Intelligent monitoring of home health devices to track, label and alert changes in heart health.

随着医疗保健系统（例如NHS）的压力越来越大，人们对这些医疗保健系统所能提供的服务的期望也越来越高（CQC越来越多地要求提供良好护理的证据），健康和医疗设备大量迁移到家庭。同样重要的是，要平衡相关信息的范围和简单的表达，以便临床医生或自治系统（可以在必要时产生适当的警报/消息）易于吸收。由于医疗保健数据是相对于患者的，因此在不增加临床医生工作量的情况下，跟踪数小时、数天、数月和数年的变化非常重要。这项工作将通过开发一种新的智能监测算法来解决这个问题，该算法可以检测复杂生理信号的细微变化，从而实现实时和长期监测的自主警报触发、早期干预和知情决策。这种新算法将适合直接嵌入智能设备（例如智能手表）、独立物联网中心或云中，作为更大的数字健康框架的一部分。这笔资金将用于验证方法。这项工作的结果将被用作“概念证明”，以表明该方法是有效的，并且适合规模化。这项工作将由Brimstage工程解决方案有限公司的智能监测专家John Kenny博士负责

As healthcare systems (e.g. NHS) have become increasingly stressed and the expectation of what these healthcare systems can deliver has become greater(Increasingly, CQC requires evidence that good care is being provided), there has been a significant migration of health and medical devices into the home. It is also vital to balance the range of relevant information with a simplicity of presentation to allow easy assimilation by clinicians or indeed by autonomous systems (that can generate appropriate alerts/messages when necessary).As healthcare data is relative to the patient, it is important to track changes over hours, days, months and years without increasing the workload of the clinician.This work will address this issue by developing a novel intelligent monitoring algorithm to detect subtle changes in complex physiological signals enabling autonomous alert triggering, early intervention and informed decision making in real time and in long term monitoring.The novel algorithm will be suitable to be embedded directly in a smart device (e.g. a smart watch), a standalone IOT hub, or in the cloud as part of a larger digital health framework.The funding will be used to validate the methodology. The results from this work will be used as 'proof of concept' to show that the method works and would be suitable to scale.This work will be delivered by Dr John Kenny, an expert in intelligent monitoring, from Brimstage Engineering Solutions Ltd