Browse Topic: Cardiovascular system

Items (559)
Understanding the physiological impact of vehicle electrification on operators remains an important but underexplored issue in commercial vehicle research. This study quantitatively evaluates the physiological fatigue of drivers and onboard crew members during real-world operation of commercial refuse-collection vehicles by comparing a diesel-powered vehicle with a fuel cell electric vehicle (FCEV). Both vehicles were operated on the same routes under comparable real-world operating conditions, including similar time periods and operational tasks, during municipal waste collection service. Heart Rate Variability (HRV) metrics were obtained from R-R interval (RRI) data recorded using a Polar heart rate sensor. The Root Mean Square of Successive Differences (RMSSD), a time-domain index reflecting short-term parasympathetic activity, and Poincaré (Lorenz) plot area (LP area), a nonlinear HRV index reflecting overall autonomic nervous system modulation, were calculated. In-cabin vibration and noise levels were also measured as supplementary context to support the interpretation of physiological responses. The results indicate that both RMSSD and LP area were higher during FCEV operation than during diesel vehicle operation. For the driver, RMSSD increased by approximately 61.65% and the LP area by approximately 49.91%. For the onboard crew member, RMSSD increased by approximately 18.79% and the LP area by approximately 46.02%. These findings suggest a consistent association between reduced vibration and noise characteristics in the FCEV and increased HRV indices, indicating reduced physiological fatigue during operation. This study provides quantitative evidence that fuel cell electric commercial vehicles are associated with improved occupational conditions, extending beyond conventional environmental benefits.
Utsumi, AtsukoYakoh, Takahiro
Pilot fatigue represents a critical concern in aviation safety, as it can significantly impair cognitive functions, decision-making abilities, and reaction times. In addition to decreasing performance, in-flight chronic fatigue has negative long-term health effects. Possible causes of fatigue include sleep loss, extended time awake, circadian phase irregularities and workload. Conventionally, the risk due to fatigue in aerospace is reduced by flight time limits and controlled rest requirements. Despite regulations limiting flight time and enabling optimal rostering, fatigue cannot be prevented completely. Hence, there is need to detect pilot fatigue in real time. There is ongoing research to detect pilot fatigue using devices that can capture Electroencephalogram (EEG) and Electrocardiogram (ECG). Though these devices have high fidelity, they are intrusive and can limit pilot activity. This limitation could potentially be overcome by non-intrusive devices such as a smart watch/wrist band/goggles which can measure physiological parameters that provide insights into pilot’s mental health. Heart rate variability (HRV) is one such physiological marker of interest for detecting pilot fatigue in real time. HRV can be effectively derived by processing raw Photoplethysmography (PPG) signals to gain insights into the autonomic nervous system, enabling the assessment of physiological state. Wearable devices such as a wristwatch are used in the current study to measure PPG data. Time and frequency domain analysis were performed to evaluate the potential of HRV indices. The analysis of R-R intervals and the Low Frequency / High Frequency (LF/HF) ratio plots, derived from HRV signals, revealed distinct characteristics that differentiate between an alert and a fatigued pilot. This study demonstrates a reliable non-intrusive method for detecting pilot fatigue and enhancing flight safety.
Nyamagoudar, VinayakP R, NamrathaRamachandran, Venkataramani
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.
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 rate, blood pressure and so on. We propose a solution which helps to navigate to the nearest health center or ambulance meeting point in emergency cases, overcoming technical glitches and delays by driving cars to the emergency center or meeting point, thus saving time for occupants. The prerequisite is that the vehicle has an advanced driver assistance system, detects health emergency of the occupants, V2X communication and SOS are triggered with the basic details of the situation. The system selects the nearest relevant hospital to drive to or requests the SOS center for the geo-coordinates of the ambulance meeting point using V2X communication. As soon as the system receives information related to meeting point from SOS center, autonomous driving mode is initiated, acknowledgment is sent to SOS center, and live location is shared for better communication and coordination. Additionally, the system triggers a siren and emergency lights to indicate an emergency drive, ensuring safety and a clear path. This proactive solution increases the probability of rescuing occupants by taking necessary action, rather than just monitoring, reporting, and waiting for measures.
