The process of auscultation and diagnosis of heart defects by extracting relevant features associated with pathological murmurs and classifying them using fuzzy controller is described. These murmurs reveal important information about the cardiovascular disorders which can assist general physician to come up with more accurate and reliable diagnosis at an early stage. 

The human body is a remarkable piece of biological machinery and exhibits a very efficient control system. During wars, mine explosions, or any other unfortunate incidents, if a person loses his limb, he loses the invaluable functionality provided by that limb.Progress in the last few decades has resulted in efficient prosthesis by using advance plastic materials and carbon fiber optics. Advancement in electronics has also its application in the area resulting in much controllable and capable automated functioning of the artificial limbs.

Figure 1: A detailed overview of all the sections of our project

We are working on the research and development of an automated prosthetic control unit. The project is titled as EMG Controlled Upper Limb Prosthesis (ECULP) with initial focus on Upper Limb (arm and hand) Prosthesis.  The knowledge and technological knowhow acquired in this project will subsequently enable us to extend it to control any of the major amputation. The project involves acquisition of clean EMG and EEG signals through effective signal conditioning and classification of the acquired signal in order to differentiate between the movements of the limb while also analyzing the intensity of these movements. Finally, a standalone product is to be developed that is to be interfaced with a bionic arm; helping the amputee an independent automated control of the device.

Figure 2: Procedural steps for EMG acquisition and signal conditioning.

Phase I:

·         EMG extraction unit and mechanical design of a prosthetic arm

·         Electromechanical design of upper limb prosthesis

Students Involved:

1.      Musayyab Ali (Sp08-BEE-080)

2.      Muhammad Hassan(Sp08-BEE-189)

3.      Muhammad OwaisBaloch(Sp08-BEE-068)

4.      Adil Khan(Sp08-EPE-020)

Phase II:

·         Detection and Classification of EMG signals for finger control

·         Redesigning of four channel EMG acquisition unit.

Students Involved:

5.      Jawad Tariq (Fa10-BEE-023)

6.      Muhammad Naeem (Fa10-BEE-027)

7.      JavedIqbal (Fa10-BEE-011)

8.      Abbas Shah (Fa10-BEE-005)

9.      SikandarFarooq(Sp11-BEE-069)

10.  Akhlaq Ahmad(Sp11-BCE-053)

11.  ZeeshanAkhtar(Sp11-BEE-066)

Phase III:

·         Designing of an algorithm for real time classification of EMG signals

·         EMG classifier implementation on Beagle-bone black.

Students Involved:

12.  Masood Anwar Khan(Fa09-BCE-025)

13.  Muhsin Ali(Fa09-BCE-037)

14.  Tahir Ali(Fa09-BCE-049)

15.  Zulfiqar Ali(Fa09-BCE-063)

16.  Muhammad ZubairJamil(Sp11-BEE-037)

17.  Malik TalhaSaad(Sp11-BEE-036)

18.  Hashim Ali(Sp11-BEE-032)

Institutions Involved:

Electrical Engineering Department

COMSATS IIT-Abbottabad

Pak Irish Rehabilitation Center

Abbottabad

We are thankful to Institutions like ICT (R&D) and DOST, Pakistan because of their financial support we were able to take an initiative. However, the project is in its early stages and currently further work is being carried out.

Demo: