Home telecare has emerged as an alternative solution to the problem of delivering primary healthcare services to an increasingly aged population, particularly those suffering chronic disease conditions. However, there are some major challenges relating to data management and interpretation facing the home telecare paradigm that degrade its efficacy and impede its adoption; a decision support system (DSS) promises to be one of the best solutions to address these challenges. Recently, DSSs have

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... come more widely accepted as a support tool for use with telecare systems, helping monitoring clinicians to summarise and digest what would otherwise be an unmanageable volume of data. Such systems are expected to become increasingly prominent in primary care, as telecare systems provide additional clinical measurement capabilities, supported by improving internet infrastructure and penetration throughout the world. One of the pillars of a home telecare system is the performance of unsupervised physiological self-measurement by patients in their own homes. Such measurements are prone to error and noise artifact, often due to poor measurement technique and ignorance of the measurement and transduction principles at work. These errors can degrade the quality of the recorded signals and ultimately degrade the performance of the DSS system which is aiding the clinician in their management of the patient. This thesis focuses the development of algorithms capable of automatically assessing the quality of two physiological measurements commonly acquired by a home telecare system, namely pulse oximetry and blood pressure (BP), which are both prone to artifact-related noise and interference. In developing an algorithm for automated quality assessment of pulse oximetry signals, a novel method to detect movement related noise has been developed and verified with a manually annotated gold standard (GS), performed by experts. This noise detection method relies on morphological analysis of the photoplethysmogram (PPG) signal, since ther [...]