Eswarappa, AshaNagaraj, ChaitraMudassir, Syed
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.
Singh, SamagraPandya, KavitaJituri, Keerti
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.
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, trust, and fatigue were independent constructs and exhibited distinct and significant associations with physiological metrics from corresponding measurement channels. Specifically, perceived risk correlated with sympathetic and parasympathetic activation, as reflected by heart rate variability metrics such as standard deviation of normal-to-normal intervals and root mean square of successive differences. Trust exhibited negative correlations with galvanic skin response indicators of physiological arousal, including skin conductance level and skin conductance responses, etc. Fatigue, meanwhile, showed consistent correlations with eye movement metrics like percentage of eye closure and mean fixation duration. These findings validate the specificity of physiological metrics as objective indicators for each driver state construct, highlighting their potential for real-time in-cabin monitoring, and contributes to improving traffic safety and comfort of automated vehicles.
Wang, ZhenyuanLi, QingkunWang, WenjunLiu, WeiminSun, ZhaocongCheng, Bo
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. The physical and chemical properties were determined for different blends of Biodiesel specifically JB20, JB30 and JB100 before engine testing. Engine tests were recorded on engine eddy current dynamometer and vehicle emission were recorded on chassis dynamometer to investigate the performance and emission characteristics of different biodiesel blends compared with conventional diesel. Recorded engine test performance infers improvement in observed torque and power. BSFC and Smoke results were comparable on full load and part load conditions. There is reduction in HC, CO raw emission with JB20 and JB30 Biodiesel fuel as compared to conventional Bharat Stage 6 Diesel fuel. Particulate Matter are comparable with all the above fuels. Vehicle mass emission with combination of port water injection and JB20 biodiesel has benefited further to reduce HC & NOx emission to meet Bharat Stage 6 emission norms on Diesel three-wheel vehicle on Indian Driving cycle. These findings highlight the potential of Jatropha biodiesel as a cleaner alternative to conventional diesel.
Bhoite, VikramSyed, KaleemuddinChaudhari, SandipKhairnar, GirishJagtap, PranjalReddy, Kameswar
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 standard deviation of normal-to-normal intervals (SDNN) under different riding environments; music in the frequency band of 200Hz to 600Hz can significantly improve comfort, and the average relative error of the prediction model is 8.209%. This study can provide data support for automobile manufacturers to optimize the design of suspension systems and seats. At the same time, by monitoring the physiological indicators of passengers, the vehicle system can adjust the sound signals in real time to alleviate the discomfort caused by bumps and enhance the driving experience.
Hu, LiChen, HaoWan, YeqingTian, RuiliXu, Jiahao
ETH Zurich Zurich, Switzerland
Researchers have developed a handheld device that could potentially replace stethoscopes as a tool for detecting certain types of heart disease.
A wearable wristband could significantly improve diabetes management by continuously tracking not only glucose but also other chemical and cardiovascular signals that influence disease progression and overall health.
Researchers have created a groundbreaking prototype for a new kind of leadless pacemaker designed for both children and adults. The innovative micropacemaker would be the first fully leadless system to be placed in the pericardial space surrounding the heart. That would allow the device to be implanted in a minimally invasive way in children and those with congenital heart disease, while also providing a lower-risk leadless pacemaker option for adults.
