View clinical trials related to Vital Signs.
Filter by:To develop an intervention to train family carers to perform and document basic vital signs whilst they provide personal care to their relatives after surgery in order to supplement patient monitoring conducted by nursing staff. To evaluate the effect of this intervention on the frequency of documented vital signs for patients in the first three days after surgery in a stepped-wedge cluster trial.
Patients and volunteers both with and without medical problems will be recruited; vital sign measurements are taken twice with normal equipment and while recording video data at the same time. The data collected will allow the Artificial Intelligence to develop the LifeLight algorithm to to improve measurement accuracy of its video data based vital signs monitor.
This study validates Lifelight® First, a software application, in a laboratory setting. Participants will undergo testing to obtain measurements from one or more of the four vital signs.
In recent years there has been increasing focus on the earlier detection of deterioration in the clinical condition of hospital patients with the aim of instigating earlier treatment to reverse this deterioration and prevent adverse outcomes. This is especially important in the ED, a dynamic environment with large volumes of undifferentiated patients, which carries inherent patient risk. SNAP40 is an innovative medical-grade device that can be worn on the upper arm that continuously monitors patients' vital signs including relative changes in systolic blood pressure, respiratory rate, heart rate, movement, blood oxygen saturation and temperature. It uses automated risk analysis to potentially allow clinical staff to easily and quickly identify high-risk patients. The aim of this study is to investigate whether the SNAP40 device is able to identify deterioration in the vital sign physiology of an ED patient earlier than current standard monitoring and observation charting techniques.
To this date no clinical evaluation reports of the dynamics in the National Early Warning Score (NEWS) for those patients who suffer an in-hospital cardiac arrest, IHCA, exists. This process needs to be investigated in order to optimize the future care of these patients. Research Questions H1: Patients that suffer an IHCA has had higher NEWS in the preceding 24 hours from the event compared to those who did not suffer an IHCA. H2: The dynamics in the NEWS, differs between the patients that suffer an IHCA and those who do not in the preceding 24 hours from the event.
Bodytrak® is a wireless earpiece which can monitor the user's vital signs such as tympanic (ear) temperature and heart rate. The earpiece is non-invasive and should fit comfortably within the right ear, similar to an earphone with an over-the-ear hook. Bodytrak is currently in a prototype stage. The purpose of this study is to assess the feasibility of conducting a trial investigating the integration of Bodytrak in an NHS (National Health Service) environment at Chelsea and Westminster Hospital; to collect patient vital sign data for the development of Bodytrak algorithms to detect the transition point of recovery/deterioration of health, as well as the level of consciousness; and to obtain nurse and patient feedback regarding their user experience of Bodytrak.
To assess the feasibility and usability of the Vital Signs Patch (VSP) System in the in-patient hospital setting to monitor vital signs using a patch, brain, gateway, and console. The VSP System will be incorporated into the study site's Information Technology infrastructure.
To assess the feasibility and usability of the VSP System in the in-patient hospital setting to monitor vital signs using a patch, brain, gateway, and console. The VSP System will be incorporated into the study site's Information Technology infrastructure.
Study hypothesis: Machine Learning algorithms and techniques previously developed for use in the robotics field can be applied to the field of medicine. These state-of-the-art, feature extraction and machine learning techniques can utilize patient vital sign data from bedside monitors to discover hidden relationships within the physiological waveforms and identify physiological trends or concerning conditions that are predictive of various clinical events. These algorithms could potentially provide preemptive alerts to clinicians of a developing patient problem, well before any human could detect a worrisome combination of events or trend in the data. Specific aims: 1. Collect physiological waveform and numeric trend data from patient vital signs monitors in ICUs at the University of Colorado Hospital and Children's Hospital Colorado. 2. Combine the physiological data from patient monitors with clinical data obtained from patient Electronic Medical Records including IV fluids, medications, ventilator settings, urine output, etc. for use in developing models of various clinical conditions. 3. Apply Machine Learning techniques to these models to identify physiological waveform features and trend information, which are characteristic and predictive of common clinical conditions including but not limited to: - Post-operative atrial fibrillation and other cardiac dysrhythmias - Post-operative cardiac tamponade - Tension pneumothorax - Optimal post-operative and post-resuscitation fluid needs - Intracranial hypertension and cerebral perfusion pressure
Title: The acute effect of water pipe smoking on exhaled nitric oxide (eNO) and exhaled breath condensate (EBC) pulmonary function tests in healthy volunteers Objectives: To evaluate the acute effect of one cession of water pipe smoking on airway inflammation as assessed by exhaled nitric oxide (eNO) and exhaled breath condensate (EBC) in healthy volunteers. Design: Prospective study evaluating these parameters before and after 30 minutes of water pipe smoking . The changes in inflammatory parameters pre and post smoking will be evaluated blindly. Sample size: 100 participants Participant selection: Adults subjects who regularly smoke water pipe . Intervention: Each subject will undergo evaluation including a respiratory questionnaire , pulmonary function tests , exhaled nitric oxide (eNO) and exhaled breath condensate (EBC) and carboxy- hemoglobin levels . All measurements will be evaluated before and after one cession of 30 minutes water pipe smoking Primary outcome parameter: Change in carboxy- hemoglobin Secondary outcome parameter:Change in peripheral eosinophils count, pulmonary function tests, change in FeNO, and in inflammatory parameters in EBC before and after water pipe smoking