Mehdi Seyedmahmoudian

Mixed reality tool for training on pressure immobilization treatment of snake bite envenomation

Snakebite, one of the most common and catastrophic environmental sicknesses, occurs due to the ignorance of its importance toward public health. The rich protein and peptide toxin nature of snake venom makes snake bite envenomation clinically challenging and a scientifically attractive issue. In most cases, the severity of snake bite envenomation mainly depends on the quality of first aid or snake bite management measure given to the victim prior to hospital treatment. In countries with field management strategies (such as pressure immobilization technique (PIT)), including Australia, the number of fatalities due to snake bites is considerably less compared with those in other countries without such precautionary measures. PIT involves the wrapping of a bandage or a crepe over the bitten area with a standard pressure of 55--70 and 40--70 mm Hg for lower and upper extremities, respectively. This technique delays the absorption rate or venom spread inside the body. However, the PIT displays a noticeable failure rate due to its sensitivity toward the pressure range that must be maintained when gripping the bandage around the bitten area. Off-the-shelf bandages with visual markers aid in the process of training on PIT. Despite the visual markers on the bandage, human interpretation of these markers differs, which causes discrepancies in applying correct pressure. In this paper, a mixed reality-based virtual reality (VR) training tool for PIT training is proposed. The VR application assists in training individuals to self-validate the correctness of pressure range applied to the bandage. The application provides a passive haptic response and a visual feedback on an augmented live stream of the camera to indicate whether the pressure is within the range. Visual feedback is obtained using a feature extraction technique, which adds novelty to the proposed research. Feedback suggests that the VR-based training tool will assist individuals in obtaining real-time feedback on the correctness of the bandage pressure and further understand the process of PIT.

Application of the hybrid ANFIS models for long term wind power density prediction with extrapolation capability

In this paper, the suitability and performance of ANFIS (adaptive neuro-fuzzy inference system), ANFIS-PSO (particle swarm optimization), ANFIS-GA (genetic algorithm) and ANFIS-DE (differential evolution) has been investigated for the prediction of monthly and weekly wind power density (WPD) of four different locations named Mersing, Kuala Terengganu, Pulau Langkawi and Bayan Lepas all in Malaysia. For this aim, standalone ANFIS, ANFIS-PSO, ANFIS-GA and ANFIS-DE prediction algorithm are developed in MATLAB platform. The performance of the proposed hybrid ANFIS models is determined by computing different statistical parameters such as mean absolute bias error (MABE), mean absolute percentage error (MAPE), root mean square error (RMSE) and coefficient of determination (R2). The results obtained from ANFIS-PSO and ANFIS-GA enjoy higher performance and accuracy than other models, and they can be suggested for practical application to predict monthly and weekly mean wind power density. Besides, the capability of the proposed hybrid ANFIS models is examined to predict the wind data for the locations where measured wind data are not available, and the results are compared with the measured wind data from nearby stations.

Evaluation of a new virtual reality micro-robotic cell injection training system

Abstract This study considers a virtual reality (VR) micro-robotic cell injection training system developed to reduce the time and cost required for a trainee to become proficient in cell injection. The VR environment replicates a micro-robotic cell injection setup to be interacted with and controlled using either a keyboard or haptic device. Using these two input control methods, user training evaluation experiments were designed and conducted to evaluate trainee performance. The performance improvement of 13 participants after undergoing training was analyzed. Results demonstrate that the participants attained higher accuracy and success rates when utilizing the haptic device control method than when applying the keyboard control method. All participants successfully performed the required task when employing the haptic device control method with haptic guidance enabled.