Measuring microcirculatory tissue blood perfusion is of interest for both clinicians and researchers in a wide range of applications and can provide essential information of the progress of treatment of certain diseases which causes either an increased or decreased blood flow. Diabetic ulcer associated with alterations in tissue blood flow is the most common cause of non-traumatic lower extremity amputations. A technique which can detect the onset of ulcer and provide essential information on the progress of the treatment of ulcer would be of great help to the clinicians. A noninvasive, noncontact and whole field laser speckle contrast imaging (LSCI) technique has been described in this paper which is used to assess the changes in blood flow in diabetic ulcer affected areas of the foot. The blood flow assessment at the wound site can provide critical information on the efficiency and progress of the treatment given to the diabetic ulcer subjects. The technique may also potentially fulfill a significant need in diabetic foot ulcer screening and management.

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Drowsiness or fatigue condition refers to feeling abnormally sleepy at an inappropriate time, especially during day time. It reduces the level of concentration and slowdown the response time, which eventually increases the error rate while doing any day-to-day activity. It can be dangerous for some people who require higher concentration level while doing their work. Study shows that 25–30% of road accidents occur due to drowsy driving. There are number of methods available for the detection of drowsiness out of which most of the methods provide an indirect measurement of drowsiness whereas electroencephalography provides the most reliable and direct measurement of the level of consciousness of the subject. The aim of this paper is to design and develop a portable and low cost brain–computer interface system for detection of drowsiness. In this study, we are using three dry electrodes out of which two active electrodes are placed on the forehead whereas the reference electrode is placed on the earlobe to acquire electroencephalogram (EEG) signal. Previous research shows that, there is a measurable change in the amplitude of theta ([Formula: see text]) wave and alpha ([Formula: see text]) wave between the active state and the drowsy state and based on this fact theta ([Formula: see text]) wave and alpha ([Formula: see text]) wave are separated from the normal EEG signal. The signal processing unit is interfaced with the microcontroller unit which is programmed to analyze the drowsiness based on the change in the amplitude of theta ([Formula: see text]) wave. An alarm will be activated once drowsiness is detected. The experiment was conducted on 20 subjects and EEG data were recorded to develop our drowsiness detection system. Experimental results have proved that our system has achieved real-time drowsiness detection with an accuracy of approximately 85%.

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