A scalable tracking human model was proposed for recognizing human jogging and walking activities. The model aims to detect and track a particular subject by using wearable sensor. Data collected are in accelerometer readings in three axes and gyroscope readings in three axes. The development of proposed human model is based on the moderating effects on human movements. Two moderators were proposed as the moderating factors of human motion and they are angular velocity and elevation angle. Linear regression is used to investigate the relationship among inputs, moderators and outputs of the model. The result of this study showed that the angular velocity and elevation angle moderators are affecting the relation of research output. Acceleration in x-axis (Ax) and angular velocity in y-axis (Gy) are the two main components in directing
a motion. Classification between jogging and walking motions was done by measuring the magnitude of angular velocity and elevation angle. Jogging motion was classified and identified with larger angular velocity and elevation angle. The two proposed hypotheses were supported and proved by research output. The result is expected to be beneficial and able to assist researcher in investigating human motions.
The development of human-like brain phantom is important for data acquisition in microwave imaging. The characteristics of the phantom should be based on the real human body dielectric properties such as relative permittivity. The development of phantom includes the greymatter and whitematter regions, each with a relative permittivity of 38 and 28 respectively at 10 GHz frequency. Results were compared with the value obtained from the standard library of Computer Simulation Technology (CST) simulation application and the existing research by Fernandez and Gabriel. Our experimental results show a positive outcome, in which the proposed mixture was adequate to represent real human brain for data acquisition.
The study was conducted based on two objectives as framework. The first objective is to determine the point of microwave signal reflection while penetrating into the simulation models and, the second objective is to analyze the reflection pattern when the signal penetrate into the layers with different relative permittivity, εr. Thus, several microwave models were developed to make a close proximity of the in vivo human brain. The study proposed two different layers on two different characteristics models. The radii on the second layer and the corresponding antenna positions are the factors for both models. The radii for model 1 is 60 mm with an antenna position of 10 mm away, in contrast, model 2 is 10 mm larger in size with a closely adapted antenna without any gap. The layers of the models were developed with different combination of materials such as Oil, Sandy Soil, Brain, Glycerin and Water. Results show the combination of Glycerin + Brain and Brain + Sandy Soil are the best proximity of the in vivo human brain grey and white matter. The results could benefit subsequent studies for further enhancement and development of the models.