Human driver errors, such as distracted driving, inattention, and aggressive driving, are the leading causes of road accidents. Understanding the underlying factors that contribute to these behaviors is critical for improving road safety. Previous studies have shown that physiological states, like raised heart rates due to stress and anxiety, can influence driving behavior, leading to erratic driving and an increased risk of accidents. In this study, we conducted on-road tests using a measurement system based on the Driver-Driven vehicle-Driving environment (3D) method. We collected physiological signals, specially electrocardiography (ECG) data, from human drivers to examine the relationship between physiological states and driving behaviors. The aim was to determine whether ECG can serve as an indicator of potential risky driving behaviors, such as sudden acceleration and frequent steering adjustments. This information enables automated driving (AD) systems to intervene in dangerous situations. We collected measurements from 22 participants, each tested for 15 minutes on the highway, resulting in a dataset of 330 minutes of physiological data and over 500 km of driving data. The data was segmented into 15-second intervals for detailed analysis. Each segment was labeled twice: physiological states classified as ’stress’ or ’relaxation’ based on heart rate derived from ECG, and driving styles categorized as ’defensive’, ’average’, or ’sporty’ based on CAN-Bus data. Preliminary findings revealed a significant correlation between overall driving behavior on the highway and physiological states. We selected key driving parameters, including velocity, acceleration, lateral acceleration, and yaw rate. We found that acceleration in longitudinal and lateral direction can best indicate driver control and intention, and they vary significantly under two physiological states. This study focuses on how physiological signals change during aggressive driving and aims to establish these signals as indicators for alerting drivers, ultimately reducing the risks of accident associated with aggressive driving behaviors.
Ji, DejieFlormann, MaximilianBollmann, JulianHenze, RomanDeserno, Thomas M.
Mini organs are incomplete without blood vessels. To facilitate systematic studies and ensure meaningful comparisons with living organisms, a network of perfusable blood vessels and capillaries must be created — in a way that is precisely controllable and reproducible. A team has established a method using ultrashort laser pulses to create tiny blood vessels in a rapid and reproducible manner. Experiments show that these vessels behave just like those in living tissue. Liver lobules have been created on a chip with great success.
A research team has developed DeepNeo, an AI-powered algorithm that automates the process of analyzing coronary stents after implantation. The tool matches medical expert accuracy while significantly reducing assessment time. With strong validation in both human and animal models, Deep-Neo has the potential to standardize monitoring after stent implantation and thus improve cardiovascular treatment outcomes.
Cardiovascular disease (CVD) remains a leading — and growing — cause of morbidity and mortality worldwide, with the economic burden of care projected to skyrocket over the coming decades.
Boston Scientific entered 2025 with significant momentum. Fresh off a standout first quarter, the company’s leadership has outlined a compelling vision for sustainable long-term growth rooted in high-performing cardiology franchises, operational precision, and disruptive technologies in electrophysiology (EP). Leaders spoke at a recent Bank of America Healthcare Conference. The discussion marked outgoing CFO Dan Brennan’s final investor presentation and underscored Boston Scientific’s transformation into one of medtech’s most durable growth stories.
This study presents a novel biomimetic flow-field concept that integrates a triply periodic minimal surface (TPMS) porous architectures with a hierarchical leaf-vein-inspired distribution zone, fabricated through 3D printing. By mimicking natural transport systems, the proposed design enhances oxygen delivery and water removal in proton exchange membrane fuel cells (PEMFCs). The results showed that I-FF and G-FF significantly improved mass transport and water management compared to conventional CPFF. The integrated design I-FF-LDZ achieves up to 32% improvement in power density at 1.85 A/cm2@0.4 V and delays the onset of mass transport losses. The study also reveals that optimizing the volume fraction Vf significantly affects gas penetration, with lower Vf (30%) improving performance in the mass-limited region. These findings underscore the promise of nature-inspired, 3D-printed flow-field architectures in overcoming key transport limitations and advancing the scalability of next-generation PEMFC systems.
Ho-Van, PhucLim, Ocktaeck
A pacemaker is a small device that helps control your heartbeat so you can return to your normal life. It has three main parts: a pulse generator that creates electrical signals, a controller-monitor that manages these signals, and leads that deliver the signals to the heart. One key benefit of the pacemaker is its strong titanium casing. Titanium is very strong and lightweight, and it is biocompatible, meaning it works well with the body without causing harmful reactions. This metal is highly resistant to corrosion, which helps keep the casing intact and protective even when exposed to bodily fluids.
An invention that uses microchip technology in implantable devices and other wearable products such as smart watches can be used to improve biomedical devices including those used to monitor people with glaucoma and heart disease.
A team of researchers has developed self-powered, wearable, triboelectric nanogenerators (TENGs) with polyvinyl alcohol (PVA)-based contact layers for monitoring cardiovascular health. TENGs help conserve mechanical energy and turn it into power.
