A Novel In-Home Sleep Monitoring System Based on Fully Integrated Multichannel Front-End Chip and Its Multilevel Analyses

IF 3.7 3区 医学 Q2 ENGINEERING, BIOMEDICAL IEEE Journal of Translational Engineering in Health and Medicine-Jtehm Pub Date : 2023-02-24 DOI:10.1109/JTEHM.2023.3248621
Shaofei Ying;Lin Wang;Yahui Zhao;Maolin Ma;Qin Ding;Jiaxin Xie;Dezhong Yao;Srinjoy Mitra;Mingyi Chen;Tiejun Liu
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引用次数: 1

Abstract

Objective: A novel in-home sleep monitoring system with an 8-channel biopotential acquisition front-end chip is presented and validated via multilevel data analyses and comparision with advanced polysomnography. Methods and procedures: The chip includes a cascaded low-noise programmable gain amplifier (PGA) and 24-bit $\Sigma $ - $\Delta $ analog-to-digital converter (ADC). The PGA is based on three op-amp structure while the ADC adopts cascade of integrator feedforward and feedback (CIFF-B) architecture. An innovative chopper-modulated input-scaling-down technique enhances the dynamic range. The proposed system and commercial polysomnography were used for in-home sleep monitoring of 20 healthy participants. The consistency and significance of the two groups’ data were analyzed. Results: Fabricated in 180 nm BCD technology, the input-referred noise, input impedance, common-mode rejection ratio, and dynamic range of the acquisition front-end chip were $0.89 \mu $ Vpp, 1.25 GN), 113.9 dB, and 119.8 dB. The kappa coefficients between the sleep stage labels of the three scorers were 0.80, 0.76, and 0.79. The consistency of the slowing index, multiscale entropy, and percentile features between the two devices reached 0.958, 0.885, and 0.834. The macro sleep architecture characteristics of the two devices were not significantly different (all p $>$ 0.05). Conclusion: The proposed chip was applied to develop an in-home sleep monitoring system with significantly reduced size, power, and cost. Multilevel analyses demonstrated that this system collects stable and accurate in-home sleep data. Clinical impact: The proposed system can be applied for long-term in-home sleep monitoring outside of laboratory environments and sleep disorders screening that with low cost.

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基于全集成多通道前端芯片的新型家庭睡眠监测系统及其多层次分析
目的:提出一种新型的8通道生物电位采集前端芯片家庭睡眠监测系统,并通过多层次数据分析和与先进的多导睡眠图的比较进行验证。方法和程序:该芯片包括级联低噪声可编程增益放大器(PGA)和24位$\Sigma$-$\Delta$模数转换器(ADC)。PGA基于三运算放大器结构,ADC采用级联积分器前馈和反馈(CIFF-B)结构。一种创新的斩波调制输入按比例缩小技术增强了动态范围。所提出的系统和商业多导睡眠图用于20名健康参与者的家庭睡眠监测。分析两组数据的一致性和显著性。结果:采用180nm BCD技术制造的采集前端芯片的输入参考噪声、输入阻抗、共模抑制比和动态范围分别为0.89\mu$Vpp、1.25GN)、113.9dB和119.8dB。三个评分者睡眠阶段标签之间的kappa系数分别为0.80、0.76和0.79。两种设备之间的减速指数、多尺度熵和百分位特征的一致性分别达到0.958、0.885和0.834。两种设备的宏睡眠架构特征没有显著差异(均为p$>;$0.05)。结论:所提出的芯片可用于开发一种尺寸、功耗和成本显著降低的家庭睡眠监测系统。多层次分析表明,该系统收集了稳定、准确的家庭睡眠数据。临床影响:该系统可用于实验室环境外的长期家庭睡眠监测和低成本的睡眠障碍筛查。
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来源期刊
CiteScore
7.40
自引率
2.90%
发文量
65
审稿时长
27 weeks
期刊介绍: The IEEE Journal of Translational Engineering in Health and Medicine is an open access product that bridges the engineering and clinical worlds, focusing on detailed descriptions of advanced technical solutions to a clinical need along with clinical results and healthcare relevance. The journal provides a platform for state-of-the-art technology directions in the interdisciplinary field of biomedical engineering, embracing engineering, life sciences and medicine. A unique aspect of the journal is its ability to foster a collaboration between physicians and engineers for presenting broad and compelling real world technological and engineering solutions that can be implemented in the interest of improving quality of patient care and treatment outcomes, thereby reducing costs and improving efficiency. The journal provides an active forum for clinical research and relevant state-of the-art technology for members of all the IEEE societies that have an interest in biomedical engineering as well as reaching out directly to physicians and the medical community through the American Medical Association (AMA) and other clinical societies. The scope of the journal includes, but is not limited, to topics on: Medical devices, healthcare delivery systems, global healthcare initiatives, and ICT based services; Technological relevance to healthcare cost reduction; Technology affecting healthcare management, decision-making, and policy; Advanced technical work that is applied to solving specific clinical needs.
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