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Longitudinal home-based monitoring of bio signals of bulbar dysfunction to aid prognostication and therapeutic monitoring in MND. The home-based devic

Longitudinal home-based monitoring of bio signals of bulbar dysfunction to aid prognostication and therapeutic monitoring in MND. The home-based devic
对延髓功能障碍生物信号进行纵向在家监测,以帮助 MND 的预测和治疗监测。
批准号:
2841335
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金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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英文摘要
We aim to develop a non-invasive bio-signal recording device designed to be used at home by people living with MND to collect longitudinal data and create a digital twin model of a person's bulbar function focused on swallowing.I will validate the EMG muscle sensors and microphone against a gold standard setup by BIOPAC that researcher Johnny McNulty used in a previous study. I will also validate the IMU against an accelerometer MMR-MOTION R, also used in an earlier study. The validation work will be performed with healthy volunteers.Once validated, I will run a focus group to discuss the device's design and intended use. Following this co-design stage, I will further develop the electronics and power management to make the device portable and wearable. I will also create material to teach patients and carers how to use it. Note: this is not a medical device, but a device used for scientific research. Ethics approval will be required for its use but not MHRA approval.Working with clinical MND expert James Bashford and patient representatives, we will create a list of tasks that we intend the users to carry out while wearing the sensors. These will be simple tasks, easy and quick to carry out regularly at home to collect longitudinal data. First, I will use the raw data to calculate mean, standard deviation, and peak values to observe how they evolve with time. Then, I will use that information to develop a machine-learning model that relates bio-signal data with symptoms. I will then use this to produce a prediction system that identifies parameter changes predictive of symptom evolution.While collecting data weekly at home from the patients themselves, the patients will also be asked to come once a month to the hospital or labs for further tests using high-density surface EMG, Electroglottograph and spirometry. These methods have been used in published papers and I still need to finalise which equipment I will be using.
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基于AI-Home模式的脑肿瘤术后患者康复体系构建及实证研究
  • 批准号:
    2026JJ82675
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2026
  • 负责人:
    王睿
  • 依托单位: