In Hospital and in Home Remote Patient Monitoring

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Connected e-Health

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1021))

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Abstract

Remote patient monitoring (RPM) are most often used nowadays. RPM enables you to monitor patients in their own homes, at work, in transit, or even on vacation. The condition of patient is monitored by doctor easily from the hospital. The RPM can connect patients and clinicians in order to maintain continuous surveillance of patients. Wearable sensors are used in patient body to monitor the parameters of patients such as heart rate, temperature, blood pressure, glucose level, and oxygen level. The wearable sensors are connected to the Android mobile phone via Bluetooth. Every patient should have Android mobile with internet which receives collected data from all sensors through Bluetooth interface unit. The Android application is shared to patient while register in the hospital, and then the collected data is sent to the hospital. The collected information is transmitted to server in hospital from the Android mobile phone. In hospital, all patient data with unique id is stored in the server. The server is controlled by robotic process automation (RPA) by UI path. The collected data are analyzed by RPA and intimated to the doctor about the patient. RPA is interfaced with server. The RPA is used to automatically update the patient data from hospital server database to the doctor. If the patient is in critical condition, the RPA automatically intimated to the particular doctor via mobile and automatically fix the appointment to that patient and the doctor. The patient condition is known by doctor through Android mobile phone which is registered with hospital with unique id. If the concern doctor is not available, the RPA can fix the appointment to another doctor automatically. With the help of server, the doctor can know the history of patient and start treatment.

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Palanivel Rajan, S., Dineshkumar, T. (2022). In Hospital and in Home Remote Patient Monitoring. In: Mishra, S., González-Briones, A., Bhoi, A.K., Mallick, P.K., Corchado, J.M. (eds) Connected e-Health. Studies in Computational Intelligence, vol 1021. Springer, Cham. https://doi.org/10.1007/978-3-030-97929-4_15

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