跳至主要内容
临床试验/NCT07376993
NCT07376993进行中(未招募)不适用

Pulse Signal Acquisition in Patients With Heart Failure

National Heart Centre Singapore1 个研究点 分布在 1 个国家目标入组 60 人开始时间: 2023年4月12日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
进行中(未招募)
入组人数
60
试验地点
1
主要终点
AI-developed Heart Failure detection algorithm

研究概览

简要总结

Heart Failure (HF) is usually a chronic condition that gradually gets worse. The heart muscle becomes weaker and has trouble pumping blood to nourish the cells in human body. General symptoms are breathlessness, fatigue, ankle swelling. Accurate and timely diagnosis is crucial to ensure patients receive appropriate treatment. Patients often present to primary care clinicians, however diagnosis by primary care clinicians is inaccurate as symptoms and signs commonly overlap with other conditions. Only 26% of patients with a suspected HF have a confirmed diagnosis after formal investigation according to diagnostic criteria. There is a strong demand to develop an accurate, easy-to-use, costeffective device to detect HF in primary clinics or even by patients themselves before it is too late to modify the natural history of the disease.

TCM palpation provides a simple, cheap, and non-invasive approach for diagnosis and evaluation of the severity of HF, and does not involve use of expensive equipment. There are several specific pulse patterns associated with the clinical manifestation of HF. One of the project collaborators, a TCM physician with a PhD in Chinese Medicine, explained that patients with HF usually have alternating pulse strengths, strong pulse and subsequent weak pulses. The various degrees of severity can be readily manifested as Jiemai, Cumai, and Daimai on the pulse palpation. Based on the investigators' preliminary sensor test results, these pulse features can be easily detected using a micro tubular epidermal sensor, likewise developed by the investigators. Therefore, the investigators propose to use their micro tubular epidermal sensor to develop a TCM pulse analyser, which can be used by primary care clinicians and patient themselves to detect HF in a timely and accurate manner.

研究设计

研究类型
Interventional
分配方式
Na
干预模型
Single Group
主要目的
Supportive Care
盲法
None

入排标准

年龄范围
35 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Age 35 years and above.
  • The recruited patients should have been diagnosed by NHCS's Doctor in charge with HF.
  • Ability to provide informed consent.

排除标准

  • - Pregnant Women as their TCM pulse signal maybe different from normal (non-pregnant) time.

研究组 & 干预措施

Intervention

Experimental

Pulse signal measurement using measurement device

干预措施: Pulse Measurement (Device)

结局指标

主要结局

AI-developed Heart Failure detection algorithm

时间窗: On the day of enrollment

To develop pulse pattern feature extraction, selection, and classification models using AI approaches with a premier focus on HF detection, based on TCM theory.

Pulse data acquisition from HF patients and non-HF people

时间窗: On the day of enrollment

To collect pulse data from HF patients and non-HF people to train and test the machine learning models developed based on AI methods.

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Sponsor

研究点 (1)

Loading locations...

相似试验