Our product “EKKO-A Wave Therapeutic Device” proposes a new solution for cognitive rehabilitation using vibrational waves. EKKO is a portable device which uses vibrational waves to treat neurological disorders based on Neurotransmission Cognitive Theory Vibrational waves have been found to be effective in the fast recovery of muscles because of their resonance with the natural frequencies of the muscle fibers and are already used in the medical industry. Our product uses vibration waves for cognitive rehabilitation based on neurotransmission cognitive theory. The proposed product includes vibration wave therapy device and an intelligent assistant software with cloud services. This product can be used at home by parents of special children and also at special education centers for rehabilitation of special children.

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OCT Image Analysis System for Grading and Diagnosis of Retinal Diseases and its Integration in i-Hospital

This project is the enhancement over our previously developed hospital management & information system (HMIS) which also includes the added feature of automatically analyzing fundus imagery for the possible detection of diabetic retinopathy (DR) and glaucoma. In this project, we have revamped our HMIS to be under full compliance with HL7 health standard through OpenMRS. Furthermore, we have added the support to automatically analyze 2D and 3D OCT imagery for detecting retinopathy along with the enhanced retinal visualization.

It is worth mentioning that this project along with its predecessor has won multiple gold and silver awards in the R&D category at Asia Pacific ICT Alliance Award (APICTA) and Pakistan Software Houses Association for IT and ITES (P@SHA).

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AL-BASR is designed to represent data that accurately captures the state of patient at all times. It is an Electronic Patient Health Record System. Allows an entire patient history to be viewed; without the need to track down the patient‟s previous medical record. Assists in ensuring that data is accurate, appropriate and legible. By maintaining one modifiable file, that is updated constantly, it reduces data replication.

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Net-Enabled Retinal Image Analysis its Integration in i-telemedicine system

The proposed system is a telemedicine system for telescreening of DR with capabilities of self diagnosis, real time access to data from rural areas, assignment of ophthalmologist for expert opinion and management of a national database for regular monitoring. The main aim of project is to provide a low cost and easy access solution to patients with diabetes for regular monitoring of the retina to avoid the risk of sudden vision loss. In this project, we propose a self diagnosis system for DR with capabilities of automated screening and diagnosis of abnormalities present in human retina, a universal communication node to provide real time availability of data and intelligent server to assign expert and schedule patient’s data and help in early detection of DR to save patient’s vision. The system will take real time high quality retinal images from fundus camera and will grade it according to type and number of abnormalities present in it using state of the art image processing and pattern recognition techniques. The images with possible DR will be sent to ophthalmologists for further diagnosis and the data for each patient will be saved for regular monitoring and to check the progress of disease.

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Pneumonia kills nearly 2 million children around the world out of a total of 150 million children who affected by it and about 98% of these deaths occur in developing countries. According to latest estimates, Pakistan lies in the top five countries which account for about 99 percent of childhood pneumonia cases.

Our product Smart Steth consists of a digital stethMic and an android based application for self-diagnosis.

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Decision Support System for Detection of Glaucoma using Structural and Non Structural Features

Glaucoma is 2nd leading cause of blindness all over the world and we have 1.8 million glaucoma patients in Pakistan. The purpose of this project was to develop algorithms for early detection of  glaucoma. Our main objectives were development of algorithms for detection of glaucoma, collection of data sets for validity of these algorithms, incorporating the algorithms into a system for proper use of doctors and making a low cost retina screening system. We made collaboration with Armed Forces institute of Ophthalmology (AFIO) who helped us in data collection of local patients, trials and validity of algorithms.

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