Remote Incontinence Care Innovation

大小便失禁是指无法控制自己的尿液或大便，在老年人、痴呆症患者和其他教员日渐衰弱的情况下最为常见；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)，至少有一半的老年人口患有大小便失禁。为此，Connected Health和Arrow Electronics开发了一种创新的、获得专利的非侵入性尿失禁监测器，名为airCept。独特的是，AirCept拥有成为远程和完全非接触式设备的能力。AirCept扫描大小便失禁患者周围的环境空气，寻找湿润或肮脏的症状。在检测到后，airCept会向敬业的工作人员发送警报，以便迅速做出管理良好的护理反应。作为远程医疗产品，所有相关的技术合规性指南均得到遵守，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部门全面验证这项技术，包括但不限于医院护理、疗养院护理、百代护理、居家/家庭护理、临终关怀、新生儿护理。此外，申请者专有的移动和网络应用程序不仅可以提醒护理人员注意大小便失禁事件，还可以让护理人员应用布里斯托尔大便图表输入。随着这些确认输入和活动细节被记录在云中，申请者已经开始与Microsoft Insiers Labs合作，将机器学习应用于他们的技术，以期提高性能，并开始查看可能产生的其他相关见解，例如通过厕所窗口促进大小便失禁、频繁尿路感染、便秘等。拥有这些见解可能会提供一种关于失禁护理的全新措施。通过这一项目，该项目将开发100个完全经过认证的单位，以便在所有适用的医疗保健部门进行测试部署。这些测试演示将允许对技术性能进行完整的分析，提供对云成本、用户反馈等实际问题的深入见解，所有这些都将验证产品并允许进行任何微小的更改。此外，也是重要的一点，将需要大量的单位开始提供足够大的数据集，以确定实施机器学习的可行性，这将是实施大小便促进功能所必需的。

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.