It has become increasingly important to monitor drivers’ negative emotions during driving to prevent accidents. Despite drivers’ anxiety being critical for safe driving, there is a lack of systematic approaches to detect anxiety in drivin...
Affective computing and stress recognition from biosignals have a high potential in various medical applications such as early intervention, stress management and risk prevention, as well as monitoring individuals’ mental health. This paper pre...
Background: Pain remains one of the most debilitating and prevalent symptoms in cancer patients. However, assessment based solely on subjective self-report tools is limited by cognitive impairment and the heterogeneous nature of cancer pain. Since ev...
Biosignal-based technology has been increasingly available in our daily life, being a critical information source. Wearable biosensors have been widely applied in, among others, biometrics, sports, health care, rehabilitation assistance, and edutainm...
Nowadays, some of the most severe problems faced by health institutions are related to people’s mental health. According to the World Health Organization, approximately one billion people lived with a condition that affected their mental health...
During the last decade, new technological tools have emerged to provide first responders with augmented senses in emergency and disaster situations. Some of these tools focus on providing extra information about their surroundings. However, despite a...
The increase in the number of adolescents with internet gaming disorder (IGD), a type of behavioral addiction is becoming an issue of public concern. Teaching adolescents to suppress their craving for gaming in daily life situations is one of the cor...
Occupational disorders considerably impact workers’ quality of life and organizational productivity, and even affect mortality worldwide. Such health issues are related to mental health and ergonomics risk factors. In particular, mental health...
Perception and expression of pain in cancer patients are influenced by distress levels, tumor type and progression, and the underlying pathophysiology of pain. Relying on traditional pain assessment tools can present limitations due to the highly sub...
Physiological information such as respiratory rate and heart rate in the sleep state can be used to evaluate the health condition of the sleeper. Traditional sleep monitoring systems need body contact and are intrusive, which limits their applicabili...
The main objective of this project was to develop a remote monitoring solution using an open-source platform, the e-health platform V2.0, which served as the foundation for this solution due to its capability to integrate various tools and technologi...
Enhanced understanding and control of electrophysiology mechanisms are increasingly being hailed as key knowledge in the fields of modern biology and medicine. As more and more excitable cell mechanics are being investigated and exploited, the need f...
This paper demonstrates the advantages of the multiple-input transconductor (MI-Gm) in filter application, in terms of topology simplification, increasing filter functions, and minimizing the count of needed active blocks and their consumed power. Fu...
Visual biosignals can be used to analyze human behavioral activities and serve as a primary resource for Facial Expression Recognition (FER). FER computational systems face significant challenges, arising from both spatial and temporal effects. Spati...
With the development of mobile and wearable devices with biosensors, various healthcare services in our life have been recently introduced. A significant issue that arises supports the smart interface among bio-signals developed by different vendors...
Artificial Intelligence (AI) has broadly connected the medical field at various levels of diagnosis based on the congruous data generated. Different types of bio-signal can be used to monitor a patient’s condition and in decision making. Medica...
A critical challenge to using longitudinal wearable sensor biosignal data for healthcare applications and digital biomarker development is the exacerbation of the healthcare “data deluge,” leading to new data storage and organization chal...
To measure biosignals constantly, using textile-integrated or even textile-based electrodes and miniaturized electronics, is ideal to provide maximum comfort for patients or athletes during monitoring. While in former times, this was usually solved b...
Body temperature and bio-signals are important health indicators that reflect the human health condition. However, monitoring these indexes is inconvenient and time-consuming, requires various instruments, and needs professional skill. In this study,...
1 September 2021
We evaluated new features from biosignals comprising diverse physiological response information to predict the outcome of weaning from mechanical ventilation (MV). We enrolled 89 patients who were candidates for weaning from MV in the intensive care...
Human bio-signal fusion is considered a critical technological solution that needs to be advanced to enable modern and secure digital health and well-being applications in the metaverse. To support such efforts, we propose a new data-driven digital t...
As a definition, Human–Machine Interface (HMI) enables a person to interact with a device. Starting from elementary equipment, the recent development of novel techniques and unobtrusive devices for biosignals monitoring paved the way for a new class...
Previous studies to recognize negative emotions for mental healthcare have used heavy equipment directly attaching electroencephalogram (EEG) electrodes to the head, and they have proposed binary classification methods to identify negative emotions....
This work presents a novel approach to detecting stress differences between experts and novices in Situation Awareness (SA) tasks during maritime navigation using one type of wearable sensor, Empatica E4 Wristband. We propose that for a given workloa...
Multimodal bio-signals acquisition based on wearable devices and using virtual reality (VR) as stimulus source are promising techniques in emotion recognition research field. Numerous studies have shown that emotional states can be better evoked thro...
