Framework of sensor-based monitoring for pervasive patient care.
Ontology highlight
ABSTRACT:
SUBMITTER: Triantafyllidis AK
PROVIDER: S-EPMC5047273 | biostudies-other | 2016 Sep
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Goal: The SARS-CoV-2 viral infection could cause severe acute respiratory syndrome, disturbing the regular breathing and leading to continuous coughing. Automatic respiration monitoring systems could provide the necessary metrics and warnings for timely intervention, especially for those with mild symptoms. Current respiration detection systems are expensive and too obtrusive for any large-scale deployment. Thus, a low-cost pervasive ambient sensor is proposed. Methods: We will posit a barometer on the working desk and develop a novel signal processing algorithm with a sparsity-based filter to remove the similar-frequency noise. Three modes (coughing, breathing and others) will be conducted to detect coughing and estimate different respiration rates. Results: The proposed system achieved 97.33% accuracy of cough detection and 98.98% specificity of respiration rate estimation. Conclusions: This system could be used as an effective screening tool for detecting subjects suffering from COVID-19 symptoms and enable large scale monitoring of patients diagnosed with or recovering.
| S-EPMC8545027 | biostudies-literature
Project description:Currently, many critical care indices are not captured automatically at a granular level, rather are repetitively assessed by overburdened nurses. In this pilot study, we examined the feasibility of using pervasive sensing technology and artificial intelligence for autonomous and granular monitoring in the Intensive Care Unit (ICU). As an exemplary prevalent condition, we characterized delirious patients and their environment. We used wearable sensors, light and sound sensors, and a camera to collect data on patients and their environment. We analyzed collected data to detect and recognize patient's face, their postures, facial action units and expressions, head pose variation, extremity movements, sound pressure levels, light intensity level, and visitation frequency. We found that facial expressions, functional status entailing extremity movement and postures, and environmental factors including the visitation frequency, light and sound pressure levels at night were significantly different between the delirious and non-delirious patients. Our results showed that granular and autonomous monitoring of critically ill patients and their environment is feasible using a noninvasive system, and we demonstrated its potential for characterizing critical care patients and environmental factors.
| S-EPMC6541714 | biostudies-literature
Project description:BackgroundRemote patient monitoring (RPM) has been increasingly adopted over the last decade, with the COVID-19 pandemic fostering its rapid development. As RPM implementation is recognised as complex and highly demanding in terms of resources and processes, there are multiple challenges in providing RPM in an integrated logic.MethodsTo examine the structural elements that are relevant for implementing RPM integrated care, a scoping review was conducted in PubMed, Scopus, and Web of Science, leveraging a search strategy that combines terms relative to (1) conceptual models and reallife initiatives; (2) RPM; and (3) care integration.Results28 articles were included, covering nine conceptual models and 19 real-life initiatives. Eighteen structural elements of RPM integrated care implementation were identified among conceptual models, defining a structure for assessing real-life initiatives. 78.9% of those initiatives referred to at least ten structural elements, with patient education and self-monitoring promotion, multidisciplinary core workforce, ICTs (information and communications technologies) and telemonitoring devices, and health indicators measurement being present in all studies, and therefore being core elements to the design of RPM initiatives.ConclusionRPM goes far beyond technology, with underlying processes and involved actors playing a central role in care provision. The structural elements identified can guide RPM implementation and promote maturity in adoption. Future research may focus on assessing design completeness, evaluating impacts, and analysing related financial arrangements.
| S-EPMC10461888 | biostudies-literature
Project description:Flexible respiratory monitoring devices have become available for outside-hospital application scenarios attributable to their improved system wearability. However, the complex fabrication process of such flexible devices results in high prices, limiting their applications in real-life scenarios. This study proposes a flexible, low-cost, and easy-processing paper-based humidity sensor for sleep respiratory monitoring. A paper humidity sensing model was established and sensors under different design parameters were processed and tested, achieving high sensitivity of 5.45 kΩ/%RH and good repeatability with a matching rate of over 85.7%. Furthermore, the sensor patch with a dual-channel 3D structure was designed to distinguish between oral and nasal breathing from origin signals proved in the simulated breathing signal monitoring test. The sensor patch was applied in the sleep respiratory monitoring of a healthy volunteer and an obstruct sleep apnea patient, demonstrating its ability to distinguish between different respiratory patterns as well as various breathing modes.
