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Induction-based breathing sensors in automobiles enable unobtrusive respiratory rate monitoring as an indicator of a driver's alertness and health. This paper introduces a quantitative method based on signal quality to guide the integration of textile inductive electrodes in automotive applications. A case study with a simplified setup illustrated the ability of the method to successfully provide basic design rules about where and how to integrate the electrodes on seat belts and seat backs to gather good quality respiratory signals in an automobile. The best signals came from the subject's waist, then from the chest, then from the upper back, and finally from the lower back. Furthermore, folding the electrodes before their integration on a seat back improves the signal quality for both the upper and lower back. This analysis provided guidelines with three design rules to increase the chance of acquiring good quality signals: (1) use a multi-electrode acquisition approach, (2) place the electrodes in locations that maximize breathing-induced body displacement, and (3) use a mechanical amplifying method such as folding the electrodes in locations with little potential for breathing-induced displacement. [ABSTRACT FROM AUTHOR]

As the market share of electric vehicles continues to rise, consumer demands for comfort within the vehicle interior have also increased. The noise generated by electric seats during operation has become one of the primary sources of in-cabin noise. However, the offline detection methods for electric seat noise severely limit production capacity. To address this issue, this paper presents an online quality inspection system for automotive electric seats, developed using LabVIEW. This system is capable of simultaneously detecting both the noise and electrical functions of electric seats, thereby resolving problems associated with multiple detection processes and low integration levels that affect production efficiency on the assembly line. The system employs NI boards (9250 + 9182) to collect noise data, while communication between LabVIEW and the Programmable Logic Controller (PLC) allows for programmed control of the seat motor to gather motor current. Additionally, a supervisory computer was developed to process the collected data, which includes generating frequency and time-domain graphs, conducting data analysis and evaluation, and performing database queries. By being co-located with the production line, the system features a highly integrated hardware and software design that facilitates the online synchronous detection of noise performance and electrical functions in automotive electric seats, effectively streamlining the detection process and enhancing overall integration. Practical verification results indicate that the system improves the production line cycle time by 34.84%, enabling rapid and accurate identification of non-conforming items in the seat motor, with a detection time of less than 86 s, thereby meeting the quality inspection needs for automotive electric seats. [ABSTRACT FROM AUTHOR]

The aim of the study is to compare the head displacement of the KPSIT C50 dummy during a frontal collision at a speed of 20 km/h, along with the change in the angle of the car seat backrest. Passenger car manufacturers recommend setting the backrest angle of the car seat between 100 and 125 degrees. It should be noted that the driver's position is of great importance in the event of a collision injury. In the event of a rear-end collision, the position of the headrest of the car seat is an element that affects the degree of the driver's injuries. In extreme cases, incorrect positioning of the headrest, even at low speed, can lead to serious injuries to the cervical spine and even death. The article is part of a large-scale study on low-speed crash testing. The research problem concerned the influence of the seat backrest angle on the head displacement during a low-speed collision. The article compares the displacement of the head of the KPSIT C50 dummy during a series of crash tests, where the angle of the car seat backrest was changed. On the basis of the research, it was found that the optimal angle of the car seat backrest is 110 degrees. In addition, a preliminary analysis of the displacements of the dummy's head showed a high risk of whiplash injury in people sitting in a fully reclined seat. [ABSTRACT FROM AUTHOR]

Due to the complexity of the automobile manufacturing process, some flexible and delicate assembly work relies on manual operations. However, high-frequency and high-load repetitive operations make assembly workers prone to physical fatigue. This study proposes a method for evaluating human physical fatigue for the manual assembly of automobiles with methods: NIOSH (National Institute for Occupational Safety and Health), OWAS (Ovako Working Posture Analysis System) and RULA (Rapid Upper Limb Assessment). The cerebral oxygenation signal is selected as an objective physiological index reflecting the human fatigue level to verify the proposed physical fatigue evaluation method. Taking auto seat assembly and automobile manual assembly as an example, 18 group experiments were carried out with the ARE platform (Augmented Reality-based Ergonomic Platform). Furthermore, predictions of metabolic energy expenditure were performed for experiments in Tecnomatix Jack. Finally, it is concluded that the proposed physical fatigue evaluation method can reflect the human physical fatigue level and is more accurate than the evaluation of metabolic energy consumption in Tecnomatix Jack because of the immersion that comes with the AR devices and the precision that comes with motion capture devices. [ABSTRACT FROM AUTHOR]

