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Biosignals - Science topic
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Publications related to Biosignals (4,411)
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Photoplethysmography (PPG) is the most widely used non-invasive technique for monitoring biosignals and cardiovascular health, with applications in both clinical settings and consumer health through wearable devices. Current machine learning models trained on PPG signals are mostly task-specific and lack generalizability. Previous works often used...
Electromyography (EMG) stands out as an accessible and inexpensive method for identifying muscle contractions on the surface and within deeper muscle tissues. Using specialized electronic circuits for amplification and filtering can help develop simple but effective systems for detecting and analyzing these signals. However, EMG devices developed b...
Contrastive learning yields impressive results for self-supervision in computer vision. The approach relies on the creation of positive pairs, something which is often achieved through augmentations. However, for multivariate time series effective augmentations can be difficult to design. Additionally, the number of input channels for biosignal dat...
Bioelectrical signal measurements play a crucial role in clinical diagnosis and continuous health monitoring. Conventional wet electrodes, however, present limitations as they are conductive gel for skin irritation and/or have inflexibility. Here, we developed a cost-effective and user-friendly stretchable dry electrode constructed with a flexible...
Background
Ubiquitination plays a key role in various cancers, and F-box and WD repeat domain containing 7 (FBW7) is a tumor suppressor that targets several cancer-causing proteins for ubiquitination. This paper set out to pinpoint the role of FBW7 in hepatocellular carcinoma (HCC).
Methods
The target proteins of FBW7 and the expression of hromodo...
Introduction. Immersive virtual reality applications in areas such as gaming, training, and neurorehabilitation are growing in popularity. While most applications aim for maximal realism, simplifying the virtual environment might bring several advantages, such as a reduction in users’ mental workload, potentially promoting learning and neurorehabil...
Objective
Recent evidence suggests that disturbances of sleep architecture are linked to Alzheimer’s disease (AD) pathology. Here, we assessed the association between sleep architecture and regional amyloid and tau pathology employing a portable sleep-monitoring device in addition to PET imaging.
Methods
18 cognitively normal adults (CN; M(Age) =...
Auscultation of the heart and the electrocardiogram (ECG) are two central components of the cardiac exam. Recent innovations of the stethoscope have enabled the simultaneous acquisition of a high-quality digital acoustic signal and ECG. We present foundation models trained on phonocardiogram (PCG) and ECG data collected from digital stethoscopes du...
With the acceleration of global population aging, the elderly have an increasing demand for home care and nursing institutions, and the significance of health prevention and management of the elderly has become increasingly prominent. In this context, we propose a biometric recognition method for multi-modal biomedical signals. This article focuses...
Polymer nanoparticles that can sharply sense and detect biological signals in cells are promising candidates for biomedical and theranostic nanomaterials. However, the response ability of current polymer assemblies poorly matches the requirement of trace concentration level (10⁻⁶ ~ 10−9 mol/L) of cellular biosignals due to their linear signal input...
Objective
Wearable nonelectroencephalographic biosignal recordings captured from the wrist offer enormous potential for seizure monitoring. However, signal quality remains a challenging factor affecting data reliability. Models trained for seizure detection depend on the quality of recordings in peri‐ictal periods in performing a feature‐based sepa...
In recent decades, research on mechanotransduction has advanced considerably, focusing on the effects of audible acoustic waves (AAWs) and low-vibration stimulation (LVS), which has propelled the field of sonobiology forward. Taken together, the current evidence demonstrates the influence of these biosignals on key cellular processes, such as growt...
Remote physical activity recognition is gaining popularity as it provides improved healthcare monitoring services without hampering the daily lifestyle of individuals. For smart healthcare, several wearable sensors i.e., inertial measurement unit (IMU), mechanomyography (MMG), electromyography (EMG) and other biosignal devices are used commonly to...
End-effector based assistive robots face persistent challenges in generating smooth and robust trajectories when controlled by human's noisy and unreliable biosignals such as muscle activities and brainwaves. The produced endpoint trajectories are often jerky and imprecise to perform complex tasks such as stable robotic grasping. We propose STREAMS...
