The heart disease diagnosing system based on force sensitive chair's measurement, biorthogonal wavelets and neural networks

• Published in: IEEE/ASME International Conference on Advanced Intelligent Mechatronics pp. 676 - 681
• Main Authors: Akhbardeh, A., Junnila, S., Koivuluoma, M., Koivistoinen, T., Varri, A.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 2005
• Subjects: Biomedical signal processing; Biosensors; Cardiac disease; Electrodes; Feature extraction; Force measurement; Force sensors; Heart; Neural networks; Sensor systems
• ISBN: 0780390474; 9780780390478
• ISSN: 2159-6247
• DOI: 10.1109/AIM.2005.1511060

The heart disease diagnosing (HDD) system consists of a sensitive movement EMFI-film sensor installed under the upholstery of a chair. Whilst a man rests on the chair, this force sensitive sensor produces a single electrical signal containing components reflective of cardiac-ballistocardiogram (BCG), respiratory, and body movement related motion. Among different measurements of body activities, BCG has an interesting property that no electrodes are needed to be attached to the body during recording. This makes it suitable for evaluation of a man's heart condition in any place such as home, car, or office. This paper describes briefly our developed HDD system and especially a combined intelligent signal processing method to detect, extract features, and finally cluster BCG cycles. The system is designed to assist medical doctors to diagnose heart diseases of subject under test. Indeed, it is a fully automatic system which is not sensitive to any BCG latency as well as non-linear disturbance. It uses high resolution biorthogonal wavelet transform to extract essential BCG features and then clusters them using artificial neural networks (ANNs). Some evaluations using recordings from normal young, normal old and abnormal old volunteers indicated that our combined method is reliable and has a high performance