-rim region. This was the only test that exceeded the 300 g threshold. This study presented a method for quantifying real-world impact locations of damaged bike helmets. Higher variance in helmet performance was found at the regions on or below the test line than at the region above the test line.

Detecting Coronary Artery Disease Using Rest Seismocardiography and Gyrocardiography

In this study, we present a non-invasive solution to identify patients with coronary artery disease (CAD) defined as ⩾50% stenosis in at least one coronary artery. The solution is based on the analysis of linear acceleration (seismocardiogram, SCG) and angular velocity (gyrocardiogram, GCG) of the heart recorded in the x, y, and z directional axes from an accelerometer/gyroscope sensor mounted on the sternum. The database was collected from 310 individuals through a multicenter study. The time-frequency features extracted from each SCG and GCG data channel were fed to a one-dimensional Convolutional Neural Network (1D CNN) to train six separate classifiers. The results from different classifiers were later fused to estimate the CAD risk for each participant. The predicted CAD risk was validated against related results from angiography. The SCG z and SCG y classifiers showed better performance relative to the other models (p &lt; 0.05) with the area under the curve (AUC) of 91%. The sensitivity range for CAD detection was 92–94% for the SCG models and 73–87% for the GCG models. Based on our findings, the SCG models achieved better performance in predicting the CAD risk compared to the GCG models; the model based on the combination of all SCG and GCG classifiers did not achieve higher performance relative to the other models. Moreover, these findings showed that the performance of the proposed 3-axial SCG/GCG solution based on recordings obtained during rest was comparable, or better than stress ECG. These data may indicate that 3-axial SCG/GCG could be used as a portable at-home CAD screening tool.

The Influence of Headform/Helmet Friction on Head Impact Biomechanics in Oblique Impacts at Different Tangential Velocities

Oblique impacts of the helmet against the ground are the most frequent scenarios in real-world motorcycle crashes. The combination of two factors that largely affect the results of oblique impact tests are discussed in this work. This study aims to quantify the effect of the friction at the interface between the headform and the interior of a motorcycle helmet at different magnitudes of tangential velocity. The helmeted headform, with low friction and high friction surface of the headform, was dropped against three oblique anvils at different impact velocities resulting in three different magnitudes of the tangential velocity (3.27 m/s, 5.66 m/s, 8.08 m/s) with the same normal component of the impact velocity (5.66 m/s). Three impact directions (front, left-side and right-side) and three repetitions per impact condition were tested resulting in 54 impacts. Tangential velocity variation showed little effect on the linear acceleration results. On the contrary, the rotational results showed that the effect of the headform’s surface depends on the magnitude of the tangential velocity and on the impact direction. These results indicate that a combination of low friction with low tangential velocities may result into underprediction of the rotational headform variables that would not be representative of real-world conditions.