Commercial wearable biosignal sensing technologies encounter challenges associated with irritation or discomfort caused by unwanted objects in direct contact with the skin, which can discourage the widespread adoption of wearable devices. To address this issue, we propose a fabric-based lamina emergent MXene-based electrode, a lightweight and flexi...
Organic electrochemical transistors could be used in in-sensor computing and wearable healthcare applications. However, they lack the conformity and stretchability needed to minimize mechanical mismatch between the devices and human body, are challenging to fabricate at a scale with small feature sizes and high density, and require miniaturized rea...
The research poster introduces a new method for classifying chronic lower back pain (CLBP) using biosignals, specifically surface electromyography (sEMG) and inertial measurement unit (IMU) data. The study aims to improve CLBP detection and monitoring by introducing neuromorphic computing techniques to address the limitations of current methods, su...
We present an update on the EAVI physiological interface, a wireless, microcontroller based hardware design for the acquisition of bioelectrical signals. The system has been updated to process electroencephalogram brain signals in addition to muscle electromyogram. The hardware/firmware system interfaces with host software carrying out feature extr...
Barkground
Circular RNAs (circRNAs) play important regulatory roles in a variety of biological processes in mammals. Multiple birth-traits in goats are affected by several factors, but the expression and function of circRNAs in follicular development of goats are not clear. In this study, we aimed to investigate the possible regulatory mechanisms o...
Dental, oral, and craniofacial diseases jeopardize health and reduce the quality of life. Accessing disease-related signals in advance is beneficial to prevent the occurrence or progression of those diseases. However, the inconvenience of periodical in-hospital examinations and the difficulty of sustaining daily health monitoring challenge personal...
Researchers have attempted to control robotic hands and prostheses through biosignals but could not match the human hand. Surface electromyography records electrical muscle activity using non-invasive electrodes and has been the primary method in most studies. While surface electromyography-based hand motion decoding shows promise, it has not yet m...
Advances in bioinformatics are primarily due to new algorithms for processing diverse biological data sources. While sophisticated alignment algorithms have been pivotal in analyzing biological sequences, deep learning has substantially transformed bioinformatics, addressing sequence, structure, and functional analyses. However, these methods are i...
We collected biosignals from 63 participants and extracted the features corresponding to each level of exerted muscle force. Data were classified into typical and atypical patterns. Data analysis was performed using the Linear Latent Curve Model (LCM) and the Conditional Linear LCM. The typical patterns demonstrated a high degree of fit. Factors, s...
Background: Traditional physical rehabilitation involves participants performing repetitive body movements with the assistance of physiotherapists. Owing to the exercises’ monotonous nature and lack of reward, participants may become disinterested and cease their recovery. Games could be used as tools to engage participants in the rehabilitation pr...
Dental, oral, and craniofacial diseases can substantially impact the quality of human life, thereby posing a serious public health concern. Although conventional therapies such as surgery have solved these problems largely, the prognosis of patients is not always satisfactory. Cell membrane-coated nanoparticles (CMCNPs) carry nanodrugs with the hel...
Biosignal acquisition is key for healthcare applications and wearable devices, with machine learning offering promising methods for processing signals like surface electromyography (sEMG) and electroencephalography (EEG). Despite high within-session performance, intersession performance is hindered by electrode shift, a known issue across modalitie...
Global stress is widespread in today’s post-pandemic world of political and economic uncertainty. Vibroacoustic technology is a vibrotactile intervention with multiple uses, but its impact on stress lacks interpretation. This research assessed if the vibroacoustic technology of a Vibroacoustic Sound Massage (VSM) can reduce psychological, physiolog...
Biosignal interfaces, using sensors in, on, or around the body, promise to enhance wearables interaction and improve device accessibility for people with motor disabilities. However, biosignals are multi-modal, multi-dimensional, and noisy, requiring domain expertise to design input features for gesture classifiers. The \$B-recognizer enables mid-a...
