A fuzzy expert system design for analysis of body sounds and design of an unique electronic stethoscope (development of HILSA kit)

Noninvasive Diagnosis of Irritable Bowel Syndrome via Bowel Sound Features: Proof of Concept

Irritable bowel syndrome (IBS) is a common and debilitating disorder estimated to affect approximately 11% of the world's population. Typically, IBS is a diagnosis of exclusion after patients undergo a costly and invasive colonoscopy to exclude organic disease. Clinician's and researchers have identified a need for a new cost-effective, accurate, and noninvasive diagnostic test for IBS.

BLUETOOTH-BASED WIRELESS DIGITAL STETHOSCOPE WITH MOBILE INTEGRATION

Acoustic stethoscopes are used to monitor signals from patients. Incidentally, the connecting tube between the chest-piece and the ear-piece of common stethoscopes is known to serve as a medium for transmitting pathogens from patients to physicians or from one patient to another patient. This work presents a wireless stethoscope design with mobile integration that transmits heart sounds to mobile devices for evaluation and analysis, thus, eliminates the connecting tube. This is an extension of the previous work that presented the proof of concept of a wireless stethoscope with Bluetooth transmission. In this work, however, the chest-piece of the traditional stethoscope is integrated with microcontroller unit and Bluetooth communication device. Captured signals are processed and transmitted wirelessly to a mobile device with interface application software for recording, listening and visual display of waveforms. Following numerical simulation, a prototype was developed. Testing conducted on the prototype device using a class 2 Bluetooth device with 4[Formula: see text]dBm transmission power showed good quality received signals when the mobile device was placed 20[Formula: see text]m within indoor environments and 42[Formula: see text]m in open-space outdoor environment, beyond which degradation in quality occurs. It is worth pointing out that a smart Bluetooth device with high transmission range and data speed may produce much longer operating distance. Hence, for applications that require operating ranges beyond 50[Formula: see text]m, smart Bluetooth devices may be well suited for such systems. This system may serve as the means for monitoring patients from remote locations particularly quarantine units and can also be useful for training health personnel through broadcasting of recorded signals for analysis and evaluation by members of a medical team.

Developing and using expert systems and neural networks in medicine: a review on benefits and challenges

Complicacy of clinical decisions justifies utilization of information systems such as artificial intelligence (e.g. expert systems and neural networks) to achieve better decisions, however, application of these systems in the medical domain faces some challenges. We aimed at to review the applications of these systems in the medical domain and discuss about such challenges. Following a brief introduction of expert systems and neural networks by representing few examples, the challenges of these systems in the medical domain are discussed. We found that the applications of expert systems and artificial neural networks have been increased in the medical domain. These systems have shown many advantages such as utilization of experts' knowledge, gaining rare knowledge, more time for assessment of the decision, more consistent decisions, and shorter decision-making process. In spite of all these advantages, there are challenges ahead of developing and using such systems including maintenance, required experts, inputting patients' data into the system, problems for knowledge acquisition, problems in modeling medical knowledge, evaluation and validation of system performance, wrong recommendations and responsibility, limited domains of such systems and necessity of integrating such systems into the routine work flows. We concluded that expert systems and neural networks can be successfully used in medicine; however, there are many concerns and questions to be answered through future studies and discussions.

Analysis of respiratory sounds: state of the art

OBJECTIVE

This paper describes state of the art, scientific publications and ongoing research related to the methods of analysis of respiratory sounds.

METHODS AND MATERIAL

Review of the current medical and technological literature using Pubmed and personal experience.

RESULTS

The study includes a description of the various techniques that are being used to collect auscultation sounds, a physical description of known pathologic sounds for which automatic detection tools were developed. Modern tools are based on artificial intelligence and on technics such as artificial neural networks, fuzzy systems, and genetic algorithms…

CONCLUSION

The next step will consist in finding new markers so as to increase the efficiency of decision aid algorithms and tools.