Variation in Normal Ear Temperature

Sund‐Levander, Märtha; Grodzinsky, Ewa

doi:10.1016/j.amjms.2017.05.013

Cited by 19 publications

(15 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The model temperature was changed based on recent investigations of the variation in normal ear temperature measured in 2006 individuals [26]. Table 1.…”

Section: Sensitivity Assessment Of the Numerical Modelmentioning

confidence: 99%

“…Number of axons (1) 21-133 68 18 [24] Axon fiber diameter (µm) 7-12 8 0.5 [24] Model temperature ( • C) 35.6-37 36.3 0.2 [26] Ear conductivity (S/m) 0.1-0.7 0.4 0.1 [27] Electrode penetration depth (mm) 0.8-1.5 -* 0.1 [12] Electrode position (mm) (±0.1, ±0.1) 0 0.1 [12] * For sensitivity index simulations of other parameters the electrode penetration depth was fixed to 1.5 mm.…”

Section: Range Avmentioning

confidence: 99%

See 1 more Smart Citation

Sensitivity Analysis of a Numerical Model for Percutaneous Auricular Vagus Nerve Stimulation

et al. 2019

View full text Add to dashboard Cite

Background: Less-invasive percutaneous stimulation of the auricular branch of the vagus nerve (pVNS) gained importance as a possible nonpharmacological treatment for various diseases. The objective is to perform a sensitivity analysis of a realistic numerical model of pVNS and to investigate the effects of the model parameters on the excitation threshold for single and bundled axons. Methods: Sim4Life electrostatic solver and neural tissue models were combined for electromagnetic and neural simulation. The numerical model consisted of a high-resolution model of a human ear, blood vessels, nerves, and three needle electrodes. Investigated parameters include the axon diameter and number, model temperature, ear conductivity, and electrodes’ penetration depth and position. Results: The electric field distribution was evaluated. Model temperature and ear conductivity are the non-influential parameters. Axons fiber diameter and the electrodes’ penetration depth are the most influential parameters with a maximum threshold voltage sensitivity of 32 mV for each 1 μm change in the axon diameter and 38 mV for each 0.1 mm change in the electrodes’ penetration depth. Conclusions: The established sensitivity analysis allows the identification of the influential and the non-influential parameters with a sensitivity quantification. Results suggest that the electrodes’ penetration depth is the most influential parameter.

show abstract

“…The model temperature was changed based on recent investigations of the variation in normal ear temperature measured in 2006 individuals [26]. Table 1.…”

Section: Sensitivity Assessment Of the Numerical Modelmentioning

confidence: 99%

Section: Range Avmentioning

confidence: 99%

Sensitivity Analysis of a Numerical Model for Percutaneous Auricular Vagus Nerve Stimulation

et al. 2019

View full text Add to dashboard Cite

show abstract

“…The assessment of body temperature uses a new approach based on the difference from baseline, the so-called ‘DiffTemp ’ instead of predecided values for fever, ie, >38°C. 23 Recording ‘DiffTemp’ as part of EDIS enables a more targeted approach focusing on specific aspects of behaviour and functional status. However, as EDIS is still undergoing ongoing development, it is yet to be to be widely adopted in Sweden.…”

Section: Introductionmentioning

confidence: 99%

Exploring views and experiences of how infections are detected and managed in practice by nurses, care workers and manager’s in nursing homes in England and Sweden: a survey protocol

et al. 2020

View full text Add to dashboard Cite

IntroductionIn order to avoid unnecessary hospital admission and associated complications, there is an urgent need to improve the early detection of infection in nursing home residents. Monitoring signs and symptoms with checklists or aids called decision support tools may help nursing home staff to detect infection in residents, particularly during the current COVID-19 pandemic.We plan to conduct a survey exploring views and experiences of how infections are detected and managed in practice by nurses, care workers and managers in nursing homes in England and Sweden.Methods and analysisAn international cross-sectional descriptive survey, using a pretested questionnaire, will be used to explore nurses, care workers and managers views and experiences of how infections are detected and managed in practice in nursing homes. Data will be analysed descriptively and univariate associations between personal and organisational factors explored. This will help identify important factors related to awareness, knowledge, attitudes, belief and skills likely to affect future implementation of a decision support tool for the early detection of infection in nursing home residents.Ethics and disseminationThis study was approved using the self-certification process at the University of Surrey and Linköping University ethics committee (Approval 2018/514-32) in 2018. Study findings will be disseminated through community/stakeholder/service user engagement events in each country, publication in academic peer-reviewed journals and conference presentations. A LAY summary will be provided to participants who indicate they would like to receive this information.This is the first stage of a plan of work to revise and evaluate the Early Detection of Infection Scale (EDIS) tool and its effect on managing infections and reducing unplanned hospital admissions in nursing home residents. Implementation of the EDIS tool may have important implications for the healthcare economy; this will be explored in cost–benefit analyses as the work progresses.

show abstract

“…Normal body temperatures show large variations and the same applies to increased temperatures in fever. [9]  By skin: A thermistor thermometer or an infrared thermometer for skin temperature have been found to be quite reliable and more portable as compared to the traditional mercury based thermometers. [10] The pulse rate is a measure of the heart rate or the heart beats per minute.…”

Section: Introductionmentioning

confidence: 99%

Composite and Wearable Sensor Kit for Location Aware Healthcare Monitoring and Real-Time Trauma Scoring for Survival Prediction.

