December Research Picks

Fuzzy asthma detection

Scientists at the Dayalbagh Educational Institute, in Agra, India, have developed a symptom-based decision-support system that could be effective in diagnosis and control of asthma, a chronic, and potentially fatal, lung disease. In the first phase they diagnose asthma using data mining tools to track “peripheral” symptoms such as sneezing, a dry cough, or sore throat rather than the usual wheezing and breathing function metrics. In the second phase, asthma control level is measured using a fuzzy inference system that monitors shortness of breath and the more obvious symptoms of the disorder. Their initial findings suggest more effective control is possible with a concomitant reduction in costs by avoiding prescribed medication and other treatments where it is unwarranted or unnecessary at a given time for a given patient.

Tyagi, A. and Singh, P. (2014) ‘Asthma diagnosis and level of control using decision tree and fuzzy system’, Int. J. Biomedical Engineering and Technology, Vol. 16, No. 2, pp.169–181.


Keeping an eye on image compression

A new approach to compressing high-resolution medical images for reduced bandwidth in transmission and lower storage requirements for archival purposed has been developed by researchers at the University of Tlemcen, in Algeria. The team has developed a hybrid compression algorithm, that others have had success with in other fields. Their new technique combines Discrete Wavelet Transform (DWT) and Discrete Cosinus Transform (DCT) to achieve high compression rates for optical photographs taken of the retina at the back of a patient’s eyes. A 10 megabyte image can be compressed to just over half a megabyte, the team reports, with very little loss of detail. The next step will be to optimize the efficiency and then extend the algorithm to retinographic video sequences.

Boukli, H.I. and Bessaid, A. (2014) ‘Hybrid colour medical image compression by CDF wavelet and cosine transforms’, Int. J. Biomedical Engineering and Technology, Vol. 16, No. 1, pp.1–13.


On solar pond

The scientific principles of thermodynamics were first laid down during the industrial revolution of the steam-driven nineteenth century. Heat flow and heat capacity and the work heat could do were the push that turned the wheels. The concept of “exergy” emerged during this period – defined as the work that a system might do as thermal energy from the system flows into a heat reservoir. Exergy is destroyed as entropy, or disorder, increases but the nineteenth-century concept might now be exploited in solving a 21st century problem – how to trap and store the sun’s energy to use throughout the year.

One apparently simple solution is the solar pond. A solar pond is a pool of saltwater that absorbs heat from the sun and stores it simply by getting warm, they can be used subsequent local heating, desalination, drying, electricity generation and even refrigeration through evaporative cooling. Researchers at the Indian Institute of Technology Delhi, India, have carried out an analysis of the exergy and energy of a system of solar ponds and suggested various ways the energy and exergy efficiency of these systems might be improved to accommodate the changing seasons.

Ranjan, K.R., Kaushik, S.C. and Panwar, N.L. (2014) ‘Energy and exergy analyses of solar ponds in the Indian climatic conditions’, Int. J. Exergy, Vol. 15, No. 2, pp.121–151.


Depressing Bollywood music

A study of female college students suggests that depression and suicidal tendencies are more common among those who listen to Indian film music as opposed to folk, pop or rock music. Bollywood music scores high on causing depression, the team found in their survey of students. They point out that mental illness, including depression and anxiety disorders is rife in the developing world and a major cause of death. Moreover, given the traditional restrictions and modern pressures on young Indian women, there is a greater risk among females than males. They suggest that their findings may help inform psychological counseling although the correlation between listening to a particular kind of music and depression is not necessarily cause and effect in either direction.

Geethanjali, B. and Adalarasu, K. (2014) ‘Assessment of depression, anxiety and stress among female students’, Int. J. Biomedical Engineering and Technology, Vol. 16, No. 2, pp.182–193.