A low power and low noise reconfigurable analog front-end (AFE) system on a chip (SoC) for biosignal acquisition is presented. The presented AFE can be reconfigured for use in electropotential, bioimpedance, electrochemical, and photoelectrical modes...
15 August 2018
Interest in research involving health-medical information analysis based on artificial intelligence, especially for deep learning techniques, has recently been increasing. Most of the research in this field has been focused on searching for new knowl...
Nowadays insight into human-machine interaction is a critical topic with the large-scale development of intelligent vehicles. Biosignal analysis can provide a deeper understanding of driver behaviors that may indicate rationally practical use of the...
Laser-direct writing (LDW) and magneto-rheological drawing lithography (MRDL) have been proposed for the fabrication of a flexible microneedle array electrode (MAE) for wearable bio-signal monitoring. Conductive patterns were directly written onto th...
Anxiety disorder (AD) is a major mental health illness. However, due to the many symptoms and confounding factors associated with AD, it is difficult to diagnose, and patients remain untreated for a long time. Therefore, researchers have become incre...
Background: Functional dyspepsia (FD) is a common functional gastrointestinal disorder characterized by chronic digestive symptoms without identifiable structural abnormalities. FD affects approximately 8–46% of the population, leading to signi...
The roles of emergency responders are challenging and often physically demanding, so it is essential that their duties are performed safely and effectively. In this article, we address real-time bio-signal sensor monitoring for responders in disaster...
Research on real-time health systems have received great attention during recent years and the needs of high-quality personal multichannel medical signal compression for personal medical product applications are increasing. The international MPEG-4 a...
Entropy estimation metrics have become a widely used method to identify subtle changes or hidden features in biomedical records. These methods have been more effective than conventional linear techniques in a number of signal classification applicati...
Clinicians and researchers divide sleep periods into different sleep stages to analyze the quality of sleep. Despite advances in machine learning, sleep-stage classification is still performed manually. The classification process is tedious and time-...
Stress is a natural yet potentially harmful aspect of human life, necessitating effective management, particularly during overwhelming experiences. This paper presents a scoping review of personalized stress detection models using wearable technology...
Many people suffer from high mental workload which may threaten human health and cause serious accidents. Mental workload estimation is especially important for particular people such as pilots, soldiers, crew and surgeons to guarantee the safety and...
Carbon nanotubes (CNTs) and graphene have commonly been applied as the sensitive layer of strain sensors. However, the buckling deformation of CNTs and the crack generation of graphene usually leads to an unsatisfactory strain sensing performance. In...
This paper introduces a novel method for emotion classification within virtual reality (VR) environments, which integrates biosignal processing with advanced machine learning techniques. It focuses on the processing and analysis of electrocardiograph...
The evaluation of driver workload in the lead vehicle of a driver-following autonomous truck platoon was conducted using bio-signal analysis. In this study, a single driver operated the lead vehicle while the second and third trucks followed autonomo...
Applying the data encryption method used in conventional personal computers (PC) to wireless communication devices such as IoT is not trivial. Because IoT equipment is extremely slow in transferring data and has a small hardware area compared with PC...
Sepsis continues to be challenging to diagnose due to its non-specific clinical signs and symptoms, emphasizing the importance of early detection. Our study aimed to enhance the accuracy of sepsis diagnosis by integrating multimodal monitoring techno...
As non-invasive continuous blood pressure monitoring (NCBPM) has gained wide attraction in the recent decades, many pulse arrival time (PAT) or pulse transit time (PTT) based blood pressure (BP) estimation studies have been conducted. However, most o...
This study aims to predict emotions using biosignals collected via wrist-worn sensor and evaluate the performance of different prediction models. Two dimensions of emotions were considered: valence and arousal. The data collected by the sensor were u...
In the present study, we used a transformer model and a fusion of biosignals to estimate rotational acceleration in elbow and shoulder joints. To achieve our study objectives, we proposed a mechanomyography (MMG) signal isolation technique based on a...
Recently, the application of bio-signals in the fields of health management, human–computer interaction (HCI), and user authentication has increased. This is because of the development of artificial intelligence technology, which can analyze bi...
Monitoring multiple biosignals, such as heart rate, respiration cycle, and weight transitions, contributes to the health management of individuals. Specifically, it is possible to measure multiple biosignals using load information obtained through co...
User authentication has traditionally been performed using methods such as passwords or fingerprints. However, passwords have security vulnerabilities, and fingerprints may hinder user convenience. To address these issues, a novel user authentication...
In this paper, interpersonal coordination is studied by analyzing physiological synchronization between individuals. To this end, a four-phase protocol is proposed to collect biosignals from the participants in each dyad. Then, the time evolution of...
Currently, mental stress is a major problem in our society. It is related to a wide variety of diseases and is mainly caused by daily-life factors. The use of mobile technology for healthcare purposes has dramatically increased during the last few ye...
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