Liver is a vital organ of the human body performing myriad of essential functions. Liver-related ailments are often life-threatening and dramatically deteriorate the quality of life of patients. Management of acute liver diseases requires adequate support of various hepatic functions. Thus far, liver transplantation has been proven as the only effective solution for acute liver diseases. However, broader application of liver transplantation is limited by demand for lifelong immunosuppression, shortage of organ donors, relative high morbidity, and high cost. Therefore, research has been focused on attempting to develop alternative support systems to treat liver diseases. Earlier attempts have been made to use nonbiological therapies based on the use of conventional detoxification procedures such as filtration and dialysis. However, the absence of liver cells in such techniques reduced the overall survival rate of the patients and led to inadequate essential liver-specific functions. As a result, there has been growing interest in the development of biological therapy-based extracorporeal liver support systems as a bridge to liver transplantation or to support the ailing liver. A bioartificial liver support is an extracorporeal device through which plasma is circulated over living and functionally active hepatocytes packed in a bioreactor with the aim to aid the diseased liver until it regenerates or until a suitable graft for transplantation is available. This review article gives a brief overview of efficacy of various liver support systems that are currently available. Also, the development of advanced liver support systems, which has been analyzed for improving the important system component such as cell source and other culture and circulation conditions for the maintenance of the liver-specific functions, have been described.

Obtaining a good socket fit is an iterative process dependent on the skill and experience of the prosthetist creating it, and requiring individualisation based on the size and shape. There is no standard measurement system used to aid prosthetic socket creation, despite the severe impacts on physical health and quality of life if one is ill-fitting. Pressure sensors embedded in a prosthetic socket were used to collect data at the socket-residuum interface. To choose an interpolation method, a 2D grid was used, with previously collected walking test pressure data, to simplify the sensor array with a border for extrapolation. Four multivariable interpolation methods were evaluated to create a colour map of the pressure data. Radial Basis Function interpolation was chosen as it produced a clear image with a graduated interpolation between data points and was used to create a colour map across the surface of a 3D prosthetic socket model. For the model to be accessible to clinical audiences, a desktop application was created using PyQt to view the model. The created application allowed for connection to the sensors via Bluetooth, with the pressure data updating the colour map on the 3D model in real-time. The created application shows the potential for a clinical product, however further development informed by feedback from rehabilitation clinicians and prosthesis users is required

Obtaining a good socket fit is an iterative process dependent on the skill and experience of the prosthetist creating it and requires individualisation based on the size and shape. There is no standard measurement system used to aid prosthetic socket creation despite the severe impacts on physical health and quality of life if one is ill fitting. Pressure sensors embedded in a prosthetic socket were used to collect data at the socket–residuum interface. To choose an interpolation method, the sensor array was simplified to a 2D grid with a border for extrapolation and tested using previously collected walking test pressure data. Four multivariable interpolation methods were evaluated to create a colour map of the pressure data. Radial basis function interpolation was chosen, as it produced a clear image with a graduated interpolation between data points, and was used to create a colour map across the surface of a 3D prosthetic socket model. For the model to be accessible to clinical audiences, a desktop application was created using PyQt to view the model. The application allowed for connection to the sensors via Bluetooth, with the pressure data updating on the 3D model in real time. Clinician feedback on the application showed the potential for a clinical product; however, further development informed by feedback from rehabilitation clinicians and prosthesis users is required.