The automotive industry and scientific community are making efforts to develop innovative solutions that would increase successful driver performance in preventing crashes caused by drivers' health and concentration. High stress is one of the causes of impaired driver performance. This study investigates the ability to classify different stress levels based on capacitive electrocardiogram (cECG) recorded during driving by unobtrusive acquisition systems with different hardware implementations. The proposed machine-learning model extracted only four features, based on the detection of the R peak, which is the most reliably detected characteristic point even in inferior quality cECG. Another criterion for selecting the features is their low computational complexity, which enables real-time application. The proposed method was validated on three open data sets recorded during driving: electrocardiogram (ECG) recorded by electrodes with direct skin contact (high quality); cECG recorded without direct skin contact through clothes by electrodes built into a portable multi-modal cushion (middle quality); and cECG recorded through the clothes without direct skin contact by electrodes built into a car seat (lowest quality). The proposed model achieved a high accuracy of 100% for high-quality ECG, 96.67% for middle-quality cECG, and 98.08% for the lower-quality cECG. [ABSTRACT FROM AUTHOR]

The present study contains an experimental analysis of the vibratory response in a low-cylinder engine motorcycle at varying suspension preloads. Three different speed bumps of varying heights were used to subject the motorcycle to different vibrations. The analysis was carried out in three domains: time, frequency, and time-frequency. A triaxial accelerometer was used to measure the vibrations at the seat of the vehicle. The results indicated that the suspension system became more differentiated as the height of the bumps increased. However, for lower bumps, the action of the three spring preloads studied was quite similar. Quantitatively, only the higher bump showed a significant difference between the set preloads. The spectral distribution revealed that the frequency of interest was below 20 Hz for all the studied cases, which is in the same range of human body natural frequencies. The findings of this research can be utilized to enhance the design of low-cost motorcycles, thereby improving the safety and comfort of their drivers and passengers. This study constitutes a significant step towards developing an affordable system capable of gathering sufficient data to support the creation of evidence-based public health policies and propose new transport industry standards based on field measurements. [ABSTRACT FROM AUTHOR]

This study investigated the squeal mechanism induced by friction in a lead screw system. The dynamic instability in the friction noise model of the lead screw was derived through a complex eigenvalue analysis via a finite element model. A two degree of freedom model was described to analyze the closed solutions generated in the lead screw, and the friction noise sensitivity was examined. The analysis showed that the main source of friction noise in the lead screw was the bending mode pair, and friction-induced instability occurred when the ratio of the stiffness of the bending pair modes was 0.9–1. We also built an architecture to predict multiple outputs from a single model using deep neural networks and demonstrated that friction-induced instability can be predicted by deep neural networks. In particular, instability with nonlinearity was predicted very accurately by deep neural networks with a maximum absolute difference of about 0.035. [ABSTRACT FROM AUTHOR]

As an advanced driver assistance system, automatic emergency braking (AEB) can effectively reduce accidents by using high-precision and high-coverage sensors. In particular, it has a significant advantage in reducing front-end collisions and rear-end accidents. Unfortunately, avoiding side collisions is a challenging problem for AEB. To tackle these challenges, we propose active seat belt pretensioning on driver injury in vehicles equipped with AEB in unavoidable side crashes. Firstly, records of impact cases from China's National Automobile Accident In-Depth Investigation System were used to investigate a scenario in which a vehicle is impacted by an oncoming car after the vehicle's AEB system is triggered. The scenario was created using PreScan software. Then, the simulated vehicles in the side impact were devised using a finite element model of the Toyota Yaris and a moving barrier. These were constructed in HyperMesh software along with models of the driver's side seatbelt, side airbag, and side curtain airbag. Moreover, the models were verified, and driver out-of-position instances and injuries were evaluated in simulations with different AEB intensities up to 0.7 g for three typical side impact angles. Last but not least, the optimal combination of seatbelt pretensioning and the timing thereof for minimizing driver injury at each side impact angle was identified using orthogonal tests; immediate (at 0 ms) pretensioning at 80 N was applied. Our experiments show that our active seatbelt with the above parameters reduced the weighted injury criterion by 5.94%, 22.05%, and 20.37% at impact angles of 90°, 105°, and 120°, respectively, compared to that of a conventional seatbelt. The results of the experiment can be used as a reference to appropriately set the collision parameters of active seat belts for vehicles with AEB. [ABSTRACT FROM AUTHOR]