In the rapidly evolving field of life sciences and biomedicine, detecting low‐abundance biomolecules, and ultraweak biosignals presents significant challenges. This has spurred a rapid development of analytical techniques aiming for increased sensitivity and specificity. These advancements, including signal amplification strategies and the integrat...
The present study focuses on the design and construction of an innovative device aimed at identifying plantar foot conditions, such as normal, cavus, and flat feet, through the analysis of biosignals. The device was based on two identification methods: the plantar footprint test and the use of a template equipped with digital and analog sensors mad...
Recent advancements in artificial intelligence (AI) technologies, particularly machine learning (ML) techniques, have opened up a promising frontier in the development of intelligent soft bioelectronics, demonstrating unparalleled performance in interfacing with the human body. Hydrogels, owing to their unique combination of biocompatibility, tunab...
This article introduces a cost-effective gateway into the fascinating world of neuroscience: the PIEEG-16, a versatile shield for RaspberryPi designed to measure 16 channels of various biosignals, including EEG (electroencephalography), EMG (electromyography), and ECG (electrocardiography) without any data transfer over the network (Wi-Fi, Bluetoot...
Lignin‐based carbon nanomaterials offer several advantages, including biodegradability, biocompatibility, high specific surface area, ease of functionalization, low toxicity, and cost‐effectiveness. These materials show promise in biochemical sensing applications, particularly in the detection of metal ions, organic compounds, and human biosignals....
Arm and hand function play a critical role in the successful completion of everyday tasks. Lost function due to neurological impairment impacts millions of lives worldwide. Despite improvements in the ability to assess and rehabilitate arm deficits, knowledge about underlying sources of impairment and related sequela remains limited. The comprehens...
Continuous monitoring of electrophysiological biosignals such as electrocardiogram (ECG) and bioimpedance (BioZ) rely on gel‐based electrodes and adhesive skin interfaces requiring active patient interaction inherently restricting chronic use. Current solutions aimed at addressing seamless, comfortable, and reliable recordings with dry electrodes u...
The World Health Organisation (WHO) reports that diabetes affects roughly 180 million people worldwide and that cardiovascular illnesses account for nearly 30% of all fatalities worldwide. Applications involving radio frequency (RF) or microwave technology are crucial to medical diagnosis and illness prevention. The most recent developments in the...
The object of this study is a wireless local Wi-Fi network for broadcasting biomedical signals, its structure, and principles of construction. The task of minimizing the power consumption of a Wi-Fi transmitter has been addressed, which provides the possibility of building a wireless system for long-term monitoring of biomedical signals. As a resul...
By generating synthetic biosignals, the quantity and variety of health data can be increased. This is especially useful when training machine learning models by enabling data augmentation and introduction of more physiologically plausible variation to the data. For these purposes, we have developed a synthetic biosignal model for two signal modalit...
Here, we report an ultrasoft extra long-lasting, reusable hydrogel-based sensor that enables high-quality electrophysiological recording with low-motion artifacts. The developed sensor can be used and stored in an ambient environment for months before being reused. The developed sensor is made of a self-adhesive electrical-conductivity-enhanced ult...
Exceptionally preserved feathers from the Mesozoic era have provided valuable insights into the early evolution of feathers and enabled colour reconstruction of extinct dinosaurs, including early birds. Mounting chemical evidence for the two key components of feathers–keratins and melanins - in fossil feathers has demonstrated that exceptional pres...
We introduce the concept of LabLinking: a technology-based interconnection of experimental laboratories across institutions, disciplines, cultures, languages, and time zones - in other words human studies and experiments without borders. In particular, we introduce a theoretical framework of LabLinking, describing multiple dimensions of conceptual,...
The present manuscript reports on the progress made toward the official announcement of the first World Conference on Cellular Communication and Signaling. This conference is made possible by the Association for research on biosignaling and communication initiative, which was originally launched in 2020 and revitalized during the 12th International...