Advancements in sensor technologies have led to increased interest in detecting and diagnosing “driver states”—collections of internal driver factors generally associated with negative driving performance, such as alcohol intoxication, cognitive load, stress, and fatigue. This is accomplished using imperfect behavioral and physiological indicators that are associated with those states. An example is the use of elevated heart rate variability, detected by a steering wheel sensor, as an indicator of frustration. Advances in sensor technologies, coupled with improvements in machine learning, have led to an increase in this research. However, a limitation is that it often excludes naturalistic driving environments, which may have conditions that affect detection. For example, reductions in visual scanning are often associated with cognitive load [1]; however, these reductions can also be related to novice driver inexperience [2] and alcohol intoxication [3]. Through our analysis of the research, we discover that the tendency to explore these singular driver states with only a comparison to “normal” driving is common. Additionally, research on interventions for these driver states is relatively scarce (fewer than 10% of cognitive load-related papers we examined assessed or discussed intervention solutions) and narrowly tailored to specific states [e.g., 4, vis-à-vis cognitive load]. States that share common behavioral and physiological markers tend to be explored independently when a more universal and integrated approach may be warranted. In this paper, we identify the need for a driver state and intervention framework that addresses these limitations by exploring state indicators and their overlap, interventions for one or multiple states, and major research gaps. Our framework offers practical approaches for handling one or many driver states, including interventions that may be deployed at different timings during a trip.
Seaman, SeanZhong, PeihanAngell, LindaDomeyer, JoshuaLenneman, John
The proliferation of intelligent technologies in the future battlefield necessitates an exploration of crew workload balancing strategies for human-machine integrated formations. Many current techniques to measure cognitive workload, through qualitative surveys or wearable sensors, are too brittle for the harsh, austere operational environments found in military settings. Non-invasive workload estimation techniques, such as those that analyze physiological effects from video feeds of the crew, present a way forward for workload-aware Soldier-machine interfaces that could trigger events – such as task reallocation – if limits on crew or individual workload are exceeded. One such technique that is being explored is the use of facial expression analysis for workload estimation. We present the performance results of regression and classification models developed from supervised machine learning algorithms that predict pNN50, a common heart rate variability metric used as a physiological measure for workload, from action unit intensity data of the Facial Action Coding System (FACS). Drawing from these results, we propose implementation recommendations for leveraging facial expressions to inform crew workload in workload-aware Soldier-machine interfaces. We conclude with a discussion on open challenges and areas of exploration for non-invasive workload estimation in military vehicle applications.
Mikulski, ChristopherRiegner, Kayla
As human drivers' roles diminish with higher levels of driving automation (SAE L2-L4), understanding driver engagement and fatigue is crucial for improving safety. We developed an integrated hardware and software system to analyze driver interaction with automated vehicles, with a particular focus on cognitive load and fatigue assessment. The system includes three submodules; namely the Driver Behavior Measurement (DBM), Vehicle Dynamics Measurement (VDM), and the Driver Physiological Measurement (DPM). The DBM module uses electro-optical (EO) and infrared (IR) camera to track a number of facial features such as eye aspect ratio (EAR), mouth aspect ratio (MAR), pupil circularity (PUC), and mouth to eye aspect ratio (MOE). Although determining these metrics from images of the driver’s face in conditions such as low light or with sunglasses is challenging, the paper showed that fusion of EO and IR image analysis produces robust performance. The VDM module utilizes an Inertial Measurement Unit (IMU) to provide vehicular motion data such as speed, acceleration, braking and yaw rate to aid detection of fatigue-related irregularities. A wearable heart rate monitor was used in the DPM module to track driver heart rate as an indicator of stress and fatigue. Data from these modules is fused and processed using a previously published CNN-LSTM model, achieving 90.1% accuracy in detecting fatigue in preliminary tests performed with one driver. The test results show that the system is robust, scalable, and suitable for large-scale studies on driver engagement with highly automated vehicles.
