Browse Topic: Anatomy
Researchers at Cornell University, working with collaborators, have created an extremely small neural implant that can sit on a grain of salt. Despite its size, the device can wirelessly transmit brain activity data from a living animal for more than a year.
Researchers at the University of California, Irvine, and New York’s Columbia University have embedded transistors in a soft, conformable material to create a biocompatible sensor implant that monitors neurological functions through successive phases of a patient’s development.
In response to the 42nd (2025) Annual VFS Student Design Competition, the Graduate Student Design Team from the University of Maryland introduces Wyvern, a novel hydrogen-powered electric compound rotor-craft engineered for maximum loiter and operational safety. Named after a mythical dragon that defies convention by not breathing fire, Wyvern only breathes water vapor by forgoing hydrocarbon combustion in favor of the quiet and clean power of hydrogen. This design reflects not only an aeronautical solution to an engineering challenge but a greater aspiration to reshaping how practical and clean vertical flight can be achieved.
This study evaluates whether a statewide layered medical-drone architecture can improve time-critical EMS logistics in Florida by delivering blood products, AEDs, and critical support devices. We define Time-To-Clinical-Support (TTCS) as the interval from incident recognition to first effective therapy and use Florida EMS benchmark intervals, county-level population and centroid distance data, and p-median hub placement to model system performance. Scenario analysis compares 20-, 40-, and 60-hub deployments and estimates order-of-magnitude effects on AED TTCS and survival gains under explicit assumptions for availability, cruise speed, dispatch overhead, and bystander uptake. The results indicate that a mid-scale network may reduce delay sufficiently to produce meaningful clinical benefit, provided it is integrated with EMS dispatch, medical direction, cold-chain controls, and hurricane-resilient infrastructure. Regulatory pathway constraints, incomplete county-level OHCA data, and uncertainty in mission availability remain the primary limitations on precision and external validity.
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 unlocked during impact and assigned a torsional stiffness of 600 Nm/rad. Additional modifications were implemented in the hip region to enhance model applicability. Comparative simulations demonstrated that the modified THOR model achieved closer agreement with PMHS responses than both the Hybrid III and the baseline open-source THOR models. In particular, the posterior pelvic tilt was reduced from approximately 20° in the baseline THOR to about 10° in the modified version. These results indicate that incorporating PMHS-based thoracolumbar flexion characteristics together with targeted hip modifications significantly improves the biofidelity of the THOR dummy for reclined-occupant crash scenarios, providing a solid foundation for future dummy development and safety assessment.
A Detroit-based startup says its device can analyze brain activity to help figure out whether a driver is impaired. The impaired driver-detection business has been heating up since even before NHTSA announced in 2024 that it was working what would eventually be a mandate that vehicles be able to detect impaired drivers and mitigate the danger they represent to the motoring public.
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.
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 enhancing lower leg protection. As part of an innovative safety initiative, Tata Motors has developed a collapsible brake pedal mechanism designed to mitigate lower leg injuries during frontal crashes. This patented system incorporates a series of levers and linkages that disengage upon impact, allowing the brake pedal to collapse and thereby reducing the risk of intrusion-related injuries to the driver lower legs. The mechanism is engineered to be robust, ensuring that normal braking performance and pedal operation remain unaffected during everyday vehicle use, while providing effective injury mitigation in crash scenarios.
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 model in a frontal crash scenario. The methodology includes the initial correlation of Hybrid III CAE simulation results with physical sled test data, followed by a comparative analysis with GHBMC M50-O v6-2 based simulations. A significant difference was observed in pelvic forward displacement between the Hybrid III and GHBMC M50-O v6-2. The difference in interaction originates from the difference in the construction of the pelvis between the Hybrid III and GHBMC. In the GHBMC, reduced displacement occurs because the pelvis locks in the seat. This interaction is absent in ATDs, resulting in increased torso rotation and a potential rise in upper extremity injury risk for HBMs. The study examines the various reasons for pelvic locking and increased upper body rotation. These evaluations aim to raise the negative consequences of pelvic locking on upper extremity injuries. The probable solutions that can reduce pelvis locking while preserving occupant stability is also discussed. The study highlights the significance of HBMs in understanding occupant interactions and supports their use in the development of next-generation restraint systems.
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 evaluations demonstrate the system's proficiency in classifying occupant states, including normal, distressed, and unconscious conditions, achieving high prediction accuracy with low false positive rates. Notably, the system attains sub-10-second detection latency and facilitates end-to-end response actions within a 5-minute window. Experimental deployment in a Mercedes vehicle demonstrated high accuracy in occupancy detection (97%), vital sign monitoring (94%), and full ERS (Emergency Response System) activation within five minutes, meeting Euro NCAP 2025+ Child Presence Detection (CPD) requirements. Furthermore, the cloud infrastructure supports the accumulation of health data, contributing to personalized driver profiles and informed decision-making for future interventions. This research underscores the potential of UWB radar technology in augmenting automotive safety through real-time health monitoring, paving the way for smarter and more secure vehicular environments.
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 characteristics and assess the relative kinematics between the seatback and rear seat structure. Results demonstrate that seatback bottoming out under intrusion conditions significantly elevates thoracic loading. These findings highlight the need for improved rear structural design strategies to manage load paths in underride scenarios and to minimize front seatback rearward collapse and associated occupant loading.
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.
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.
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.
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.
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.
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.
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