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A highly accurate human hand kinematics model and identification are proposed. The model includes the five digits and the palm arc based on mapping function between surface landmarks and estimated joint centres of rotation. Model identification was experimentally performed using a motion tracking system. The evaluation of the marker position estimation error, which is on sub-millimetre level across all digits, underlines model quality and accuracy. Noticeably, with the development of this model, we were able to improve various modelling assumptions from literature and found a basic linear relationship between surface and skeleton rotational angles.

Drowsy driving is a major cause of traffic accidents. Eye blinking is considered as important evidence of driver drowsiness. In this paper, a portable and low cost device for monitoring a driver's drowsiness is proposed. The proposed system consists of two main parts that detect eye blinking based on IR sensors mounted on eyewear. Depending on the reflected and absorbed IR radiation, this system detects and classifies the eye blinking into normal blinking (NB) or prolonged blinking (PB). The detected prolonged blinking is used to trigger an audio/visual alarm system which draws the driver's attention back. The system was simulated initially by LabVIEW® software. Moreover, the system was bench tested on 15 adult volunteers; eye blinking were detected and classified successfully for all subjects. The results of this research are promising and additional investigation is required to further improve the method.

Diabetes is becoming more prevalent over the world, with approximately 7.8 million new cases diagnosed each year. The most crucial aspect of diabetes therapy is frequent glucose monitoring; the one and only way diabetics can maintain healthy blood sugar standard is through diet and exercise. Blood glucose monitoring techniques have gone through massive transformations over the past few years. Non-invasive procedures outperform invasive and minimally invasive ones in terms of inconvenience, pain, and recovery time. Thus, this review aims to explore the latest tools for non-invasive glucose monitoring sensors and techniques. The study showed that non-invasive techniques such as optical and non-optical techniques are better than invasive techniques in terms of accuracy, reliability, repeatability, and ease of use. The study also uncovered that the photoacoustic spectroscopy and ultrasonic techniques have room for further development and advancement considering their flexible nature. The work also proved that the ultrasonic technique is the most promising approach, in conclusion.

A safe and wireless system for infant apnoea monitoring and treatment is proposed. It consists of two separate modules that detect apnoea based on a microcontroller processing and transmitting signals to the remote unit using wireless communication arrangement. Depending on the ECG signal, this system records the infant's heart and respiratory rates. Recognition of the consecutive QRS complexes within the ECG signal helps in calculating these vitals. Abnormal breathing rate or heart rate (apnoea) triggers both an alarm system on the remote unit to inform parents of this abnormality and a treatment device that stimulates the infant to breathe using vibration transducer. Different ECG signals from the MIT-Physionet database were used to test the prototype. The system successfully extracted, analysed and transmitted required vitals and decisions to the receiving unit. Finally, the system was bench tested on 25 adult volunteers and 12 young children; voluntarily cessations of breathing were detected successfully for all subjects.