Abstract: In the general scientific quest for increased quality of life a natural ambition is to know more about human body kinematics. Varied knowledge can be extracted from sensors placed on human body and through associated biomechanical parameter evaluation the causal connection between different biomechanical parameters and medical conditions can be inferred. From a biomechanical point of view, one of the most important parameters within the human body is the amplitude of angular movements of joints. Although many angular sensors are used in industry, particular characteristics such as small size, flexibility and appropriate attachment methods must be taken into consideration when estimating the amplitude of movement of human joints. This paper reviews the existing low cost easy to manipulate angular sensors listed in the scientific literature, which currently are or could be used in rehabilitation engineering, physiotherapy or biomechanical evaluations in sport. The review is carried out in terms of a classification based on the sensors’ working principles and includes resistive, capacitive, magnetic and piezoresistive sensors.

Abstract: Modern close loop control for blood glucose level in a diabetic patient necessarily uses an explicit model of the process. A fixed parameter full order or reduced order model does not characterize the inter-patient and intra-patient parameter variability. This paper deals with an online frequency domain kernel estimation method for modeling a nonlinear dynamic system of multivariable glucose-insulin process in a type-1 diabetic patient that captures the process dynamics in presence of uncertainties and parameter variations. The present work proposes a frequency domain kernel estimation of a Volterra model using the harmonic excitation input by taking FFT on the input data sequence from the glucose-insulin process of the patient. Volterra equations up to second order kernels with extended input vector for Volterra model are solved online by adaptive recursive least square (ARLS) algorithm. Twice the length of the extended input vector for the glucose-insulin process is considered for finding the frequency domain kernels that can be directly used as the Volterra transfer function and are useful for closed loop internal model control. The input-output data taken from the 19th order first principle model of the patient in intravenous route, have been used to identify the system with a short filter memory length of M=2 and the validation results have shown good fit both in frequency and time domain responses with nominal patient as well as with intrapatient parameter variations.

Abstract: Cerebrovascular abnormalities are extremely complex, due to the multitude of factors acting simultaneously on cerebral hemodynamics. Cerebral Arterio Venous Malformation (CAVM) hemodynamic in one of the vascular abnormality condition results changes in the flow and pressure level in blood vessels. This can cause rupture or decreased blood supply to the tissue through capillary causing infarct. Measuring flow and pressure without intervention along the vessel is big challenge due to occlusion, bending and thinning of the vessel in Arteriovenous Malformation patients. In this paper, we proposed a lumped model for the Vessels Deformation in CAVM Structures that will help clinicians to find the pressure and velocity measurements non-invasively.