Research on Flexible Sensors for Wearable Devices: A Review

Nanomaterials, Journal Year: 2025, Volume and Issue: 15(7), P. 520 - 520

Published: March 30, 2025

With the development of new materials and trend miniaturization smart devices, wearable devices are playing an increasingly important role in people’s lives occupying a larger market share. Meanwhile, operation is based on flexible sensors inside them. Although has been very rapid more than 20 years since entering 21st century, facing booming demand at present, still faces many challenges such as miniaturization, higher integration, greater sustainability, high precision, efficient energy saving. This paper aims to summarize sensors, look forward future provide reference for researchers.

Language: Английский

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Digital health in chronic obstructive pulmonary disease

Chronic Diseases and Translational Medicine, Journal Year: 2023, Volume and Issue: 9(2), P. 90 - 103

Published: June 1, 2023

Chronic obstructive pulmonary disease (COPD) can be prevented and treated through effective care, reducing exacerbations hospitalizations. Early identification of individuals at high risk COPD exacerbation is an opportunity for preventive measures. However, many patients struggle to follow their treatment plans because a lack knowledge about the disease, limited access resources, insufficient clinical support. The growth digital health-which encompasses advancements in health information technology, artificial intelligence, telehealth, Internet Things, mobile health, wearable therapeutics-offers opportunities improving early diagnosis management COPD. This study reviewed field terms findings showed that despite significant advances there are still obstacles impeding its effectiveness. Finally, we highlighted some major challenges possibilities developing integrating management.

Language: Английский

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Advancements in Wearable EEG Technology for Improved Home-Based Sleep Monitoring and Assessment: A Review

Biosensors, Journal Year: 2023, Volume and Issue: 13(12), P. 1019 - 1019

Published: Dec. 7, 2023

Sleep is a fundamental aspect of daily life, profoundly impacting mental and emotional well-being. Optimal sleep quality vital for overall health yet many individuals struggle with sleep-related difficulties. In the past, polysomnography (PSG) has served as gold standard assessing sleep, but its bulky nature, cost, need expertise made it cumbersome widespread use. By recognizing more accessible user-friendly approach, wearable home monitoring systems have emerged. EEG technology plays pivotal role in monitoring, captures crucial brain activity data during serves primary indicator stages disorders. This review provides an overview most recent advancements leveraging technology. We summarize latest devices available scientific literature, highlighting their design, form factors, materials, methods assessment. exploring these developments, we aim to offer insights into cutting-edge technologies, shedding light on sensors advanced at-home comprehensive contributes broader perspective enhancing using sensors.

Language: Английский

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Meander Line Super-Wideband Radiator for Fifth-Generation (5G) Vehicles

Vehicles, Journal Year: 2024, Volume and Issue: 6(1), P. 242 - 255

Published: Jan. 23, 2024

Designing antennas for vehicular communication systems presents several unique challenges due to the dynamic nature of environments, mobility, and need reliable connectivity. A wider bandwidth is a critical requirement antennas. In this paper, super-wideband FR4 epoxy-based low-cost meander line patch antenna designed fifth-generation (5G) mobile frequency applications. The proposed excited through microstrip feedline on top substrate with continuous ground plane. implemented theoretical formula cover upper-5G range 1 (FR1) 2 (FR2). has 7.5 dBi peak gain when operated at 28 GHz. simulated ratio (BWR) 9.09:1 −10 dB reflection coefficient covering 53.4 GHz (6.6 60 GHz) range. linear planar structure, occupies small area 34 mm × 20 1.6 mm, satisfies requirements 5G millimeter-wave sub-bands sixth generation

Language: Английский

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Advancements in artificial intelligence and machine learning in revolutionising biomarker discovery

Brazilian Journal of Pharmaceutical Sciences, Journal Year: 2023, Volume and Issue: 59

Published: Jan. 1, 2023

The article explores the significance of biomarkers in clinical research and advantages utilizing artificial intelligence (AI) machine learning (ML) discovery process. Biomarkers provide a more comprehensive understanding disease progression response to therapy compared traditional indicators. AI ML offer new approach biomarker discovery, leveraging large amounts data identify patterns optimize existing biomarkers. Additionally, touches on emergence digital biomarkers, which use technology assess an individual's physiological behavioural states, importance properly processing omics multi-omics for efficient handling by computer systems. However, acknowledges challenges posed AI/ML identification including potential biases need diversity representation. To address these challenges, suggests regulation development algorithms.

Language: Английский

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Architectural Proposal for Low-Cost Brain–Computer Interfaces with ROS Systems for the Control of Robotic Arms in Autonomous Wheelchairs

Electronics, Journal Year: 2024, Volume and Issue: 13(6), P. 1013 - 1013

Published: March 7, 2024

Neurodegenerative diseases present significant challenges in terms of mobility and autonomy for patients. In the current context technological advances, brain–computer interfaces (BCIs) emerge as a promising tool to improve quality life these Therefore, this study, we explore feasibility using low-cost commercial EEG headsets, such Neurosky Brainlink, control robotic arms integrated into autonomous wheelchairs. These headbands, which offer attention meditation values, have been adapted provide intuitive based on eight signal values read from Delta Gamma (high low/medium Gamma) collected users’ prefrontal area, only two non-invasive electrodes. To ensure precise adaptive control, incorporated neural network that interprets real time so response arm matches user’s intentions. The results suggest combination BCIs, robotics, machine learning techniques, networks, is not technically feasible but also has potential radically transform interaction patients with neurodegenerative their environment.