Jirjees, AbdullahRahman, TaufiqFarhani, GhazalSingh, DanielCharlebois, Dominique
Every year, more than 5 million people in the United States are diagnosed with heart valve disease, but this condition has no effective long-term treatment. When a person’s heart valve is severely damaged by a birth defect, lifestyle, or aging, blood flow is disrupted. If left untreated, there can be fatal complications.
Recent successes in cultivating human heart tissue, knee cartilage, and pharmaceutical crystals in space have relied on technology that was initially developed decades ago with support from NASA.
With over 15,000 products, Boston Scientific is a market leader in pacemakers, defibrillators, monitoring equipment, spinal and brain stimulation, stents, catheters, and ablation devices. On one recent cardiac monitoring battery component, the company had an application running year-round on multiple mills, rectangular in shape, consisting of multiple milling operations per part, requiring an operator per mill at all times. Both Mill operations consist of multi-part fixtures as the process involved running Mill OP-1, light hand deburring and prepping the parts for Mill OP-2 fixture & process, following manual deburring step. The overall process was running around seven minutes per part.
A new device aims to detect acute exacerbations of chronic conditions. The wearable monitoring device contains multiple types of sensors, enabling faster and more accurate detection of exacerbations of chronic obstructive pulmonary disease and chronic conditions like asthma, heart disease and other inflammatory disorders. Eventually, the technology may help everyday people monitor their overall health and attune to early warning signs of illness.
Biosensors are devices that can monitor physiological states, like heart rate or blood pressure, or detect biological parameters such as glucose levels or the presence of specific proteins in the blood. The information biosensors collect can be used to support a medical diagnosis (for instance, a specific infection) or to provide feedback to the user on parameters of interest (for instance, the number of calories burned in a workout).
Researchers at University of Galway have developed a way of bioprinting tissues that change shape as a result of cell-generated forces, in the same way that it happens in biological tissues during organ development.
A study at Mayo Clinic suggests that an hourglass-shaped stent could improve blood flow and ease severe and reoccurring chest pain in people with microvascular disease. Of 30 participants in a phase 2 clinical trial, 76 percent saw improvement in their day-to-day life. For example, some participants who reported not being able to walk around the block or up a flight of stairs without chest pain were able to do these ordinary physical activities at the end of a 120-day period.
Interventional cardiologists have long used the traditional angiogram technique to diagnose and plan interventional procedures. An estimated 80–85 percent still lean on the process, which includes injecting contrasting material and utilizing x-ray images to guide the next steps for patient care. The other 15–20 percent supplement angiography with catheter-driven intravascular imaging devices to view arteries internally. Intravascular imaging is rapidly growing, with technological advancements, increased physician utilization, and a growing body of evidence showing positive patient outcomes when imaging is used to guide procedures.
Wearable devices like smartwatches and fitness trackers interact with parts of our bodies to measure and learn from internal processes, such as our heart rate or sleep stages. Now, MIT researchers have developed wearable devices that may be able to perform similar functions for individual cells inside the body.
Komatsu introduced its first battery-electric load-haul-dump (LHD) machine, the WX04B, at the MINExpo tradeshow in September. The WX04B is designed specifically for narrow vein mines in underground hard rock mining operations. Komatsu is pairing the electric LHD with its new OEM-agnostic 150-kW battery charger that was also revealed in Las Vegas. The 4-tonne WX04B LHD features what Komatsu claims is best-in-class energy density, offering up to four hours of runtime on a single charge. The Li-ion NMC (nickel-manganese-cobalt) battery from Proterra has a capacity of 165 kWh and nominal voltage of 660 V. Fewer charge cycles are needed compared to competitors, the company claims, which helps to maximize operational efficiency and minimize downtime. Proterra and Komatsu began their collaboration on the LHD's H Series battery system in 2021, long before Komatsu's acquisition of American Battery Solutions (ABS) in December 2023.
Gehm, Ryan
The Hospital for Sick Children/University of Toronto Toronto, ON, Canada
In the quest to develop lifelike materials to replace and repair human body parts, scientists face a formidable challenge: Real tissues are often both strong and stretchable and vary in shape and size.
