Mae'r Athro Summers yn cael ei gydnabod yn rhyngwladol am ei ragoriaeth ymchwil, sy'n canolbwyntio ar ddau faes: mesuregau ar gyfer dadansoddi celloedd (cytometreg) a datblygu diagnosteg a therapiwteg sy'n seiliedig ar nanoronynnau (nanofeddygaeth).
This module will introduce the concepts of biomedical engineering and will establish a grounding of knowledge within the area that can be used within subsequent modules.
This course will consider human physiology from an Engineering standpoint, concentrating on the system architecture of major physiological components within the body, e.g. cardiovascular, nervous, muscular and respiratory systems. Emphasis will be place on the system level output and the control mechanisms required to maintain body homeostasis. A major practical element will run alongside the presentation of taught material. The Simulink programming environment will be used to: i. Model the behaviour and control of generalised systems and; ii. Simulate the function of specific biological systems relating to human physiology. Course elements: ¿ Introduction to basic systems - definition, components and architecture, emergent phenomenon ¿ Introduction to control theory - feedback, error monitoring, proportional control, dynamic systems ¿ Translation of systems control theory and models to human physiology ¿ Detailed modelling and simulation of specific physiological systems
The aim of this module is to introduce the science of measurement and explain the potential and the limitations of sensors commonly used in performance sports applications. Throughout the module, foundational principles will be explained using sporting examples of data analysis, with a particular focus on time-series data. A core principle of the module is that the process of measurement must be understood before applied studies are designed and data analysis is undertaken. The limits to measurement and the errors that can exist in a dataset have to be appreciated in the context of performance sport applications. The origin of the data also has to be considered as there are often hidden assumptions influencing its acquisition and pre-processing built into sensors. The aim here is to educate students about where their data comes from and to encourage them to critically assess the conditions under which valid measurements can be obtained in applied performance environments.
