Patient waiting alert monitoring system
Abstract : In medical field, electronics industry gaining to develop medical equipment at very high advanced level techniques, they use electronics system every time for patient caring. Patient monitoring system can be defined as the system used for monitoring physiological signals that includes the parameters like electro-cardio graph (ECG), respiratory signals, invasive and noninvasive blood pressure, body temperature, gases related parameters, etc. So, we also try to developer medical field and provide another patient caring facility to medical service for patient monitoring. As per requirement of medical field we try to complete the requirement. As per requirement of medical field we design this “patient monitoring & alerting system by using GSM”. In this project we design the services for collecting data of the patients parameter like temperature heart beat and the glucose level in the saline bottle we uses total three sensor like temperature sensor (thermistor), LDR, Heart beat sensor(IR sensor) this sensor are sense the data. By using this sensor we can find the temperature of patient, heart beat rate as well as the glucose level in the bottle.
? If the patients are in the remote areas, doctors are not available all the time and in such cases getting doctor is very difficult too. Even in emergency cases also, getting doctor is really a tough task.
? Prior knowledge about the structure of data in the training set is not required. The new training pattern gets added to the existing training set.
? KNN Algorithm finds the match for patient details using attributes like temperature, heartbeat and sound with the existing stored and trained data set.
? The output of the KNN Algorithm is a first step solution for the patient.
? This algorithm is later evaluated by applying it to the change point detection problem and comparing it to the generalized likelihood ratio (GLR) algorithm.
? However, the latest achievements in different fields of technologies may allow us to minimize the problem and successfully integrate these technologies into the modern health care systems.
? Moreover, a power consumption problem is a serious consequence in this case, which was previously addressed and leads to unnecessary complexity of the system.
? Popular approach, which incorporates several relative studies is based on Bayesian on-line change point detection and focused on the retrospective segmentation problem.
• The proposed work of Patient Monitoring & Alerting System with GSM. Microcontroller play very important role in this project that will measure parameters of patients by using different types of sensors like Thermistor, LDR, Heart beat sensor.
• Assuming the specific requirement, announced in the beginning of this section, the proposed algorithm is computationally expensive for the current project.
• A special application was designed and successfully ran for this particular purpose.
• A special sliding window is used for this particular purpose which goes through the time series and applies a Matlab function giving a coefficient as an output.
? A special sliding window is used for this particular purpose which goes through the time series and applies a Matlab function giving a coefficient as an output.
? The depicted plot is a small section cut from the whole dataset to demonstrate an algorithm performance within several hours of monitoring.
? We use a subplot in order to show a change point detection performance on the same data sector.
? However, we are able to provide a general overview of the system performance and summarize the main analyzed parameters.
? However, a particular approach involving Symbolic Aggregate Approximation of the signal has proved its efficiency when compared to other methods.
|