10033772Automatic identification of cardiorespiratory biomarkers for remote management of chronic conditionsClosedCollaborative R&DInnovate UKEarly detection of clinical deterioration in patients can help reduce admissions to intensive care units (ICUs), cardiac arrests, sepsis, and deaths. Deteriorations commonly manifest themselves early via very subtle changes in body signals, such as those directly generated by cardiac and respiratory functions. Accurately measuring those signals and computing clinical metrics (commonly referred to as "Early Warning Scores"), is essential in allowing healthcare professionals to identify whether a patient is at risk. Unfortunately, current methods to measure these signals, and subsequently identifying deteriorations, are suboptimal. This leads to very significant, and sometimes tragic, mistakes. It has been estimated that poor monitoring is implicated in around 31% of preventable deaths and is associated with over 80% of severe adverse events. The aim of this project is to add intelligence into the existing Acurable devices which are very small and patient friendly. This will make it possible to extract automatically physiological parameters which are important within the context of deteriorations at home. The unique physical sensing characteristics of Acurable devices will allow the extraction and interpretation of a much wider set of clinical indicators of deterioration than was ever possible with such a small device before. This will consequently eliminate the limitations of other unobtrusive methods, and minimise the risk of life-threatening deteriorations being missed or caught too late.