University of Waterloo Chemical Engineering Researcher Dr. Elisabeth Prince teamed up with researchers from the University of Toronto and Duke University to design the synthetic material made using cellulose nanocrystals, which are derived from wood pulp. The material is engineered to replicate the fibrous nanostructures and properties of human tissues, thereby recreating its unique biomechanical properties.
In recent times, indoor air quality has become an important concern as it affects people’s health and comfort. According to WHO report, air pollution causes 7 million deaths every year. PM2.5 has been identified as a key pollutant which impacts human health causing diseases like stroke, heart diseases, breathing issues, cancer and so on [1]. In today's time, we travel by personal vehicle every day, commuting for hours. It is an extension to our homes. Unfortunately, due to frequent door and windows opening, the cabin air gets exposed to outside pollution, and we end up breathing pollutants. To mitigate the problem, air purifiers are added in the automobile. As people are becoming more aware and conscious about good air quality, there is a growing demand for cabin interior air quality solutions for automobiles. A popular approach is to add an air purifier inside cars like ones being used in our homes to bring down the PM2.5 levels. The air purifier consists of a filter, blower system, PM Sensor as well as a controller. This paper involves evaluation & comparison of: Different filter media such as pollen filter (HVAC Unit), PM2.5 filter (HVAC Unit), Standalone air purifier & combination of HVAC Unit filters in automobile.
Pimpalkar, AnkitPatel, AbhishekSonkar, SurabhiRajaur, DeepakJoshi, Rishi
A wearable health monitor can reliably measure levels of important biochemicals in sweat during physical exercise. The 3D-printed monitor could someday provide a simple and non-invasive way to track health conditions and diagnose common diseases, such as diabetes, gout, kidney disease or heart disease.
For many patients waiting for a donor heart, the only way to live a decent life is with the help of a pump attached directly to their heart. This pump requires about as much power as a TV, which it draws from an external battery via a seven-millimeter-thick cable. The system is handy and reliable, but it has one big flaw: despite medical treatment, the point at which the cable exits the abdomen can be breached by bacteria.
Understanding heart function and disease, as well as testing new drugs for heart conditions, has long been a complex and time-consuming task. A promising way to study disease and test new drugs is to use cellular and engineered tissue models in a dish, but existing methods to study heart cell contraction and calcium handling require a good deal of manual work, are prone to errors, and need expensive specialized equipment.
Investigating human driver behavior enhances the acceptance of the autonomous driving and increases road safety in heterogeneous environments with human-operated and autonomous vehicles. The previously established driver fingerprint model, focuses on the classification of driving styles based on CAN bus signals. However, driving styles are inherently complex and influenced by multiple factors, including changing driving environments and driver states. To comprehensively create a driver profile, an in-car measurement system based on the Driver-Driven vehicle-Driving environment (3D) framework is developed. The measurement system records emotional and physiological signals from the driver, including the ECG signal and heart rate. A Raspberry Pi camera is utilized on the dashboard to capture the driver's facial expressions and a trained convolutional neural network (CNN) recognizes emotion. To conduct unobtrusive ECG measurements, an ECG sensor is integrated into the steering wheel. Additionally, the system accesses CAN bus signals from the vehicle to assess the driver’s driving style, extracting signals related to longitudinal and lateral control behavior from the Drive-CAN (A-CAN). Recognizing that variables from the driving environment can influence driving style, such as traffic signs and road conditions, a windshield-mounted webcam is integrated into the measurement system. This setup enables real-time detection of common traffic signs and assessment of road conditions, distinguishing between dry, wet, or icy road surfaces. Augmenting of the image data from camera, signals from in-car ADAS-sensors, such as the distance measured by the front radar in relation to neighboring vehicles, are integrated for a comprehensive analysis of driving style. The established measurement system is presently implemented in a test vehicle, poised to investigate the interplay between the 3D-parameters, with a focus on driving style of human driver.
Ji, DejieFlormann, MaximilianWarnecke, Joana M.Henze, RomanDeserno, Thomas M.
