Motion, Artifact Cancelling MIMO Method for Ambulatory Respiratory Rate Monitorin

用于动态呼吸频率监测的运动、伪影消除 MIMO 方法

• 批准号: 8582895
• 负责人: Amit Gore
• 金额: $ 30.22万
• 依托单位: GENERAL ELECTRIC GLOBAL RESEARCH CTR
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8582895
• 关键词: Algorithms; Ambulatory Monitoring; Breathing; Caregivers; Chest; Chronic Obstructive Airway Disease; Clinical; Data; Data Set; Disease; Early Intervention; Electrocardiogram; Electrodes; Evaluation; Event; Future; General Ward; Goals; Government; Health; Heart failure; Home environment; Impedance Plethysmography; Joints; Lead; Lung diseases; Machine Learning; Measurement; Measures; Methods; Michigan; Monitor; Morphologic artifacts; Motion; Outcome; Output; Patients; Pattern; Performance; Persons; Process; Quality of life; Research; Respiration; Shortness of Breath; Signal Transduction; Source; Symptoms; System; Techniques; Testing; Time; Universities; Work; analog; base; clinical practice; computerized data processing; data acquisition; design; digital; electric impedance; experience; human subject; improved; instrument; miniaturize; neglect; novel; prevent; programs; prototype; public health relevance; respiratory; sedentary

DESCRIPTION (provided by applicant): Shortness of breath and difficulty in breathing are directly associated with deteriorating conditions in patients with heart failure (HF) and/or chroni obstructive pulmonary disease (COPD). Continuous monitoring of respiratory status in these patients can alert caregivers to administer early interventions to manage disease symptoms, thus preventing catastrophic events and improving quality of life. Unfortunately, continuous monitoring of respiratory rate and pattern is often overlooked or neglected in clinical practice due to the general difficulty in performing these measurements, especially in non-intubated ambulatory settings. Present measurement methods that capture the patient's airway are most accurate but difficult to administer and often intolerable for the patient, whereas methods that rely on capturing chest motion historically suffer from poor accuracy due to motion artifacts. We propose a MIMO-based motion artifact cancelling multi-lead impedance measurement method for robust ambulatory respiratory rate monitoring. We have recently demonstrated that respiration and motion artifacts are theoretically separable in ambulatory subjects with multi-lead impedance measurements. The motion artifacts are sporadic and localized high energy non-stationary events compared to respiratory signals. Due to the limited dynamic range and quantization errors of the conventional data acquisition system, source separation algorithms struggle to extract reliable respiratory signal information. The proposed MIMO system approach overcomes these limitations by integrating statistical learning directly within analog to digital conversion process. As a result, this miniaturized hardware realization method enables continuous, real-time and power-efficient tracking of the respiratory signal corrupted by motion artifacts. Preliminary study of the MIMO based algorithm has shown promising results for ambulatory respiratory rate monitoring. In this research we plan to develop the optimized hardware prototype of the MIMO system to validate the performance under real ambulatory conditions. We believe that the MIMO based multi-lead imped- ance measurement method is likely to be accepted by both clinicians and patients due to routine use of electrodes. Going forward, in our future work we envision integrating the proposed research with ECG monitoring sharing same set of electrodes to provide continuous and accurate cardiorespiratory information for general ward as well as for home health/wellness monitoring of ambulatory patients.

描述（由申请人提供）：呼吸短促和呼吸困难与心力衰竭（HF）和/或慢性阻塞性肺疾病（COPD）患者的病情恶化直接相关。持续监测这些患者的呼吸状态可以提醒护理人员进行早期干预以管理疾病症状，从而预防灾难性事件并改善生活质量。不幸的是，由于进行这些测量普遍存在困难，尤其是在非插管的门诊环境中，因此在临床实践中经常忽视或忽视呼吸频率和模式的连续监测。捕获患者气道的当前测量方法是最准确的，但是难以管理并且通常对于患者是不可忍受的，而依赖于捕获胸部运动的方法历史上由于运动伪影而遭受较差的准确性。 我们提出了一种基于MIMO的运动伪影消除多导联阻抗测量方法，用于鲁棒的动态呼吸率监测。我们最近已经证明，呼吸和运动伪影理论上是可分离的，在多导联阻抗测量的动态受试者。与呼吸信号相比，运动伪影是零星的和局部的高能量非平稳事件。由于传统数据采集系统的有限动态范围和量化误差，源分离算法难以提取可靠的呼吸信号信息。所提出的MIMO系统方法通过将统计学习直接集成在模数转换过程中来克服这些限制。因此，这种小型化的硬件实现方法使得能够对被运动伪影破坏的呼吸信号进行连续、实时和功率有效的跟踪。 基于MIMO的算法的初步研究已经显示出用于动态呼吸率监测的有希望的结果。在这项研究中，我们计划开发优化的硬件原型的MIMO系统，以验证性能在真实的流动条件下。我们认为，由于电极的常规使用，基于MIMO的多导联阻抗测量方法可能会被临床医生和患者接受。展望未来，在我们未来的工作中，我们设想将拟议的研究与共享同一组电极的ECG监测相结合，为普通病房以及非卧床患者的家庭健康/健康监测提供连续准确的心肺信息。