Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
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Conf Proc IEEE Eng Med Biol Soc · Jan 2012
Cardiac output estimation in mechanically ventilated patients: a comparison between prolonged expiration method and thermodilution.
A non-invasive method to estimate cardiac output (CO) in mechanically ventilated patients, based on prolonged expiration, has been previously described. With the aim to assess its performances, we prospectively enrolled fifteen cardiac surgery patients, and compared the results obtained with the non-invasive method with the ones obtained using two invasive approaches based on thermodilution. ⋯ These values show the slight underestimation of CO by the proposed non-invasive method with respect to the gold standard. On the other hand the described method could represent a good compromise between accuracy and non-invasiveness, which fosters the implementation of a new monitoring tool suitable for a semi-continuous CO assessment.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2012
Case ReportsBrain state evolution during seizure and under anesthesia: a network-based analysis of stereotaxic eeg activity in drug-resistant epilepsy patients.
Epilepsy is a neurological condition with a prevalence of 1%, and 14-34% have medically refractory epilepsy (MRE). Seizures in focal MRE are generated by a single epileptogenic zone (or focus), thus there is potentially a curative procedure - surgical resection. This procedure depends significantly on correct identification of the focus, which is often uncertain in clinical practice. ⋯ Our preliminary study suggests that seizure foci may be the most weakly connected regions in the brain during the beginning of a seizure and the most strongly connected regions towards the end of a seizure. Additionally, in one of the patients analyzed, the network connectivity under anesthesia highlights seizure foci. Ultimately, network centrality computed from sEEG activity may be used to develop an automated, reliable, and computationally efficient algorithm for identifying seizure foci.
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Sternal seismocardiogram (SCG) is the assessment of microvibrations produced by the beating heart as detected by an accelerometer positioned on the sternum. This signal reflects mechanical events of the heart contraction, including the opening and closure of mitral and aortic valves and maximal blood flow acceleration. Traditionally, SCG has been detected in a laboratory setting with the subject lying at rest in supine position. ⋯ A large number of SCG estimates could be obtained over the 24 hours. In particular, more than 100 estimates per hour were available during the day; at night this rate was three times higher. Thus our study indicates that not only the 24h SCG monitoring in daily life is feasible but also that possible changes over time in SCG and its derived parameters may be tracked with an extreme temporal detail.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2012
Clinical TrialReal-time cardiorespiratory coherence detects antinociception during general anesthesia.
Heart rate variability (HRV) may provide anesthesiologists with a noninvasive tool for monitoring nociception during general anesthesia. A novel real-time cardiorespiratory coherence (CRC) algorithm has been developed to analyze the strength of linear coupling between heart rate (HR) and respiration. CRC values range from 0 (low coherence, strong nociception) to 1 (high coherence, no nociception). ⋯ For comparison, three traditional measures of HRV (LF/HF ratio, SDNN, and RMSSD) responded on average by only 3.8%, 14%, and 3.9%, respectively. Finally, two traditional clinical measures of nociception (HR and blood pressure) responded on average by only 3.9% and 0.91%, respectively. CRC may thus be used as a real-time nociception monitor during general anesthesia.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2012
PersonA: Persuasive social network for physical Activity.
Advances in physical activity (PA) monitoring devices provide ample opportunities for innovations in the way the information produced by these devices is used to encourage people to have more active lifestyles. One such innovation is expanding the current use of the information from self-management to social support. We developed a Persuasive social network for physical Activity (PersonA) that combines automatic input of physical activity data, a smartphone, and a social networking system (SNS). ⋯ The implementation of self-monitoring, social support, and persuasive concepts using currently available technologies has the potential for promoting healthy lifestyle, greater community participation, and higher quality of life. We also expect that PersonA will enable health professionals to collect in situ data related to physical activity. The platform is currently being used and tested to improve PA level of three groups of users in Pittsburgh, PA, USA.