Browse Topic: Anatomy

Items (5,128)
Drivers obtain road information through head and neck rotation. In order to study the influences of head and neck rotation posture on occupant injury in frontal impact scenario, the THUMS (Total Human Model for Safety) AM50 human body model with five different head and neck rotation postures but without active muscles was adopted to study the biomechanical injury responses of occupant under the frontal impact scenario at 56 km/h in this study. Firstly, the kinematic responses of total body and head acceleration curves at the center of gravity predicted by PMHS (Post Mortem Human Subject) and THUMS AM50 human model under the sled test conditions were compared to verify the simulation model for subsequent study. Then, the THUMS AM50 human model with standard occupant seating posture was adjusted to have five different head and neck rotation postures with 0°, ±20°, and ±40° rotation angle, respectively. Finally, a series of frontal impact sled with or without airbag simulations were
Li, Dongqiangjiang, YejieTan, ChunLi, YanyanGong, ChuangyeWu, HequanJiang, Binhui
To investigate the characteristics of injuries sustained by occupant with different lower limb postures under the frontal impact sled conditions. Using the finite element method a series of simulation analyses were conducted on THUMS (Total Human Model for Safety) AM50 human body model with four different postures, including standing posture, lower limb bent at 100°, 90°, and crossed forward-backward, under the frontal impact scenario at 56 km/h in this study. The simulation results indicated that the overall injury risk predicted by the THUMS AM50 huma body model with lower limb crossed forward-backward was higher than that predicted by the model with other postures. The values of injury criteria including of HIC (Head Injury Criterion), head resultant acceleration, and thoracic VC (Viscous Criterion) predicted by the THUMS AM50 huma body model with lower limb crossed forward-backward were highest in these series simulations. Also, the biomechanical responses, including stress or
Li, Dongqiangjiang, YejieTan, ChunLi, YanyanLi, YihuiWu, HequanJiang, BinhuiZhu, Feng
The WorldSID-50M dummy is widely adopted in regulatory and third-party testing programs (e.g., ECE, Euro-NCAP, C-NCAP) owing to its advanced design and superior biofidelity. However, in vehicle side oblique pole crash tests involving shoulder-covered side airbags - an expanded testing modality - excessive deflection of the upper thoracic ribs was observed. Notably, this phenomenon was absent in standard side moving deformable barrier (SMDB) tests. This study pursued two core objectives: (1) to systematically document the excessive upper thoracic rib deflection of the WorldSID-50M dummy in side oblique pole crash tests; and (2) to investigate the influence of arm-thorax interaction on such deflection using a Human Body Model (HBM) representative of a 50th percentile male occupant. Numerical simulation results reveal that while arm-thorax interaction does contribute to rib deflection, its impact on the excessive deflection of the upper thoracic ribs is negligible.
Zhou, DYChen, ShaopengYan, LiWu, JingLiu, ChongLv, XiaojiangYang, Heping
This study aimed to evaluate the influence of child anthropometry, seating postures (recline and rotation), seatbelt force limiting, and frontal collision scenarios on the kinematic response and injury risk in highly automated vehicles. The TUST IBMs 6YO-O model was conducted the frontal collisions in sled tests. This simulation matrix includes five percentiles six-year-old occupants (P3, P25, P50, P75, and P97), three seatback angles (20°, 30°, and 45°), four seat rotation angles (0°, 90°, 180°, and 270°), three seatbelt force limiting (2.6 kN, 3.6 kN, and 4.6 kN), and three frontal collision types. Injury risks were assessed including the child occupant's head, neck, chest/abdomen, and lumbar region in each simulation (n=540). The results indicate that the child anthropometry, the seatback angle, and the seat rotation angle have a significant influence on the motion responses. Statistically significant differences between all the groups within each independent variable category were
Wang, YanxinZhao, HongqianLi, HaiyanHe, LijuanCui, ShihaiLv, Wenle
Head restraint requirements and designs have evolved to minimize the delay in head support and reduce differential loading in the neck. As a result, they have become bigger, closer to the occupant’s head, and angled forward relative to the seat back. Head restraints have been found missing or detached in the field; they may be removed pre-crash due to occupant comfort issues, or post-crash for better accessibility during extrication. Additionally, although rare, head restraints may become detached in severe rear impacts due to occupant loading. To better understand occupant-to-head restraint dynamic interactions, nine rear sled tests were conducted. The test conditions were selected to represent worst case severe loading scenarios. An instrumented 50th Hybrid III ATD (Anthropomorphic Test Device) was lap-shoulder belted on a right-front seat. The neck was equipped with a bracket and lower neck load cell designed for rear impacts. Three series of sled tests were performed wherein the