| S-EPMC9503997 | biostudies-literature
Project description:A new highly fluorescent zinc-organic framework [Zn2(btca)(DMSO)2]n (Zn-MOF) was prepared via in situ ligand formation by the solvothermal reaction of Zn(NO3)2·6H2O and pyromellitic dianhydride (PMDA) in DMSO solvent. During the solvothermal reaction, PMDA was gradually hydrolyzed to a pyromellitic acid, 1,2,4,5-benzene tetracarboxylic acid (H4btca), to provide a tetracarboxylic acid as a linker in the reaction medium. Single-crystal X-ray diffraction analysis exhibits a 3D porous structure with open tetragonal channels running along the crystallographic c-axis. The Zn-MOF was explored as an on-mode fluorescent sensor for tracing cimetidine in biological fluids and pharmaceutical samples in the presence of interfering species. The results show a quick response in a short time range. The characteristics of this sensor were investigated by field-emission scanning electron microscopy, dynamic light scattering, energy-dispersive X-ray analysis, powder X-ray diffraction, Fourier transform infrared and UV-vis spectroscopy as well as thermogravimetric, and elemental analyses.
| S-EPMC9260946 | biostudies-literature
Project description:Digital mobility assessment using wearable sensor systems has the potential to capture walking performance in a patient's natural environment. It enables monitoring of health status and disease progression and evaluation of interventions in real-world situations. In contrast to laboratory settings, real-world walking occurs in non-conventional environments and under unconstrained and uncontrolled conditions. Despite the general understanding, there is a lack of agreed definitions about what constitutes real-world walking, impeding the comparison and interpretation of the acquired data across systems and studies. The goal of this study was to obtain expert-based consensus on specific aspects of real-world walking and to provide respective definitions in a common terminological framework. An adapted Delphi method was used to obtain agreed definitions related to real-world walking. In an online survey, 162 participants from a panel of academic, clinical and industrial experts with experience in the field of gait analysis were asked for agreement on previously specified definitions. Descriptive statistics was used to evaluate whether consent (> 75% agreement as defined a priori) was reached. Of 162 experts invited to participate, 51 completed all rounds (31.5% response rate). We obtained consensus on all definitions ("Walking" > 90%, "Purposeful" > 75%, "Real-world" > 90%, "Walking bout" > 80%, "Walking speed" > 75%, "Turning" > 90% agreement) after two rounds. The identification of a consented set of real-world walking definitions has important implications for the development of assessment and analysis protocols, as well as for the reporting and comparison of digital mobility outcomes across studies and systems. The definitions will serve as a common framework for implementing digital and mobile technologies for gait assessment and are an important link for the transition from supervised to unsupervised gait assessment.
| S-EPMC8378707 | biostudies-literature
Project description:The detection and profiling of pathogenic bacteria is critical for human health, environmental, and food safety monitoring. Herein, we propose a highly sensitive colorimetric strategy for naked eye screening of 16S ribosomal RNA (16S rRNA) from pathogenic agents relevant to infections, human health, and food safety monitoring with a magnetic focus lateral flow sensor (mLFS) platform. The method developed was demonstrated in model 16S rRNA sequences of the pathogen Escherichia coli O157:H7 to detect as low as 1 fM of targets, exhibiting a sensitivity improved by ∼5 × 105 times compared to the conventional GNP-based colorimetric lateral flow assay used for oligonucleotide testing. Based on the grayscale values, semi-quantitation of up to 1 pM of target sequences was possible in ∼45 min. The methodology could detect the target 16S rRNA from as low as 32 pg/mL of total RNA extracted from pathogens. Specificity was demonstrated with total RNA extracted from E. coli K-12 MG1655, Bacillus subtilis (B. subtilis), and Pseudomonas aeruginosa (P. aeruginosa). No signal was observed from as high as 320 pg/mL of total RNA from the nontarget bacteria. The recognition of target 16S rRNA from 32 pg/mL of total RNA in complex matrices was also demonstrated. The proposed mLFS method was then extended to monitoring B. subtilis and P. aeruginosa. Our approach highlights the possibility of extending this concept to screen specific nucleic acid sequences for the monitoring of infectious pathogens or microbiome implicated in a range of diseases including cancer.