In response to the global safety concern of drowsiness during driving, the European Union enforces that new vehicles must integrate detection systems compliant with the general data protection regulation. To identify drowsiness patterns while preserving drivers’ data privacy, recent literature has combined Federated Learning (FL) with different bio...
One of the most important problems in virtual environments (VEs) is the difficulty users face when trying to deal with increasingly complex systems. Thus, giving machines the ability to understand human emotions would make interactions easier and more reliable. By using an EEG device as a biosignal sensor, the human emotional state can be modeled a...
The Artificial Intelligence (AI) and Machine Learning (ML) fields provide us with the knowledge of brain function, improving early identification and treat various neurological disorders. The importance of AI/ML in brain-computer interface is to improve techniques for gathering knowledge, evaluating, and preventing neurological diseases. ML has bee...
Traditional analog front-ends for biomedical signal acqui- Non-Linear Element sitions operate at very low frequencies (Hz-range) and are severely affected by flicker and environmental noise, which degrade the quality of low-frequency signals, thereby reducing the signal-to-noise ratio. While offering advantages, the increasingly common use of micro...
Background:
Intraoperative functional mapping for glioma resection often necessitates awake craniotomies, requiring active patient participation. This procedure presents challenges for both the surgical team and the patient. Thus, minimizing mapping time becomes crucial. Passive mapping utilizing electrocorticography (ECoG) presents a promising ap...
Affective computing enables computers to recognize and respond to human emotions and cognitive states using multimodal state recognition. This chapter explores cognitive load estimation through a machine learning life cycle, addressing data collection and preparation, modeling, and deployment challenges. Experiments demonstrate effective unimodal a...
Myopotential pattern recognition to decode the intent of the user is the most advanced approach to controlling a powered bioprosthesis. Unfortunately, many factors make this a difficult problem and achieving acceptable recognition quality in real-word conditions is a serious challenge. The aim of the paper is to develop a recognition system that wi...
The analysis of biomedical signals is a very challenging task. This review paper is focused on the presentation of various methods where biomedical data, in particular vital signs, could be monitored using sensors mounted to beds. The presented methods to monitor vital signs include those combined with optical fibers, camera systems, pressure senso...
Machine learning applications on signals such as computer vision or biomedical data often face significant challenges due to the variability that exists across hardware devices or session recordings. This variability poses a Domain Adaptation (DA) problem, as training and testing data distributions often differ. In this work, we propose Spatio-Temp...
Here, we report an ultrasoft extra long-lasting reusable hydrogel-based sensor that enables high quality electrophysiological recording with low motion artifacts. The developed sensor can be used and stored in the ambient environment for months before being reused again. The developed sensor is made of a self-adhesive electrical-conductivity-enhanc...
Auscultation of the heart and the electrocardiogram (ECG) are two central components of the cardiac exam. Recent innovations of the stethoscope have enabled the simultaneous acquisition of a high-quality digital acoustic signal and single or three-lead ECG during a routine cardiac exam. We present foundation models trained on phonocardiogram (PCG)...
This paper presents the first application of spiking neural networks (SNNs) for the classification of chronic lower back pain (CLBP) using the EmoPain dataset. Our work has two main contributions. We introduce Spike Threshold Adaptive Learning (STAL), a trainable encoder that effectively converts continuous biosignals into spike trains. Additionall...
Biosensors have emerged as vital tools for the detection and monitoring of essential biological information. However, their efficiency is often constrained by limitations in the power supply. To address this challenge, energy harvesting systems have gained prominence. These off‐grid, independent systems harness energy from the surrounding environme...
Continuous monitoring of physiological signals from the human body is critical in health monitoring, disease diagnosis, and therapeutics. Despite the needs, the existing wearable medical devices rely on either bulky wired systems or battery-powered devices needing frequent recharging. Here, we introduce a wearable, self-powered, thermoelectric flex...
Understanding a person’s perceived quality of sleep is an important problem, but hard due to its poor definition and high intra- as well as inter-individual variation. In the short term, sleep quality has an established impact on cognitive function during the following day as well as on fatigue. In the long term, good quality sleep is essential for...