Parenteau, ChantalBurnett, RogerDavidson, Russell
With the rapid development of automated driving and the increasing adoption of “zero-gravity” seats, the crash safety of highly reclined occupants has become a critical issue. The current THOR dummy, designed for frontal impacts in the standard upright posture, exhibits limitations when directly applied to reclined seating configurations, including insufficient spinal flexion capability and excessive posterior pelvic rotation. In this study, the thoracolumbar spine kinematics of the THUMS human body model, reconstructed against post-mortem human subject (PMHS) tests, were analyzed. A two-segment linear fitting was employed to characterize a “dummy-like” spinal flexion response, yielding a virtual rotational hinge located near the thoracolumbar joint of the original THOR model. The characteristic rotation angle obtained from THUMS showed a strong linear correlation with the flexion moment of the T12–L1 vertebrae. Based on this relationship, the rotational joint of the THOR dummy was
Guo, WenchengKuang, GaoyuanShen, WenxuanTan, PuyuanZhou, Qing
In the context of Industry 5.0, effective human–machine collaboration requires seamless and natural interaction. Hand-Gesture Recognition (HGR) has emerged as a promising technology for developing human–machine interfaces (HMI) that enable users to control robotic systems without physical controllers or wearable devices. This research presents a real-time HGR system designed to control a 6-Degree-of-Freedom (DoF) robotic arm using YOLOv10, a state-of-the-art deep learning model for hand gesture detection and classification. While YOLOv10 delivers high recognition accuracy, its computational demands surpass the capabilities of edge devices typically mounted on robotic platforms, creating a hardware bottleneck. To address this challenge, a cooperative client–server architecture is proposed, distributing computational workload between the edge device and a more powerful remote server. An RGB camera attached to the robotic arm captures hand gesture images and transmits them to the server
DeHaven, Aaron LeePark, Jungme
A machine learning (ML)-based meta-analysis was conducted to evaluate rear seat occupant safety performance in the Insurance Institute for Highway Safety (IIHS) Moderate Overlap Frontal (MOF) 2.0 crash test. ML models were trained on historical IIHS crash test data to predict rear passenger injury metrics using vehicle architecture, restraint system characteristics, crash pulse parameters, and vehicle kinematics as input features. The models demonstrated high predictive accuracy and were subsequently used in a Sobol sensitivity analysis to identify critical design parameters influencing injury outcomes. The analysis revealed that rear passenger injury metrics were most sensitive to restraint system parameters. Specifically, crash pulse magnitude was the dominant factor for head injury metrics, pretensioner activation time for neck tension force, and lap belt force for the Neck Injury Criterion (Nij). For chest-related metrics—sternum deflection, dynamic belt position, and maximum belt
Lalwala, MiteshKim, WonheeFurton, LisaSong, Jay
Five sled tests were performed with a Hybrid III (H-III) 10-year-old child sized Anthropomorphic Test Device (ATD) positioned in the 2nd row left seat of a three row 2006 Sport Utility Vehicle (SUV). A HYGE Sled buck was positioned to represent/replicate a side impact collision to the passenger (right) side of the SUV, with a Principal Direction of Force (PDOF) of 60 degrees, resulting in a far side side-impact for the ATD. Of the 5 tests performed, three of the five tests were performed with a delta-V of 17 mph, and two of the tests at a delta-V of 24 mph. Of the 17 mph tests, one test was performed with a properly restrained ATD, and two tests performed with improper restraint positioning. Both of the 24 mph tests were performed with improper restraint positioning, effectively identical to the two 17 mph delta-V tests. The two improper restraint use tests (at both 17 and 24 mph delta-V) included two different improper restraint scenarios. The first scenario of improper restraint
Luepke, PeterHewett, NatalieBetts, KevinVan Arsdell, WilliamWeber, PaulStankewich, CharlesMiller, GregoryWatson, RichardSochor, Mark