| S-EPMC8153928 | biostudies-literature
Project description:We use self-report and electrodermal activity (EDA) wearable sensor data from 77 nights of sleep of six participants to test the efficacy of EDA data for sleep monitoring. We used factor analysis to find latent factors in the EDA data, and used causal model search to find the most probable graphical model accounting for self-reported sleep efficiency (SE), sleep quality (SQ), and the latent factors in the EDA data. Structural equation modeling was used to confirm fit of the extracted graph to the data. Based on the generated graph, logistic regression and naïve Bayes models were used to test the efficacy of the EDA data in predicting SE and SQ. Six EDA features extracted from the total signal over a night's sleep could be explained by two latent factors, EDA Magnitude and EDA Storms. EDA Magnitude performed as a strong predictor for SE to aid detection of substantial changes in time asleep. The performance of EDA Magnitude and SE in classifying SQ demonstrates promise for using a wearable sensor for sleep monitoring. However, our data suggest that obtaining a more accurate sensor-based measure of SE will be necessary before smaller changes in SQ can be detected from EDA sensor data alone.
| S-EPMC6470539 | biostudies-literature
Project description:Accumulation of acetic acid indicates an imbalance of the process due to a disturbed composition of the microorganisms. Hence, monitoring the acetic acid concentration is an important parameter to control the biogas process. Here, we describe the generation and validation of a fluorescence-based whole cell sensor for the detection of acetic acid based on the yeast Saccharomyces cerevisiae. Acetic acid induces the transcription of a subset of genes. The 5´-regulatory sequences (5´ URS) of these genes were cloned into a multicopy plasmid to drive the expression of a red fluorescent reporter gene. The 5´ URS of YGP1, encoding a cell wall-related glycoprotein, led to a 20-fold increase of fluorescence upon addition of 30 mM acetic acid to the media. We show that the system allows estimating the approximate concentration of acetic acid in condensation samples from a biogas plant. To avoid plasmid loss and increase the long-term stability of the sensor, we integrated the reporter construct into the yeast genome and tested the suitability of spores for long-term storage of sensor cells. Lowering the reporter gene's copy number resulted in a significant drop of the fluorescence, which can be compensated by applying a yeast pheromone-based signal amplification system.
| S-EPMC8092980 | biostudies-literature
Project description:BackgroundTemperature measurement is a vital part of daily neonatal care. Accurate measurements are important for detecting deviations from normal values for both optimal incubator and radiant warmer functioning. The purpose of monitoring the temperature is to maintain the infant in a thermoneutral environmental zone. This physiological zone is defined as the narrow range of environmental temperatures in which the infant maintains a normal body temperature without increasing his or her metabolic rate and thus oxygen consumption. Although the temperature measurement gold standard is the skin electrode, infrared thermography (IRT) should be considered as an effortless and reliable tool for measuring and mapping human skin temperature distribution and assist in assessing thermoregulatory reflexes.MethodsBody surface temperature was recorded under several clinical conditions using an infrared thermography imaging technique. Temperature distributions were recorded as real-time video, which was analyzed to evaluate mean skin temperatures. Emissivity variations were considered for optimal neonatal IRT correction for which the compensation vector was overlaid on the tracking algorithm to improve the temperature reading. Finally, a tracking algorithm was designed for active follow-up of the defined region of interest over a neonate's geometry.ResultsThe outcomes obtained from the thermal virtual sensor demonstrate its ability to accurately track different geometric profiles and shapes over the external anatomy of a neonate. Only a small percentage of the motion detection attempts failed to fit tracking scenarios due to the lack of a properly matching matrix for the ROI profile over neonate's body surface.ConclusionsThis paper presents the design and implementation of a virtual temperature sensing application that can assist neonatologists in interpreting a neonate's skin temperature patterns. Regarding the surface temperature, the influence of different environmental conditions inside the incubator has been confirming.
| S-EPMC4015601 | biostudies-literature