Ride comfort is one of the key issues in passenger transport. Its level depends on many factors related to both environmental factors and individual human characteristics. Ensuring good travel conditions translates into higher quality transport services. This article presents a literature review, which shows that ride comfort is most often considered in the context of the impact of mechanical vibrations on the human body, while other factors are usually neglected. The aim of this study was to conduct experimental studies that take into account more than one type of ride comfort. These studies concerned metro cars in the Warsaw metro system. Three types of comfort were evaluated: vibrational, thermal, and visual, based on vibration acceleration measurements, air temperature, relative air humidity, and illuminance. The ride comfort in the vehicle bodies' front, middle, and rear parts was tested under typical running conditions. The criteria for assessing the effect of individual physical factors on ride comfort were selected based on applicable European and international standards. The test results indicate good thermal and light environment conditions in every measuring point. The slight decrease in passenger comfort is undoubtedly due to the effects of vibrations occurring while mid journey. In tested metro cars, horizontal components have a more significant impact on reducing vibration comfort than other components. [ABSTRACT FROM AUTHOR]

Since drunk driving poses a significant threat to road traffic safety, there is an increasing demand for the performance and dependability of online drunk driving detection devices for automobiles. However, the majority of current detection devices only contain a single sensor, resulting in a low degree of detection accuracy, erroneous judgments, and car locking. In order to solve the problem, this study firstly designed a sensor array based on the gas diffusion model and the characteristics of a car steering wheel. Secondly, the data fusion algorithm is proposed according to the data characteristics of the sensor array on the steering wheel. The support matrix is used to improve the data consistency of the single sensor data, and then the adaptive weighted fusion algorithm is used for multiple sensors. Finally, in order to verify the reliability of the system, an online intelligent detection device for drunk driving based on multi-sensor fusion was developed, and three people using different combinations of drunk driving simulation experiments were conducted. According to the test results, a drunk person in the passenger seat will not cause the system to make a drunk driving determination. When more than 50 mL of alcohol is consumed and the driver is seated in the driver's seat, the online intelligent detection of drunk driving can accurately identify drunk driving, and the car will lock itself as soon as a real-time online voice prompt is heard. This study enhances and complements theories relating to data fusion for online automobile drunk driving detection, allowing for the online identification of drivers who have been drinking and the locking of their vehicles to prevent drunk driving. It provides technical support for enhancing the accuracy of online systems that detect drunk driving in automobiles. [ABSTRACT FROM AUTHOR]

We propose urethane-foam-embedded silicon pressure sensors, including a stress-concentration packaging structure, for integration into a car seat to monitor the driver's cognitive state, posture, and driving behavior. The technical challenges of embedding silicon pressure sensors in urethane foam are low sensitivity due to stress dispersion of the urethane foam and non-linear sensor response caused by the non-uniform deformation of the foam. Thus, the proposed package structure includes a cover to concentrate the force applied over the urethane foam and frame to eliminate this non-linear stress because the outer edge of the cover receives large non-linear stress concentration caused by the geometric non-linearity of the uneven height of the sensor package and ground substrate. With this package structure, the pressure sensitivity of the sensors ranges from 0 to 10 kPa. The sensors also have high linearity with a root mean squared error of 0.049 N in the linear regression of the relationship between applied pressure and sensor output, and the optimal frame width is more than 2 mm. Finally, a prototype 3 × 3 sensor array included in the proposed package structure detects body movements, which will enable the development of sensor-integrated car seats. [ABSTRACT FROM AUTHOR]

