Automated Anesthesia Injector for Patient Monitoring System using Unified Technology Learning Platform
R.Sagayaraj1, A.Sheela2, U.Saravanakumar3
1Dr. R. Sagayaraj*, Professor, Department of Electrical & Electronics Engineering, Muthayammal Engineering College, Namakkal, India.
2A.Sheela, Associate Professor, Department of Electrical & Electronics Engineering, Kongu Engineering College, Erode, India.
3Dr. U.Saravanakumar, Professor & Head, Department of ECE, Muthayammal Engineering College, Namakkal, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 3692-3696 | Volume-8 Issue-12, October 2019. | Retrieval Number: L26441081219/2019©BEIESP | DOI: 10.35940/ijitee.L2644.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This work focuses on the level of anaesthesia injected to the patient at a specified time span and to observe the various physical parameters of the patient such as temperature, heartbeat, blood pressure, glucose level, blood level and respiration of the patient in an effective manner. To avoid the death of a patient in the anaesthetic condition during operation, an anaesthesiologist is with the patient at the time of surgery to monitor the patient. In the existing system, for the monitoring of anaesthesia, Anaesthesiologist will accompany the patient until the patient becomes stable. To overcome the above issue, the proposed automated patient monitoring system will hog the limelight in hospitals in the near future. Through automation in the monitoring system with high speed advanced ARM 8 processor which executes large instructions used for the implementation. The automatic anaesthesia monitoring system has capable of monitoring multiple parameters, which is essential for the patient during the anaesthetic condition. The physical parameters are sensed using suitable sensors and transmitted through the Zigbee module over a wireless network to the anaesthesiologist so that the anaesthesiologist can monitor the patient anaesthetic condition and other parameters at their own premises. Also, they can view the results in the monitor screen with the help of a personal computer. The proposed system reduces the risk of severe injury and death during anaesthesia. The proposed system is executed using the Unified Technology Learning Platform and the simulation results against various parameters of the patient are performed using Labview software.
Keywords: ARM 8 Processor, Anesthesia, Embedded Controlled Sensor Network, Unified Technology Learning Platform, Zigbee Module.
Scope of the Article: e-Learning