Head restraint requirements and designs have evolved to minimize the delay in head support and reduce differential loading in the neck. As a result, head restraints have become bigger and more angled forward, sitting, closer to the occupant’s head. Head restraints separation from seatbacks are sometimes observed in the field. Are head restraint detachments resulting from occupant comfort issues prior to the crash, occupant loading during the crash or were they removed by emergency personnel for extrication? Understanding the retention strength of head restraints and the type of evidence left behind by a forced removal may help researchers resolve the question of how a head restraint may be found post-crash separated from the seat. Quasistatic pull tests were conducted to measure vertical retention capabilities, compare vertical adjustment and release mechanisms, and document deformation and damage. Eighteen different front seat head restraint designs were evaluated. The model years
Parenteau, ChantalBurnett, RogerDavidson, Russell
Autonomous vehicles may attract more passengers to recline their seat for comfort. However, under severe rear-end crashes and large reclining angle, the backward inertia could completely throw occupant out of seat. Even if the occupant body can be restrained by seatbelt, the occupant’s head could slide out of the head restraint area. Any of these situations may cause severe injuries. To address this safety concern, we developed a sliding seat system designed to enhance occupant retention. Activated by impact inertia of rear-end collision, the system allows the seat sliding backward along its track in a controlled manner, and the sliding stroke is accompanied by a restraint force and absorbs some amount of kinetic energy during the sliding. Thus, occupant retention can be enhanced, and injury risks of head and neck can be reduced. To demonstrate this concept, we built a MADYMO model and conducted a parametric analysis. The model includes a 50th percentile human model, a vehicle seat
Dai, RuiZhou, QingPuyuan, TanShen, Wenxuan
Scientists used a “smart” shirt equipped with an electrocardiogram to track participants’ heart-rate recovery after exercise and developed a tool for analyzing the data to predict those at higher or lower risk of heart-related ailments.
This study investigates the concentrations of PM2.5 and PM10 inside an automobile under real-world driving conditions, one of the most polluted cities globally. India faces severe air pollution challenges in many cities, including Delhi, which are consistently ranking among the most polluted cities in the world. Major contributors to this pollution include vehicular emissions, industrial activities, construction dust, and biomass burning. Exposure to PM2.5 and PM10 has been linked to numerous adverse health effects, including respiratory and cardiovascular diseases, aggravated asthma, decreased lung function, and premature mortality. PM2.5 particles, being smaller, can penetrate deeper into the lungs and even enter the bloodstream, causing more severe health issues. In big cities like New Delhi, long driving times exacerbate exposure to these pollutants, as commuters spend extended periods in traffic. Measurements were taken both inside and outside the vehicle to assess the real-world
Gupta, RajatPimpalkar, AnkitPatel, AbhishekKumar, ShubhamJoshi, RishiKumar, Mukesh
This invention solves a significant safety issue where drivers have low visibility of the Outside Rear View Mirror (ORVM) in the case of rain, fog, dust or ice formation on the Side Door Window Glass (SDWG). Currently developed methods, such as hydrophobic finishing or films and heated window glass on the doors, provide temporary or weak results, and thus, a more successful and dependable method is demanded. In order to address this problem, we have modified the Outer Waist Seal, which includes a Glass Wiping Mechanism in it. Outer Waist Seal is a type of weather strip fixed on the bottom of the side window of a vehicle on the panel of the door. It does not allow the flow of heavy water, dust and debris into the door cavity, besides supporting the glass on the window when it is in a movement process. The stationary fixed arm of this system is coupled with a rotating arm and an attached wiper blade powered by a low-speed-high-torque motor and interfaced with the Body Control Module (BCM
Neelam, RajatChowdhury, AshokPanchal, GirishKumar, Saurav
The rapid development of science and technology has impacted on the human lifestyle. The automotive industry plays a crucial role as travel is an integral part of human lifestyle. This indeed has increased the need and demand for automotive domain to step ahead with technology and innovations. Especially, related to ADAS features and AI/ML based algorithms to provide comfort, safety, and many other factors for the consumers. The busy life of human beings has shown an increased rate of many health-related issues like stress, anxiety, heart attacks, blood pressure and so on. The existing system in vehicles detects health emergency and triggers SOS to the emergency service center. However, several catastrophic events occur due to delayed information, thus there is a need for a proactive solution that combines technology and human safety. In this work, we have investigated the different methods which detect the health issues of occupants in a vehicle by monitoring their stress level, heart