Presently, most passive safety tests are performed with a precisely specified seat position and carefully seated ATD (anthropomorphic test device) dummies. Facing the development of autonomous vehicles, as well as the need for safety verification during crashes with various seat positions such research is even more urgently needed. Apart from the numerical environment, the existing testing equipment is not validated to perform such an investigation. For example, ATDs are not validated for nonstandard seatback positions, and the most accurate method of such research is volunteer tests. The study presented here was performed on a sled test rig utilizing a 50cc Hybrid III dummy according to a full factorial experiment. In addition, input factors were selected in order to verify a safe test condition for surrogate testing. The measured value was head acceleration, which was used for calculation of a head injury criterion. What was found was an optimal seat angle −117°—at which the head injury criteria had the lowest represented value. Moreover, preliminary body dynamics showed a danger of whiplash occurrence for occupants in a fully-reclined seat. [ABSTRACT FROM AUTHOR]

Professional drivers need constant attention during long driving periods and sometimes perform tasks outside the truck. Driving discomfort may justify inattention, but it does not explain post-driving accidents outside the vehicle. This study aims to study the discomfort developed during driving by analysing modified preferred postures, pressure applied at the interface with the seat, and changes in pre- and post-driving gait patterns. Each of the forty-four volunteers drove for two hours in a driving simulator. Based on the walking speed changes between the two gait cycles, three homogeneous study groups were identified. Two groups performed faster speeds, while one reduced it in the post-steering gait. While driving, the pressure at the interface and the area covered over the seat increased throughout the sample. Preferred driving postures differed between groups. No statistical differences were found between the groups in the angles between the segments (flexed and extended). Long-time driving develops local or whole-body discomfort, increasing interface pressure over time. While driving, drivers try to compensate by modifying their posture. After long steering periods, a change in gait patterns can be observed. These behaviours may result from the difficulties imposed on blood circulation by increasing pressure at this interface. [ABSTRACT FROM AUTHOR]

Background: The growth of the number of vehicles in traffic has led to an exponential increase in the number of road accidents with many negative consequences, such as loss of lives and pollution. Methods: This article focuses on using a new technology in automotive electronics by equipping a semi-autonomous vehicle with a complex sensor structure that is able to provide centralized information regarding the physiological signals (Electro encephalogram—EEG, electrocardiogram—ECG) of the driver/passengers and their location along with indoor temperature changes, employing the Internet of Things (IoT) technology. Thus, transforming the vehicle into a mobile sensor connected to the internet will help highlight and create a new perspective on the cognitive and physiological conditions of passengers, which is useful for specific applications, such as health management and a more effective intervention in case of road accidents. These sensor structures mounted in vehicles will allow for a higher detection rate of potential dangers in real time. The approach uses detection, recording, and transmission of relevant health information in the event of an incident as support for e-Call or other emergency services, including telemedicine. Results: The novelty of the research is based on the design of specialized non-invasive sensors for the acquisition of EEG and ECG signals installed in the headrest and backrest of car seats, on the algorithms used for data analysis and fusion, but also on the implementation of an IoT temperature measurement system in several points that simultaneously uses sensors based on MEMS technology. The solution can also be integrated with an e-Call system for telemedicine emergency assistance. Conclusion: The research presents both positive and negative results of field experiments, with possible further developments. In this context, the solution has been developed based on state-of-the-art technical devices, methods, and technologies for monitoring vital functions of the driver/passengers (degree of fatigue, cognitive state, heart rate, blood pressure). The purpose is to reduce the risk of accidents for semi-autonomous vehicles and to also monitor the condition of passengers in the case of autonomous vehicles for providing first aid in a timely manner. Reported abnormal values of vital parameters (critical situations) will allow interveneing in a timely manner, saving the patient's life, with the support of the e-Call system. [ABSTRACT FROM AUTHOR]

This paper deals with the issues of the impact of vertical vibrations on a child seated in a child seat during a journey. Its purpose was to assess the impact of fastening the child seats and road conditions on the level of vibrations recorded on child seats. The paper describes the tested child seats, the methodology of the tests and the test apparatus included in the measuring track. The tests were carried out in real road conditions where the child seats were located on the rear seat of a passenger vehicle. One was attached with standard seat belts, and the other with the ISOFIX base. When driving on roads with three types of surface, the following vertical accelerations were measured: seat of the child seats, the rear seat of the vehicle and the ISOfix base. The recorded accelerations were first analyzed in the time domain and then in the frequency domain. Three indexes (r.m.s, rmq and VDV) were used to assess the vibration comfort. Research has shown that the classic method of fastening a child seat with standard seat belts is more advantageous in terms of vibration comfort. Calculated indicators confirmed the negative impact of separating the child seat from the rear seat of the vehicle using the IQ ISOFIX base. [ABSTRACT FROM AUTHOR]

