Comparison of Respiratory Rate Detection by Seven Sensor Signals in Clinically Challenging Conditions

The underlying problem for two of the three most common patterns of unexpected hospital deaths (PUHD) is hypoventilation1. Concern over this opioid-induced respiratory depression has led many experts and consensus guidelines to recommend that all patients receiving opioids be monitored for respiratory rate. Currently, no clinically accepted “gold-standard” monitoring device exists for non-intubated, spontaneously breathing patients. We studied seven distinct respiratory sensors to compare their effectiveness in respiratory monitoring. Methods: With IRB approval, data were collected from 26 volunteers who were administered target controlled infusions of remifentanil and propofol in order to induce low respiratory rates. Data were collected from a suite of sensors which were analyzed using a single, custom breath detection algorithm. Breath rates derived from a capnometer, accelerometer, oro-nasal thermistor, nasal pressure transducer, microphone, photoplethysmogram, and impedance respiratory sensor were compared against breath rates derived from the reference standard of respiratory inductance plethysmography bands at both low and normal respiratory rate ranges. Results: Capnometry and acceleromtry reported respiratory rates closest to those reported by the respiratory inductance plethysmography bands. Conclusion: Detecting respiratory rate in the post-operative environment is a clinically challenging problem which likely requires further study

Evaluation of pulse transit time for different sensing methodologies of arterial waveforms.

We perform a novel comparative analysis between optically and mechanically derived pulse transit time (PTT), which is a universally employed technique for cuffless blood pressure (BP) estimation. Two inline photoplethysmogram (PPG) sensors were placed at the distal and proximal phalanxes of the index finger, and two finger ballistocardiogram (BPP) sensors were wrapped on top of the PPG sensors fixture around the phalanxes of the index finger. The stacking of the BPP sensor over the PPG sensor provided vertical spatial alignment for same location acquisition of the blood flow waveform through the radial artery. The analysis of variance (ANOVA) between PTT derived from the PPG and BPP sensors resulted in a statistically significant difference at p < 0.05. The PTT derived from the BPP sensors showed higher values (17.8 milliseconds on average) than the PTT derived from the PPG sensors. Higher accuracy PTT values will improve the estimation of cuffless BP and thus has the potential to revolutionize the technology

Physiological-based Driver Monitoring Systems: A Scoping Review

A physiological-based driver monitoring system (DMS) has attracted research interest and has great potential for providing more accurate and reliable monitoring of the driver’s state during a driving experience. Many driving monitoring systems are driver behavior-based or vehicle-based. When these non-physiological based DMS are coupled with physiological-based data analysis from electroencephalography (EEG), electrooculography (EOG), electrocardiography (ECG), and electromyography (EMG), the physical and emotional state of the driver may also be assessed. Drivers’ wellness can also be monitored, and hence, traffic collisions can be avoided. This paper highlights work that has been published in the past five years related to physiological-based DMS. Specifically, we focused on the physiological indicators applied in DMS design and development. Work utilizing key physiological indicators related to driver identification, driver alertness, driver drowsiness, driver fatigue, and drunk driver is identified and described based on the PRISMA Extension for Scoping Reviews (PRISMA-Sc) Framework. The relationship between selected papers is visualized using keyword co-occurrence. Findings were presented using a narrative review approach based on classifications of DMS. Finally, the challenges of physiological-based DMS are highlighted in the conclusion. Doi: 10.28991/CEJ-2022-08-12-020 Full Text: PD

Physiological Approach To Characterize Drowsiness In Simulated Flight Operations During Window Of Circadian Low

Drowsiness is a psycho-physiological transition from awake towards falling sleep and its detection is crucial in aviation industries. It is a common cause for pilot’s error due to unpredictable work hours, longer flight periods, circadian disruption, and insufficient sleep. The pilots’ are prone towards higher level of drowsiness during window of circadian low (2:00 am- 6:00 am). Airplanes require complex operations and lack of alertness increases accidents. Aviation accidents are much disastrous and early drowsiness detection helps to reduce such accidents. This thesis studied physiological signals during drowsiness from 18 commercially-rated pilots in flight simulator. The major aim of the study was to observe the feasibility of physiological signals to predict drowsiness. In chapter 3, the spectral behavior of electroencephalogram (EEG) was studied via power spectral density and coherence. The delta power reduced and alpha power increased significantly (