Eswarappa, AshaNagaraj, ChaitraMudassir, Syed
In recent years, virtual models have been extremely helpful in predicting potential injury risk to occupants in vehicle crashes. Virtual models offer detailed occupant anthropometry and closest possible bio-fidelity over existing test devices. This study focuses on the assessment of chest deflections in frontal thorax impacts using virtual human body models of a few anthropometries and transforming the assessment of injuries for a broader range of anthropometries (sections of the population). The study utilizes machine learning to enable injury assessment across a wide range of body types. A standard test scenario (Kroell load case) with a frontal blunt thoracic impact is considered for this study. Results from physical tests and simulations from various finite element human body models (HBMs) from literature are used to train supervised machine learning models. The combination of virtual simulation and machine learning reduces the reliance on physical prototypes and expands the reach
Sridhar, RaamArya, BibhuDivakar, PrajwalR, Udhaya KumarBhutki, PrasadKumar, DevendraKurkuri, MahendraMohan, Pradeep
Indian passenger car accident data indicates that approximately 44% of crashes are frontal impacts (Refer fig 1). Among the injuries sustained in these crashes, lower leg injuries are notably critical, contributing to nearly 25% of driver occupant injuries (Refer fig 2). To evaluate such injuries, the Bharat New Car Assessment Program (BNCAP) includes lower leg injury metrics as part of the Frontal Offset Deformable Barrier (ODB64) test. While the overall injury performance is assessed at the vehicle level, BNCAP also monitors vehicle interior intrusions—particularly pedal intrusions—as key contributors to lower limb injury severity. A major challenge in frontal crashes is the intrusion of the vehicle's front-end structure into the occupant compartment. Rigid components, particularly the brake pedal assembly, can be displaced rearward during a crash, significantly increasing the risk of lower leg injuries. Therefore, minimizing pedal intrusions into the driver foot-well is critical for
Shetti, Rahul R.Kudale, ShaileshNaik, NagarajBisen, BadalKotak, VijayDudhewar, SwapnilBhagat, AmitDurgaprasad, HNV
Severe rear-impact collisions can cause significant intrusion into the occupant compartment when the structural integrity of the rear survival space is insufficient. Intrusion patterns are influenced by impact configuration—underride, in-line, or override—with underride collisions channeling forces below the beltline through the rear wheels as a primary load path. This force concentration rapidly propels the rear seat-pan forward, contacting the rearward-rotating front seatback. The resulting bottoming-out phenomenon produces a forward impulse that amplifies loading on the front occupant’s upper torso, increasing the risk of thoracic injury even when the head is properly supported by the head restraint. This study analyzes a real-world rear-impact collision that resulted in fatal thoracic injuries to the driver, attributed to the interaction between the driver’s seatback and the forward-moving rear seat pan. A vehicle-to-vehicle crash test was conducted to replicate similar intrusion
Thorbole, Chandrashekhar
This study introduces a novel in-cabin health monitoring system leveraging Ultra-Wideband (UWB) radar technology for real-time, contactless detection of occupants' vital signs within automotive environments. By capturing micro-movements associated with cardiac and respiratory activities, the system enables continuous monitoring without physical contact, addressing the need for unobtrusive vehicle health assessment. The system architecture integrates edge computing capabilities within the vehicle's head unit, facilitating immediate data processing and reducing latency. Processed data is securely transmitted via HTTPS to a cloud-based backend through an API Gateway, which orchestrates data validation and routing to a machine learning pipeline. This pipeline employs supervised classifiers, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Random Forest (RF) to analyze features such as temporal heartbeat variability, respiration rate stability, and heart rate. Empirical
Singh, SamagraPandya, KavitaJituri, Keerti
