Remote Incontinence Care Innovation

失禁是无法控制自己的尿液或排便，这在老年人、痴呆症患者和其他功能减退的患者中最常见;它也是长期护理入院的主要驱动力（Tariq 2004）。在爱尔兰、英国和北美的养老院（CH）中，至少有一半的老年人患有尿失禁。 为此，Connected Health和Arrow Electronics开发了一种创新的专利非侵入式失禁监测仪，称为airCeption。独特的airCeption拥有成为远程和完全无接触设备的能力。airCeption扫描失禁患者周围的环境空气，寻找潮湿或污染事件。一旦检测到，airCeption会向专门的工作人员发送警报，以便做出迅速和管理良好的护理响应。 作为一个远程医疗保健产品，所有相关的技术合规性准则都得到遵守，包括GDPR，HIPPA，ENISA，CoP和Azure最佳实践，以及通过FCC + CE（ETSI）预扫描检查。 现在的目标是在相关医疗保健领域全面验证该技术，包括但不限于临终关怀、护理家庭护理、EMI护理、家庭/家庭护理、临终关怀、新生儿护理。 此外，申请人专有的移动的和网络应用不仅提醒护理人员注意失禁事件，而且还使护理人员能够应用布里斯托图表输入。通过在云中记录这些确认输入和事件细节，申请人已经开始与微软内部人员实验室合作，将机器学习应用于他们的技术，以期提高性能并开始查看可能生成的其他相关见解，例如通过浏览窗口来促进腹泻，通过频繁的UI引起尿路感染，便秘等。具有这种容易获得的见解可以提供围绕失禁护理的全新措施。 有了这个，这个项目将导致100个完全认可的单位的发展，通过所有适用的医疗保健部门的测试部署。这些测试演示将允许对技术性能进行完整的分析，对云成本，用户反馈等实际问题提供深入的见解，所有这些都将验证产品并允许任何小的更改。此外，重要的是，将需要大量的单元来开始提供足够大的数据集，以确定实施机器学习的可行性，这将是实施促销功能所需的。

Incontinence is the inability to control one's urine or bowel movements, it's most common among older people, those with dementia, and other faculty diminishing conditions; it is also a major driving force in long-term care admissions (Tariq 2004). At least half of the elderly population within Irelands, Britain's and North America's care homes (CH) suffer from incontinence. To this end, Connected Health and Arrow Electronics have developed an innovative and patented non-invasive incontinence monitor, called airCeption. Uniquely airCeption boasts the ability to be a remote and fully no-contact device. airCeption scans the ambient air surrounding an incontinent sufferer, searching for wetting or soiling episodes. Upon detection, airCeption transmits an alert to a dedicated member of staff allowing a prompt and well-managed care response. Being a remote healthcare offering, all the relevant technical compliance guidelines are adhered to, including, GDPR, HIPPA, ENISA, CoP & Azure Best Practice, as well as having FCC + CE(ETSI) pre-scan checks passed. The goal now is to fully validate the technology across relevant healthcare sectors, which include, though not limited to, Hosptial Care, Nursing-home Care, EMI Care, Domiciliary/Home Care, Hospice Care, Neonatal Care. Additionally, the applicants proprietary mobile and web applications not only alert carers to incontinent events, though too, enables the carers, to apply bristol stool chart inputs. With these confirmation inputs and event details being recorded, in the cloud, the applicants have started working with the Microsoft Insiders Labs to apply machine learning to their technology, with the view to improve performance and to start looking at other relevant insights that may be generated e.g via toileting windows to promote continence, urinary tract infection via frequent UIs, constipation etc. Having such insights readily available may provide an entirely new measure around incontinence care. With this, this project will lead to the development of 100 fully accredited units, for test deployment through all applicable healthcare sectors. These test demonstrations will allow a complete analysis of the technology performance, provide deep insights into practical matters such as cloud costs, user feedback etc all of which will validate the offering and allow for any small alterations. Furthermore and importantly the volume of units will be required to start providing a large enough data set to determine the feasibility of implementing machine learning, which will be required for the implementation of continence promotion features.