Implementation of an Improved Model for Medical Images Using PIC Microcontroller in Telemedicine

Abstract This paper aims to design and develop a low-cost, lightweight, portable system for critical patient monitoring system. The proposed system employs a Peripheral Interface Circuit (PIC) Microcontroller and MALAB 7.5.0(R2007) platform that performs analysis of the acquired brain image continuously. A brain tumor is identified and analyzed by detecting the infected region using a combination of Self Organizing Maps (SOM) followed by K- means algorithm. PIC Microcontroller based Region of Interest (ROI) detector in various medical images is implemented on a PIC 16F877A board and is interfaced with a Personal Computer (PC) to send status about the detection of brain tumor serially. If any abnormality is detected by the system, it sends an alarm, which sounds automatically and the warning message is also displayed on the LCD monitor device. Medical images are compressed at a lower bit rate and the abnormal data is transmitted to healthcare services or a personal doctor for diagnosis. Finally, the warning messages are sent to the doctor’s mobile whenever the patients require medical advice for treatment.

[1]  Saikat Roy,et al.  A GSM BASED INTELLIGENT WIRELESS MOBILE PATIENT MONITORING SYSTEM , 2015 .

[2]  Robert S. H. Istepanian,et al.  Practical evaluation of GPRS use in a telemedicine system in Cyprus , 2003, 4th International IEEE EMBS Special Topic Conference on Information Technology Applications in Biomedicine, 2003..

[3]  Hla Myo Tun,et al.  Wireless Patient Monitoring System Using Point to Multi Point Zigbee Technology , 2015 .

[4]  Alfred Coleman,et al.  Using a Virtual ICT Training Framework to Support Doctors in Rural Hospitals in South Africa , 2013 .

[5]  Adisorn Sirikham.  Abnormal heart rate detection device warning via mobile phone network , 2011, 2011 International Conference on Multimedia Computing and Systems.

[6]  Hujun Yin,et al.  The Self-Organizing Maps: Background, Theories, Extensions and Applications , 2008, Computational Intelligence: A Compendium.

[7]  Shi Zhang,et al.  A Portable Intelligent ECG Monitor Based on Wireless Internet and Embedded System Technology , 2008, 2008 International Conference on BioMedical Engineering and Informatics.

[8]  Inan Güler,et al.  Combining stationary wavelet transform and self-organizing maps for brain MR image segmentation , 2011, Eng. Appl. Artif. Intell..

[9]  S. K. Srivatsa,et al.  Design and implementation of mobile telecardiac system , 2008 .

[10]  Saurabh Prakash,et al.  Real time monitoring of ECG signal using PIC and web server , 2013 .

[11]  R.D. Thakare,et al.  Implementation of Neural Networks Based ECG classifi'er on TMS320C6711 processor , 2008, 2008 International Conference on Signal Processing, Communications and Networking.

[12]  Mahua Bhattacharya,et al.  GUI Based Brain Tumor Identification System by Detecting Infected Region through a Combination of Region Growing, Cryptography, and Digital Watermarking Technique , 2014, 2014 Fourth International Conference on Communication Systems and Network Technologies.

[13]  Kiran P. Somase,et al.  Mobile Robot for Object Detection Using Image Processing , 2013 .

[14]  Jitendranath Bera,et al.  Wireless Communication based Portable Telecardiology System for Rural Health Care , 2006 .

[15]  V. Thulasi Bai.  Real time portable telemedicine system for cardiac patient , 2009, 2009 International Conference on Future BioMedical Information Engineering (FBIE).

[16]  Siavash Alipour,et al.  Noisy image segmentation using a self-organizing map network , 2015 .