Real-world crashes involve diverse occupants, but traditional restraint systems are designed for a limited range of body types considering the applicable regulations and protocols. While conventional restraints are effective for homogeneous occupant profiles, these systems often underperform in real-world scenarios with diverse demographics, including variations in age, gender, and body morphology. This study addresses this critical gap by evaluating adaptive restraint systems aligned with the forthcoming EURO NCAP 2026 protocols, which emphasize real-world crash diversity and occupant type. Through digital studies of frontal impact scenarios, we analyze biomechanical responses using adaptive restraints across varied occupant demographics, focusing on head and chest injury (e.g., Chest Compression Criterion [CC]). This study used a Design of Experiments (DOE) approach to optimize occupant protection by timing the actuating of these adaptive systems. The results indicate that activating
satija, AnshulSuryawanshi, YuvrajChavan, AvinashRao, Guruprakash
Occupant Safety systems are usually developed using anthropomorphic test devices (ATDs), such as the Hybrid III, THOR-50M, ES-2, and WorldSID. However, in compliance with NCAP and regulatory guidelines, these ATDs are designed for specific crash scenarios, typically frontal and side impacts involving upright occupants. As vehicles evolve (e.g., autonomous layouts, diverse occupant populations), ATDs are proving increasingly inadequate for capturing real-world injury mechanisms. This has led to the adoption of computational Human Body Models (HBMs), such as the Global Human Body Models Consortium (GHBMC) and Total Human Model for Safety (THUMS), which offer superior anatomical fidelity, variable anthropometry, active muscle behaviour modelling, and improved postural flexibility. HBMs can predict internal injuries that ATDs cannot, making them valuable tools for future vehicle safety development. This study uses a sled CAE simulation environment to analyze the kinematics of the HBMs
Raj, PavanRao, GuruprakashPendurthi, Chaitanya SagarNehe, VaibhavChavan, Avinash
The objective of the present study is to examine trends in occupant kinematics and injuries during side impact tests carried out on vehicle models over the period of time. Head, shoulder, torso, spine, and pelvis kinematic responses are analysed for driver dummy in high speed side impacts for vehicle model years, MY2016-2024. Side impact test data from the tests conducted at The Automotive Research Association of India (ARAI) is examined for MY2016-2024. The test procedure is as specified in AIS099 or UNECE R95, wherein a 950kg moving deformable barrier (MDB) impacts the side of stationary vehicle at 50km/hr. An Instrumented 50th percentile male EUROSID-2 Anthropomorphic Test Device is positioned in the driver seat on the impacting side. Occupant kinematic data, including head accelerations, Head Injury Criterion (HIC15), Torso deflections at thorax and abdominal ribs, spine accelerations at T12 vertebra, and pelvis accelerations are evaluated and compared. The “peak” and “time to
Mishra, SatishBorse, TanmayKulkarni, DileepMahajan, Rahul
One of the biggest goals for companies in the field of artificial intelligence (AI) is developing “agentic” systems. These metaphorical agents can perform tasks without a guiding human hand. This parallels the goals of the emerging urban air mobility industry, which hopes to bring autonomous flying vehicles to cities around the world. One company wants to do both and got a head start with some help from NASA.
Cornell researchers and collaborators have developed a neural implant so small that it can rest on a grain of salt, yet it can wirelessly transmit brain activity data in a living animal for more than a year.
Trying to document how single brain cells participate in networks that govern behavior is a daunting task. Brain probes called Neuropixels, which feature high-density silicon arrays, have enabled scientists to collect electrophysiological data of this nature from a variety of animals. These include fish, reptiles, rodents, and primates, as well as humans.
Researchers are exploring new ways to utilize microwave technology in monitoring and assessing health conditions. The results of experiments conducted with realistic models are promising. Bras that detect breast cancer, leg sleeves that identify blood clots, and a helmet that monitors the effects of radiation therapy offer a glimpse into what future healthcare might look like.
EPFL researchers have invented a remarkably small and ultraflexible neurovascular microcatheter. Powered by blood flow, it can safely navigate the most intricately branched arteries in a matter of seconds.
Bioelectronics, such as implantable health monitors or devices that stimulate brain cells, are not as soft as the surrounding tissues due to their metal electronic circuits. A team of scientists has developed a soft polymer hydrogel that can conduct electricity as well as metal can. As the material is both flexible and soft, it is more compatible with sensitive tissues. This finding has the potential for a large number of applications, for example, in biocompatible sensors and in wound healing.
University of Texas at Dallas researchers have developed biosensor technology that when combined with artificial intelligence (AI) shows promise for detecting lung cancer through breath analysis.