The seat comfort of automobiles is one of the significant factors for determining the driver's fatigue, emotional experience, and individual space (which captures their individuality, rather than just a means of transportation in modern society). Conventional automobile seats could not provide seating comfort suitable for all drivers, in the form of seats that fit each driver's body type and the difficulty of meeting individual needs. This study proposes self-shape adjustable (the SSA seats) seats that improve the sitting comfort, safety, and secure the stability, by adjusting shape fit to the driver's body type. The SSA seats transforms the seat itself, in a way that improves the distribution of contact pressure and reduces sitting fatigue, with the pneumatic system. The transformed seats provide better sitting comfort and safety than the conventional automobile seat, by providing a seat shape suitable for the body shape of all users. It was verified that the SSA seats, proposed in this paper, have a uniform and improved pressure distribution, compared to the conventional seat, in various sitting postures; the contact area between the seat and user is enlarged, and the pressure concentrated on the ischial bone is lowered. In addition, it was proven (through user evaluation) that quantitative evaluation verification was the same as qualitative evaluation results. [ABSTRACT FROM AUTHOR]

Highly sensitive and flexible composite sensors with pressure and temperature sensing abilities are of great importance in human motion monitoring, robotic skins, and automobile seats when checking the boarding status. Several studies have been conducted to improve the temperature-pressure sensitivity; however, they require a complex fabrication process for micro-nanostructures, which are material-dependent. Therefore, there is a need to develop the structural designs to improve the sensing abilities. Herein, we demonstrate a flexible composite with an enhanced pressure and temperature sensing performance. Its structural design consists of a multilayered composite construction with an elastic modulus gradient. Controlled stress concentration and distribution induced by a micropatterned structure between the layers improves its pressure and temperature sensing performance. The proposed composite sensor can monitor a wide range of pressure and temperature stimuli and also has potential applications as an automotive seat sensor for simultaneous human temperature detection and occupant weight sensing. [ABSTRACT FROM AUTHOR]

The capacitive electrocardiograph (cECG) has been tested for several measurement scenarios, including hospital beds, car seats and chairs since it was first proposed. The inferior signal quality of the cECG compared to the gold standard ECG guides the ongoing research in the direction of out-of-hospital applications, where unobtrusiveness is sought and high-level diagnostic signal quality is not essential. This study aims to expand the application range of cECG not in terms of the measurement scenario but in the profile of the subjects by including subjects with implanted cardiac pacemakers. Within this study, 20 patients with cardiac pacemakers were recruited during their clinical device follow-up and cECG measurements were conducted using a seat equipped with integrated cECG electrodes. The multichannel cECG recordings of active unipolar and bipolar pacemaker stimulation were analyzed offline and evaluated in terms of F β scores using a pacemaker spike detection algorithm. F β scores from 3652 pacing events, varying from 0.62 to 0.78, are presented with influencing parameters in the algorithm and the comparison of cECG channels. By tuning the parameters of the algorithm, different ranges of F β scores were found as 0.32 to 0.49 and 0.78 to 0.88 for bipolar and unipolar stimulations, respectively. For the first time, this study shows the feasibility of a cECG system allowing health monitoring in daily use on subjects wearing cardiac pacemakers. [ABSTRACT FROM AUTHOR]

This paper focuses on a thorough summary of vital function measuring methods in vehicles. The focus of this paper is to summarize and compare already existing methods integrated into car seats with the implementation of inter alia capacitive electrocardiogram (cECG), mechanical motion analysis Ballistocardiography (BCG) and Seismocardiography (SCG). In addition, a comprehensive overview of other methods of vital sign monitoring, such as camera-based systems or steering wheel sensors, is also presented in this article. Furthermore, this work contains a very thorough background study on advanced signal processing methods and their potential application for the purpose of vital sign monitoring in cars, which is prone to various disturbances and artifacts occurrence that have to be eliminated. [ABSTRACT FROM AUTHOR]