Language: Английский

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Deciphering Optimal Radar Ensemble for Advancing Sleep Posture Prediction through Multiview Convolutional Neural Network (MVCNN) Approach Using Spatial Radio Echo Map (SREM)

Sensors, Journal Year: 2024, Volume and Issue: 24(15), P. 5016 - 5016

Published: Aug. 2, 2024

Assessing sleep posture, a critical component in tests, is crucial for understanding an individual's quality and identifying potential disorders. However, monitoring posture has traditionally posed significant challenges due to factors such as low light conditions obstructions like blankets. The use of radar technolsogy could be solution. objective this study identify the optimal quantity placement sensors achieve accurate estimation. We invited 70 participants assume nine different postures under blankets varying thicknesses. This was conducted setting equipped with baseline eight radars-three positioned at headboard five along side. proposed novel technique generating maps, Spatial Radio Echo Map (SREM), designed specifically data fusion across multiple radars. Sleep estimation using Multiview Convolutional Neural Network (MVCNN), which serves overarching framework comparative evaluation various deep feature extractors, including ResNet-50, EfficientNet-50, DenseNet-121, PHResNet-50, Attention-50, Swin Transformer. Among these, DenseNet-121 achieved highest accuracy, scoring 0.534 0.804 nine-class coarse- four-class fine-grained classification, respectively. led further analysis on ensemble For radars head, single left-located proved both essential sufficient, achieving accuracy 0.809. When only one central head used, omitting side retaining three upper-body resulted accuracies 0.779 0.753, established foundation determining sensor configuration application, while also exploring trade-offs between fewer sensors.

Language: Английский

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A Differential Inertial Wearable Device for Breathing Parameter Detection: Hardware and Firmware Development, Experimental Characterization

Sensors, Journal Year: 2022, Volume and Issue: 22(24), P. 9953 - 9953

Published: Dec. 16, 2022

Breathing monitoring is crucial for evaluating a patient's health status. The technologies commonly used to monitor respiration are costly, bulky, obtrusive, and inaccurate, mainly when the user moves. Consequently, efforts have been devoted providing new solutions methodologies overcome these limitations. These methods several uses, including healthcare monitoring, measuring athletic performance, aiding patients with respiratory diseases, such as COPD (chronic obtrusive pulmonary disease), sleep apnea, etc. Breathing-induced chest movements can be measured noninvasively discreetly using inertial sensors. This research work presents development testing of an inertia-based band breathing through differential approach. device comprises two IMUs (inertial measurement units) placed on back determine signal, carrying out information detection about activity. includes low-power microcontroller section acquire data from process them extract parameters (i.e., RR-respiration rate; TI/TE-inhalation/exhalation time; IER-inhalation-to-exhalation V-flow rate), IMU reference. A BLE transceiver wirelessly transmits acquired mobile application. Finally, test results demonstrate effectiveness dual-inertia solution; correlation Bland-Altman analyses were performed RR measurements reference, demonstrating high (r¯ = 0.92) low mean difference (MD¯ -0.27 BrPM (breaths per minute)), limits agreement (LoA¯ +1.16/-1.75 BrPM), absolute error (MAE¯ 1.15%). Additionally, experimental demonstrated that developed correctly other (TI, TE, IER, V), keeping MAE ≤5%. obtained indicated viable solution long-term both in stationary moving users.

Language: Английский

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An alternative focus on data in the neurorights discussion – Lessons from Brazil

Bioethics Open Research, Journal Year: 2024, Volume and Issue: 1, P. 3 - 3

Published: Jan. 9, 2024

Developments in neurotechnology are prompting concerns about the concepts of mental privacy, integrity, and cognitive liberty, among others. Many researchers some policymakers have begun to propose that novel human rights required meet challenges emerging poses. These proposals seen high-profile discussion, gaining already state-level recognition Chile. Others advocate a different approach by concentrating on data protection. This policy brief recommends this kind focus order (i) help regulate pace development (ii) respect potential for risks individuals permitting them greater control over how their neurodata is used. A data-centred an agile means providing legal ethical protection direction toward producing positive impacts. also refers legislative change Brazil, contrasted with Chile, where law be revised pre-empt neurotechnological issues. The Brazilian model emerges as alternative ought replicated other lawmakers globally.

Language: Английский

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Detecting Sleep Disorders in Polysomnography Data

Published: Feb. 27, 2024

The primary diagnostic test for sleep disorders is known as polysomnography, traditionally conducted while a patient sleeps under observation in specialized clinic. evolution of the Internet Things (IoT) field has facilitated collection various biometric signals, which are also monitored during this examination through wearable devices. In context, objective work to explore utilization machine learning algorithms disorder detection. Classification were assessed, and their outcomes compared by reducing number input aiming enable application polysomnography home setting. results indicate that most promising algorithm Random Forest, demonstrates satisfactory performance even with reduced data.

Language: Английский

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