Search results for: electrocardiograph.

Authors: Durgesh Kumar Ojha, Monica Subashini

Abstract:

The proposed method is to study and analyze Electrocardiograph (ECG) waveform to detect abnormalities present with reference to P, Q, R and S peaks. The first phase includes the acquisition of real time ECG data. In the next phase, generation of signals followed by pre-processing. Thirdly, the procured ECG signal is subjected to feature extraction. The extracted features detect abnormal peaks present in the waveform Thus the normal and abnormal ECG signal could be differentiated based on the features extracted. The work is implemented in the most familiar multipurpose tool, MATLAB. This software efficiently uses algorithms and techniques for detection of any abnormalities present in the ECG signal. Proper utilization of MATLAB functions (both built-in and user defined) can lead us to work with ECG signals for processing and analysis in real time applications. The simulation would help in improving the accuracy and the hardware could be built conveniently.

Keywords: ECG Waveform, Peak Detection, Arrhythmia, Matlab.

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Authors: Ashwin Belle, Bryce Benson, Mark Salamango, Fadi Islim, Rodney Daniels, Kevin Ward

Abstract:

A reliable, real-time, and non-invasive system that can identify patients at risk for hemodynamic instability is needed to aid clinicians in their efforts to anticipate patient deterioration and initiate early interventions. The purpose of this pilot study was to explore the clinical capabilities of a real-time analytic from a single lead of an electrocardiograph to correctly distinguish between rapid response team (RRT) activations due to hemodynamic (H-RRT) and non-hemodynamic (NH-RRT) causes, as well as predict H-RRT cases with actionable lead times. The study consisted of a single center, retrospective cohort of 21 patients with RRT activations from step-down and telemetry units. Through electronic health record review and blinded to the analytic’s output, each patient was categorized by clinicians into H-RRT and NH-RRT cases. The analytic output and the categorization were compared. The prediction lead time prior to the RRT call was calculated. The analytic correctly distinguished between H-RRT and NH-RRT cases with 100% accuracy, demonstrating 100% positive and negative predictive values, and 100% sensitivity and specificity. In H-RRT cases, the analytic detected hemodynamic deterioration with a median lead time of 9.5 hours prior to the RRT call (range 14 minutes to 52 hours). The study demonstrates that an electrocardiogram (ECG) based analytic has the potential for providing clinical decision and monitoring support for caregivers to identify at risk patients within a clinically relevant timeframe allowing for increased vigilance and early interventional support to reduce the chances of continued patient deterioration.

Keywords: Critical care, early warning systems, emergency medicine, heart rate variability, hemodynamic instability, rapid response team.

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Authors: Megumi Nishida, Naoya Motegi, Takurou Kikuchi, Tomoko Tokumura

Abstract:

In recent years, the power system has been changed and a flexible power pricing system such as demand response has been sought in Japan. The demand response system works simply in the household sector and the owner as the decision-maker, can benefit from power saving. On the other hand, the execution of demand response in the office building is more complex than in the household because various people such as owners, building administrators and occupants are involved in the decision-making process. While the owners benefit from demand saving, the occupants are exposed to restricted benefits of a demand-saved environment. One of the reasons is that building systems are usually under centralized management and each occupant cannot choose freely whether to participate in demand response or not. In addition, it is unclear whether incentives give occupants the motivation to participate. However, the recent development of IT and building systems enables the personalized control of the office environment where each occupant can control the lighting level or temperature individually. Therefore, it can be possible to have a system which each occupant can make a decision of whether or not to participate in demand response in the office building. This study investigates personal responses to demand response requests, under the condition where each occupant can adjust their brightness individually in their workspace. Once workers participate in the demand response, their desk-lights are automatically turned off. The participation rates in the demand response events are compared among four groups, which are divided by different motivation, the presence, or absence of incentives and the method of participation. The result shows that there are significant differences of participation rates in demand response event between four groups. The method of participation has a large effect on the participation rate. The “Opt-out” groups where the occupants are automatically enrolled in a demand response event if they do not express non-participation have the highest participation rate in the four groups. Incentives also have an effect on the participation rate. This study also reports on the impact of low illumination office environment on the occupants, such as stress or fatigue. The electrocardiogram and the questionnaire are used to investigate the autonomic nervous activity and subjective fatigue symptoms of the occupants. There is no big difference between dim workspace during demand response event and bright workspace in autonomic nervous activity and fatigue.

Keywords: Demand response, illumination, questionnaire, electrocardiograph.

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