For driver-automation collaborative driving, accurately monitoring driver state in smart cockpits is crucial for enhancing safety, comfort, and human-computer interactions. However, existing research lacks clarity regarding the relationships among driver states, and there is no consensus on the optimal physiological channels to reliably capture these states. This study examined three critical psychological constructs (i.e., perceived risk, trust in the automated driving system, and driver fatigue) using a 37-participant driving simulation experiment. We manipulated multiple factors to induce distinct driver states among participants and recorded subjective scale ratings, heart rate variability, galvanic skin response, and eye movement data. Subjective scale ratings were adopted as the ground truth to examine the corresponding measurement relationships between different physiological signals and the three targeted dimensions of driver states. Our results proved that perceived risk
Wang, ZhenyuanLi, QingkunWang, WenjunLiu, WeiminSun, ZhaocongCheng, Bo
Perceiving the movement characteristics of specific body parts of a driver is crucial for determining their activity. Moreover, the driver’s body posture significantly impacts personnel safety during collision. This study investigates the creation of a dataset using Kinect depth camera for acquiring, organizing, annotating with skeleton tracking assistance, and optimizing interpolation. The pose recognition methods enhanced through an anchor regression mechanism, leading to the refinement of a lightweight anchor regression network capable of end-to-end learning ability from depth images. The improved backbone neck head structure offers advantages of reduced model parameters and enhanced accuracy. This engineering optimization makes it better suited for practical applications within vehicles with limited computational resources limitations and high real-time demands.
Xu, HailanLi, WuhuanLu, JunWang, XinHe, WenhaoChen, ZhenmingLiu, Yunjie
Studies correlate air pollution with an increase in the incidence of respiratory diseases, affecting lung function and raising hospitalization rates. Among the pollutants associated with these diseases, inhalable coarse particulate matter (PM10) and fine particulate matter (PM2.5) stand out. The emission of particulate matter resulting from the wear of brake pads in light vehicles is the second largest source, accounting for approximately 33% of a vehicle’s total emissions. The particulate matter generated during the braking process can be analyzed through its collection in tests conducted on dynamometers, using enclosure and sampling systems. The development of the dynamometer used was based on the braking cycles described in the SAE J2522:2003 standard, whose main objective is to provide comparative data on different friction materials. Given the variations in particulate matter emissions depending on the composition of the brake pads, as reported in the literature, this study
Catão, Vítor Gustavo GomesMachado, Amanda RibeiroFiorentin, Felipe KleinSilva, João Pedro AnutoBernardino, Lucas GabrielFiorentin, Thiago AntonioCarboni, Andrea Piga
With the continuous progress of modern high-speed railroad technology, the speed of train operation is increasing, and its aerodynamic effect when traversing the tunnel is also getting more and more attention from researchers. In this paper, we constructed a three-dimensional flow field model of the wrist-arm insulator in the tunnel and considered the train speed, tunnel structure, size and position of the wrist-arm insulator, and other factors, and then through the simulation software, we simulated the change of the airflow in the tunnel when the high-speed train enters the tunnel. Through the simulation analysis, we obtained the characteristics of the flow field distribution around the wrist-arm insulator in the tunnel when the high-speed train crosses the tunnel. The results show that when the train crosses the tunnel at a high speed, the airflow inside the tunnel is strongly squeezed and disturbed by the train, forming a complex airflow field. When the train passes by, the wrist
Zhang, KangkangMa, Jianqiao
Chimeric antigen receptor (CAR) T cell therapy represents a breakthrough in cancer treatment. By harnessing the body’s immune system, CAR T therapy provides a powerful, personalized treatment option that can be particularly effective for treating blood cancers like leukemia — potentially offering patients a second chance at life when other treatments have failed.
Cornell researchers have developed a low-power microchip they call a “microwave brain,” the first processor to compute on both ultrafast data signals and wireless communication signals by harnessing the physics of microwaves.