Walinjkar¹

2018

Preprint

View full text Add to dashboard Cite

With the availability of wearable health monitoring sensor modules like 3-Lead Electrocardiogram (ECG), Pulse Oximeter (SpO2), Galvanic Skin Response (GSR), Hall effect sensor (for measuring Respiratory Rate), Blood Pressure and Temperature measuring and sensing elements, it has now become possible to device a composite health status monitoring kit that can measure vital signs and other physiological parameters pertaining to human health in real time. Traditionally, the physiological parameters along with vital signs related examination was possible only in a hospitalized or ambulatory environment, however due to advances in sensing and embedded system technology and miniaturization of data acquisition and processing elements health monitoring has become possible even when individuals remain engaged in their day to day activities at the convenience of space and location. The patients or individuals subject to monitoring may suffer from a traumatic experience due to their medical condition and may need emergent incidence response and the critical care team may have to prepare for the treatment only after the patient arrives, which often is too late, as in case of cardiac arrests or severe injuries. The research focused on real-time health status monitoring and trauma scoring using standard physiological parameters along with standard telemetry protocols to make the critical care team aware of an emergent situation and prepare for a medical emergency. Vital signs and physiological parameters (heart rate, temperature, respiratory rate, and blood pressure, SpO2) were measured in real time from human subjects non-invasively. In order to enable monitoring of the patients engaged in day to day activities, errors due to the motion were removed using stationary wavelet transform correction (correlation coefficient of 0.9 after correction) and signals from various sensors were denoised, filtered and were encoded in a format suitable for further data analysis. A composite sensor kit capable of monitoring vital signs and physiological parameters can be very useful in incident response when an individual undergoes a traumatic experience related to stroke, cardiac arrest, fits or even injury, as along with monitoring information the kit can calculate scores related to trauma like the Injury Severity Score (ISS), National Early Warning Signs (NEWS), Revised Trauma Score (RTS). Trauma Injury Severity Score (TRISS), Probability of Survival (Ps) score. An open access database of vital signs and physiological parameters from Physionet, MIMIC 2 Numerics (mimicdb/numerics) database was used to calculate NEWS and RTS and to generate correlation and regression models using the vital signs/physiological parameters for a clinical class of patients with respiratory failure and admitted to Intensive Care Unit (ICU). NEWS and RTS scores showed no significant correlation (r = 0.25, p<0.001) amongst themselves, however together NEWS and RTS showed significant correlation with Ps (blunt) (r = 0.70, p<0.001). RTS and Ps (blunt) scores showed some correlation (r = 0.63, p<0.001) and NEWS score showed significant correlation (r = 0.79, p<0.001) with Ps (blunt) scores. Furthermore, since individuals have to be monitored regardless of location, these kits have to have a built-in capability to locate the individual so that the incident response team can locate the individual based on Global Positioning System coordinates (GPS). A Quantum GIS (Geographical Information System) application using real-time GPS coordinates (OpenStreetMap coordinates) was used to calculate the shortest path using QGIS Network Analysis tool to demonstrate the calculation of shortest path and direction to locate the nearest service provider in shortest time. Along with locating the nearest healthcare service provider, it would help if the critical care team could be made aware of the physiological parameters and trauma scores using standard protocols accepted across the globe. The physiological parameters from the sensors along with the calculated trauma scores were encoded according to a standard Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) coding system and International Code of Diseases (ICD) codes and the trauma information was logged to Electronic Health Records (EHR) using Fast Health Interoperability Resources (FHIR) servers. FHIR servers provided interoperable web services to log the event information in real time. It could be concluded that analytical models trained on existing datasets can help in analyzing a traumatic experience or an injury and the information can be logged using a standard telemetry protocol as a telemedicine initiative. These scores enable the healthcare service providers to estimate the extent of trauma and prepare for medical emergency procedures and find applications in general and military healthcare.

show abstract

Variation in Normal Ear Temperature

Abstract: Ear body temperature is lower than traditionally reported and differs with age and sex. An individual difftemp of 1.0-1.5°C along with malaise might indicate fever.

Cited by 19 publications

References 43 publications

Sensitivity Analysis of a Numerical Model for Percutaneous Auricular Vagus Nerve Stimulation

Sensitivity Analysis of a Numerical Model for Percutaneous Auricular Vagus Nerve Stimulation

Exploring views and experiences of how infections are detected and managed in practice by nurses, care workers and manager’s in nursing homes in England and Sweden: a survey protocol

Composite and Wearable Sensor Kit for Location Aware Healthcare Monitoring and Real-Time Trauma Scoring for Survival Prediction.

Contact Info

Product

Resources

About