Researchers from North Carolina State University have developed an exosome-coated stent with a “smart-release” trigger that could both prevent reopened blood vessels from narrowing and deliver regenerative stem cell-derived therapy to blood-starved, or ischemic, tissue.
iMotions employs neuroscience and AI-powered analysis tools to enhance the tracking, assessment and design of human-machine interfaces inside vehicles. The advancement of vehicles with enhanced safety and infotainment features has made evaluating human-machine interfaces (HMI) in modern commercial and industrial vehicles crucial. Drivers face a steep learning curve due to the complexities of these new technologies. Additionally, the interaction with advanced driver-assistance systems (ADAS) increases concerns about cognitive impact and driver distraction in both passenger and commercial vehicles. As vehicles incorporate more automation, many clients are turning to biosensor technology to monitor drivers' attention and the effects of various systems and interfaces. Utilizing neuroscientific principles and AI, data from eye-tracking, facial expressions and heart rate are informing more effective system and interface design strategies. This approach ensures that automation advancements improve rather than hinder the driving experience.
Nguyen, Nam
As medical devices in today’s modern medicine continue to advance, they require power supplies that allow them to perform an ever-widening roles. These lightweight, wearable — and even implantable — medical devices comprise everything from activity/exercise watches, hearing aids, and medical call buttons to pacemakers, insulin pump monitors, and neuro- or gastric stimulators, as well as implantable cardiac pacemakers and defibrillators (ICDs). The rechargeable batteries used in these devices must provide for such vital functions as monitoring, signal processing, collecting and transmitting data, and providing specialized electronic pulses when needed to stimulate cardiac output and other physiological activity.
The global medical device market offers opportunities for innovation-driven growth. Demand for smart, new lifesaving and life-enhancing technologies is perhaps stronger than ever. Manufacturers around the world looking to capitalize on this eager global market face a long list of challenges — some big, some small. Supply-chain disruptions, labor shortages, rising materials costs, and other headwinds are leading to delays in both engineering and manufacturing processes. Despite these challenges, the world demands medical device manufacturers’ best. A surging geriatric population, implications of a global pandemic, and the mortality rates for heart disease, cancer, obesity, and other conditions are all contributing to strong and sustained market demand. One study predicts a compound annual growth (CAGR) of 5.4 percent will push global sales of medical devices to nearly $658 billion (USD) by 2028. Of course, the road to success will be littered with familiar roadblocks — and some that are entirely new.
With the rapid development of intelligent driving technology, there has been a growing interest in the driving comfort of automated vehicles. As vehicles become more automated, the role of the driver shifts from actively engaging in driving tasks to that of a passenger. Consequently, the study of the passenger experience in automated driving vehicles has emerged as a significant research area. In order to examine the impact of automatic driving on passengers' riding experience in vehicle platooning scenarios, this study conducted real vehicle experiments involving six participants. The study assessed the subjective perception scores, eye movement, and electrocardiogram (ECG) signals of passengers seated in the front passenger seat under various vehicle speeds, distances, and driving modes. The results of the statistical analysis indicate that vehicle speed has the most substantial influence on passenger perception. The driving mode has a minor effect on the passenger riding experience, while vehicle distance has virtually no impact. Additionally, the study found that average heart rate, average pupil diameter, maximum pupil diameter, and blink frequency can effectively reflect changes in passengers' subjective perception. Furthermore, a stepwise regression analysis was performed on the selected indicators that demonstrated statistical significance. It was discovered that passenger stress levels are positively correlated with average pupil diameter, thus establishing a relationship between passengers' subjective perception and objective physiological indicators. This study contributes to the research on the comfort of automated vehicles and can provide valuable insights for enhancing the acceptance of such vehicles.
Hu, HongyuZhang, GuojuanCheng, MingLi, ZhengyiHe, LeiSu, Lili
Monitoring the success of surgery on blood vessels is challenging, as the first sign of trouble often comes too late. By that time, the patient often needs additional surgery that carries risks similar to the original procedure. A new device could make it easier for doctors to monitor the success of blood vessel surgery.
ECGs help manage cardiovascular disease — which affects around 4 million Australians and kills more than 100 people every day — by alerting users to seek medical care.
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