Nanocellulose-based sensors in medical/clinical applications: The state-of-the-art review

In recent years, the considerable importance of healthcare and the indispensable appeal of curative issues, particularly the diagnosis of diseases, have propelled the invention of sensing platforms. With the development of nanotechnology, the integration of nanomaterials in such platforms has been much focused on, boosting their functionality in many fields. In this direction, there has been rapid growth in the utilisation of nanocellulose in sensors with medical applications. Indeed, this natural nanomaterial benefits from striking features, such as biocompatibility, cytocompatibility and low toxicity, as well as unprecedented physical and chemical properties. In this review, different classifications of nanocellulose-based sensors (biosensors, chemical and physical sensors), alongside some subcategories manufactured for health monitoring, stand out. Moreover, the types of nanocellulose and their roles in such sensors are discussed.This work was supported by the University of the Basque Country (Training of Researcher Staff, PIF 20/197)

SAGA: Smart gateway for adaptive environments

The development of adaptive environments has the main objective of providing well-being to an individual, improving the environmental conditions of indoor environments and facilitating/automating any activity. In order to implement such systems, the use of devices capable of intercommunication and acquisition of environment-related parameters around the user is essential. Using wireless sensor networks, it is possible to monitor the various quality indices of indoor environments that can be used to develop strategies to improve quality of life of the users in personalized way. In this dissertation, a system based on a wireless sensor network that analyses and improves the environmental quality of indoor spaces, as well as evaluating the health status of an individual is presented. The system acquires and acts upon air quality and illumination quality-related parameters, as well as physiological data of a user, using sensor nodes and actuators distributed throughout the environment. Several wireless communication protocols have been implemented to enable intercommunication between the several elements present in the sensor network, such as actuators, sensor nodes and a coordinating / gateway node. Several warning mechanisms have been configured to alert the user to the presence of factors that may endanger their health, namely the presence of pollutants and thermal conditions that may trigger respiratory distress. In order to provide real-time system control including additional warning mechanisms, data analysis, a dedicated web application has been developed for this system. The user can control the environment according with his own needs and preferences through profiles configuration. The whole process of system development, hardware, software, experimental tests and contributions are included in this dissertation.A criação de ambientes adaptativos tem o principal objetivo de providenciar o bem-estar a um indivíduo, melhorar as condições do ambiente em seu redor e de facilitar/automatizar qualquer atividade. De forma a implementar tais sistemas, a utilização de dispositivos com capacidade de intercomunicação e de recolha de parâmetros relacionados com o ambiente em redor do utilizador é essencial. Com a utilização de redes de sensores sem fios, é possível monitorizar os diversos índices de qualidade de um ambiente interior e dessa forma melhorar a qualidade de vida. Nesta dissertação será apresentado um sistema baseado numa rede de sensores sem fios que permite analisar e melhorar a qualidade ambiental de espaços interiores e avaliar o estado de saúde de um indivíduo. O sistema adquire e atua sobre parâmetros relacionados com a qualidade do ar e qualidade de iluminação, assim como dados fisiológicos de um utilizador, através da utilização de nós de sensores e atuadores distribuídos pelo ambiente. Foram implementados diversos protocolos de comunicação sem fios para possibilitar a intercomunicação com outros elementos da rede, nomeadamente o nó coordenador/gateway. Foram configurados diversos mecanismos de alerta de forma a avisar o utilizador para a presença de fatores que possam colocar em risco a sua saúde, nomeadamente a presença de poluentes e condições térmicas que possam desencadear desconforto respiratório. De forma a proporcionar uma análise de dados em tempo real, controlo do sistema e dispor de mecanismos de alerta adicionais, foi desenvolvida uma aplicação Web dedicada a este sistema. Através desta, o utilizador poderá tornar o ambiente adaptável às suas características e de acordo com as suas preferências, através da configuração de perfis. Todo o processo de desenvolvimento do sistema, hardware, software, testes experimentais e contribuições serão incluídos nesta dissertação