Implementation of new 3D printed & advanced materials sensors for the bio analysis of dysphagia patients

实施新的3D打印

• 批准号: 2726166
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2726166
• 关键词: Implementation; new; 3D; printed; advanced

Dysphagia is difficulty in swallowing. Although classified under "symptoms and signs" in ICD-10, in some contexts it is classified as a condition in its own right. It may be a sensation that suggests difficulty in the passage of solids or liquids from the mouth to the stomach, a lack of pharyngeal sensation or various other inadequacies of the swallowing mechanism. Dysphagia is a common secondary symptom of many diseases, for example, 50-75% of stroke patients suffer from Dysphagia. In 2018, Stroke of the Nation, stated over 100,000 people suffer stroke yearly in the UK, with 1.2 million stroke survivors. This equates to 600,000- 850,000 dysphagia sufferers within the stroke cohort alone (pre-SARS-CoV-2/COVID 19). Viscgo estimates 187,000 UK yearly aspirational pneumonia cases. Adverse outcomes lead to avoidable illness and prolonged hospitalisation. Incorrect intervention can impede treatment, increase cost, length of hospitalisation stays and increase risk of severity or death.Current state of art to treat dysphagia include video fluoroscopy, a fiberoptic endoscopic evaluation of swallowing (FEES) test and diagnostic tools which are prohibitively expensive, inconclusive, and impractical to use regularly. Descriptor categorisations, which are inaccurate, time-consuming and require multiple components and dexterity (which also leads to user conflict), are intended for training only and are not recorded.Currently, speech and language therapists perform specific assessments when treating patients suffering from dysphagia. These assessments include recording and evaluation using tests (video fluoroscopy and FEES) that are then evaluated via a process of multiple pathways. These pathways are determined from results which are purely observational and therefore open to interpretation and as such are subjective. There are hundreds of different tests (and combination of these tests) currently used. Examples of tests include the turning of the patients head to one side and observing the swallowing function in the throat (eg speed of swallow, coughing or spluttering) or the nurse applying a compression against the patients throat and observing them whilst they swallow. These tests are all crude and without reliable outcome measures.Viscgo has developed a step change approach to dysphagia. They have developed a sensor capability that can be placed on the patients throat in order to quantitively and reproducibly assess the patients swallowing function. This PhD project will further develop this wearable technology by investigating the use of smart piezoelectric sensor arrays that have the capability to gain functional data to assist in the determination of physiology against food and drink related dependencies. In addition, this throat sensor technology will have the potential to also actively stimulate local and specific muscles involved in swallowing, thus offering a potential treatment to rehabilitate patients suffering from stroke induced dysphagia.

吞咽困难是吞咽困难。尽管在 ICD-10 中被归类为“症状和体征”，但在某些情况下，它本身被归类为一种病症。它可能是一种感觉，表明固体或液体从口腔到胃的通道困难、缺乏咽部感觉或吞咽机制的各种其他缺陷。吞咽困难是许多疾病常见的继发症状，例如50-75%的中风患者患有吞咽困难。 2018 年，《国家中风》报告称，英国每年有超过 10 万人中风，其中 120 万中风幸存者。这相当于仅中风队列（SARS-CoV-2/COVID 19 之前）就有 600,000-850,000 名吞咽困难患者。 Viscgo 估计英国每年有 187,000 例吸入性肺炎病例。不良后果会导致本可避免的疾病和长期住院治疗。不正确的干预可能会阻碍治疗，增加费用、住院时间并增加严重程度或死亡的风险。目前治疗吞咽困难的最先进技术包括视频透视、吞咽光纤内窥镜评估 (FEES) 测试和诊断工具，但这些工具的价格昂贵得令人望而却步。尚无定论，并且定期使用不切实际。描述符分类不准确、耗时且需要多个组成部分和灵活性（这也会导致用户冲突），仅用于培训且不会记录。目前，言语和语言治疗师在治疗吞咽困难患者时会进行具体评估。这些评估包括使用测试（视频透视和 FEES）进行记录和评估，然后通过多种途径进行评估。这些途径是根据纯粹观察的结果确定的，因此可以进行解释，因此是主观的。目前使用了数百种不同的测试（以及这些测试的组合）。测试的例子包括将患者的头转向一侧并观察喉咙的吞咽功能（例如吞咽速度、咳嗽或吐痰），或者护士对患者的喉咙施加压力并观察他们吞咽时的情况。这些测试都很粗糙，没有可靠的结果测量。Viscgo 开发了一种治疗吞咽困难的逐步改变方法。他们开发了一种传感器功能，可以放置在患者喉咙上，以便定量和可重复地评估患者的吞咽功能。该博士项目将通过研究智能压电传感器阵列的使用来进一步开发这种可穿戴技术，该传感器阵列能够获取功能数据，以协助确定与食物和饮料相关的依赖性的生理学。此外，这种喉咙传感器技术还有可能主动刺激参与吞咽的局部和特定肌肉，从而为中风引起的吞咽困难患者的康复提供潜在的治疗方法。