Browsing by Author "Kakani, Monika"

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    Dynamic thermal/acoustic response for human bone materials at different energy levels: A diagnosis approach
    (Elsevier, 2016-10-31) Thella, Ashok Kumar; Rizkalla, James; Rathi, Neeraj; Kakani, Monika; Helmy, Ahdy; Salama, Paul; Rizkalla, Maher E.; Electrical and Computer Engineering, School of Engineering and Technology
    Background The non-invasive diagnostic approaches have gained high attention in recent years, utilizing high technology sensor systems, including infrared, microwave devices, acoustic transducers, etc. The patient safety, high resolution images, and reliability are among the driving forces toward high technology approaches. The thermal and acoustic responses of the materials may reflect the important research parameters such as penetration depth, power consumption, and temperature change used for the practical models of the system. This paper emphasizes the approach for orthopedic application where the bone densities were considered in simulation to designate the type of human bones. Methods Thermal energy pulses were applied in order to study the penetration depth, the maximum temperature change; spatially and dynamically, and the acoustic pressure distribution over the bone thickness. The study was performed to optimize the amount of energy introduced into the materials that generate the temperature value for high resolution beyond the noise level. Results Three different energy pulses were used; 1 J, 3 J and 5 J. The thermal energy applied to the four bone materials, cancellous bone, cortical bone, red bone marrow, and yellow bone marrow were producing relative changes in temperature. The maximum change ranges from 0.5 K to 2 K for the applied pulses. The acoustic pressure also ranges from 210 to 220 dB among the various types of bones. Conclusion The results obtained from simulation suggest that a practical model utilizing infra-red scanning probe and piezoelectric devices may serve for the orthopedic diagnostic approach. The simulations for multiple layers such as skin interfaced with bone will be reserved for future considerations.
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    Non invasive approach for the detection of human arterial blockages via photo acoustic modelling
    (2017-12) Kakani, Monika; Rizkalla, Maher
    This research focuses on the detection of arterial blockage due to LDL (low density lipoprotein). Arterial blockages are related to two kinds of fats LDL and the HDL. HDL being the good fat, the patient does not have to undergo the biopsy, while in case of LDL, biopsy should be performed. Issues associated with invasive approaches raise safety concerns for patients such as infection, longer operation durations, longer recovery time etc. This research focuses on a noninvasive imaging technique to detect the kind of block age. Photo acoustic approach was investigated in order to simulate human tissues leading to medical diagnosis and treatment. Photo acoustic imaging involves production of an image on absorption of laser pulses. The laser pulses are further scattered and absorbed producing heat. The goals of the study were to categorize the type of the tissue materials based on the output temperature distribution via IR sensors and reflected acoustic waves via acoustic pressure sensors. The reflected acoustic wave and IR thermal distribution may be applied towards arterial blockages to differentiate the different types of tissue layers. The simulation results should have implications towards the future implementation of the practical devices and system. Parameters including energy levels, tissue thicknesses, frequencies, penetration depth, and the densities of the LDL/HDL fat materials were considered. Various energy pulses; 1j, 3j, and 5j were considered as input sources to the tissue materials (single or multi layers). The simulated layers considered in the study were the skin, bone, blood, and fat cells. The temperature and acoustic pressure response over the various layers were analyzed for the detection of blockages. The ndings of the temperature and acoustic pressure ranges can be detected by MEMS/NEMS (Micro electro mechanical systems/ nano electro mechanical systems) sensors, such as IR and Piezoelectric devices. Bioheat and acoustic wave equations were solved simultaneously using COMSOL software for multiple layers. The proper boundary conditions were provided in the solutions of these equations. The scattering and transmission acoustic wave, and the temperature distributions, may be used as guide to the integrated sensor system design for future consideration. The simulation was performed in four stages: (1) Single layer and multiple layers at a given frequency and energy level (2) Multiple layers at a given frequency for different energy levels (3) Multiple layers at a given energy level for different frequency and (4) Multiple layers at a given frequency and energy levels with different size tissues. The simulation results showed that a range of acoustic pressure between 240 and 260 need to be detected, with a di erential temperature distribution in kelvin range. Power pulses of 10MPa showed a temperature change of 175, which is believed to be within the exible substrate sensing devices that may be used for the practical model of this research. The thesis covers a proposed system for the practical model following the simulation results received in this study.
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    Portable and Low Power Efficient Pre-Fall Detection Methodology
    (IEEE, 2018-08) Rathi, Neeraj; Kakani, Monika; Rizkalla, Maher; El-Sharkawy, Mohamed; Electrical and Computer Engineering, School of Engineering and Technology
    Fall in recent years have become a potential threat to elder generation. It occurs because of side effects of medication, lack of physical activities, limited vision, and poor mobility. Looking at the problems faced by people and cost of treatment after falling, it is of high importance to develop a system that will help in detecting the fall before it occurs. Over the years, this has influenced researchers to pursue the development to automatic fall detection system. However, much of existing work achieved a hardware system to detect pre and post fall patterns, the existing systems deficient in achieving low power consumption, user-friendly hardware implementation and high precision on a single portable system. This research points towards the development of dependable and low power embedded system device with easy to wear capabilities and optimal sensor structure. The designed system is triggered on interrupts from motion sensor to monitor users balanced, and unbalanced states. The fall decision parameters; pitch, roll, Signal Vector Magnitude (SVM), and Signal Magnitude Area (SMA) are layered to classify subject's different body posture. When the fall flag is set, the device sends important information like GPS location and fall type to caretaker. Early fall detection gives milliseconds of time to initiates the preventive measures. Near 100% sensitivity, 96% accuracy, and 95% specificity for fall detection were measured. The system can detect Front, Back, Side and Stair fall with consumption of 100uA (650uA with BLE consumption) in deep sleep mode, 6.5mA in active mode with no fall, and 14.5mA, of which 8.5 mA is consumed via the BLE when fall is declared in active mode.