The knowledge of the brake linings coefficient of friction (BLCF) is crucial for the control of the braking moment in modern vehicles equipped with electric powertrains. In the case of race vehicles equipped with carbon–carbon brakes, the coefficient of friction exhibits great variations as a function of the main influencing factors, namely the pressure, the temperature, and the sliding speed at the pad–disc interface. In this work, a Le Mans Hypercar instrumented with more than 150 sensors was adopted to perform the characterization of the BLCF from racetrack acquisitions. The front and rear left suspensions of the vehicle were instrumented with strain gauge channels and position transducers to acquire the reaction loads at the upright and the orientation of the arms. Then, the geometric matrix method was implemented for calculating the moments at the upright from which the braking torque was derived without the need to know any of the wheel inertia, nor the driveshaft torque. Data
Cortivo, DavideVendramin, MattiaDindo, Luigi
Increasing reservations about the mass consumption of fossil fuels because of their hazardous impact on ecosystem has led to an increased focus to look for renewable alternative. In the last decade, much research is made on production of biodiesel for blending with diesel to reduce diesel consumption in the transport sector. Studies suggest that biofuel do not provide any harm to environment because of their availability from natural resources. Biofuel production and its further utilization requires identifying unknown parameters having nonlinear relationships with each other. Accurate and better predictive tools are required at different stages during its usage. AI technique is one such tool that can provide support during production and utilization. The technique is utilized in designing, monitoring, predicting, decision making and optimizing systems. The present research investigates the areas of AI usage which makes use of models for designing better production strategies, accurate
KUMAR, VIVEKVashist, Devendra
The increasing demand for alternative fuels due to environmental concerns has sparked interest in biodiesel as a viable substitute for conventional diesel. Most automotive engines use diesel fuel engines. They contribute a major portion of today’s air pollution, which causes serious health issues including chronic bronchitis, respiratory tract infections, heart diseases, and many more. Greenhouse gases are produced using fossil fuel in the engines and causes global warming. To combat air pollution, we need clean renewable and environmentally friendly fuels. Due to depletion of fossil fuels, it has become necessary to find alternative fuel which are safer for the environment and humankind. One such possible solution is Biodiesel. In present study, series of experiments were carried out on 435cc naturally aspirate DI Diesel engine with port water injection and different blend of Jatropha based Biodiesel. Biodiesel was derived from Jatropha oil, produced using a heterogeneous catalyst
Bhoite, VikramSyed, KaleemuddinChaudhari, SandipKhairnar, GirishJagtap, PranjalReddy, Kameswar
Innovators at the NASA Johnson Space Center have developed a soft, wearable, robotic upper limb exoskeleton garment designed to actively control the shoulder and elbow, both positioning the limb in specific orientations and commanding the limb through desired motions. The invention was developed to provide effective upper extremity motor rehabilitation for patients with neurological impairments (e.g., traumatic brain injury, stroke).
In blinding bright light or pitch-black dark, our eyes can adjust to extreme lighting conditions within a few minutes. The human vision system, including the eyes, neurons, and brain, can also learn and memorize settings to adapt faster the next time we encounter similar lighting challenges.
University College London London, England
In an era where technology increasingly merges with healthcare to enhance patient outcomes, a groundbreaking study conducted by Fuyang Yu and his colleagues introduces an innovative approach to lower limb rehabilitation. Their research, published in Cyborg Bionic Systems, outlines the development of a lower limb rehabilitation robot designed to significantly improve the safety and effectiveness of gait training through a novel method based on human-robot interaction force measurement.
Researchers have developed novel ISM-based sweat sensors that feature enhanced signal stability and performance and avoid skin contact, while also being reusable, making them practical for daily use.
KAIST Daejeon, Republic of Korea
In recent years, the vibration comfort of automobiles has become a key consideration for consumers when purchasing vehicles. This study introduces human electrocardiogram (ECG) signals and blood pressure, and proposes a comfort prediction model based on physiological indicators. The research steps include: obtaining riding indicators and subjective feelings on flat and bumpy roads, and analyzing the differences in heart rate variability indicators and blood pressure under different road conditions through paired sample tests; playing different sound signals on bumpy roads, and using repeated measures analysis of variance to explore their impacts on physiological indicators and subjective evaluations; conducting data validity tests on the subjective evaluation results, and constructing a comfort prediction model based on correlation analysis and support vector regression algorithm. The results show that there are significant differences in indicators such as the average RR interval and
Hu, LiChen, HaoWan, YeqingTian, RuiliXu, Jiahao
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