Dataset Information

Multichannel Flexible Pulse Perception Array for Intelligent Disease Diagnosis System.

ABSTRACT: Pressure sensors with high sensitivity, a wide linear range, and a quick response time are critical for building an intelligent disease diagnosis system that directly detects and recognizes pulse signals for medical and health applications. However, conventional pressure sensors have limited sensitivity and nonideal response ranges. We proposed a multichannel flexible pulse perception array based on polyimide/multiwalled carbon nanotube-polydimethylsiloxane nanocomposite/polyimide (PI/MPN/PI) sandwich-structure pressure sensor that can be applied for remote disease diagnosis. Furthermore, we established a mechanical model at the molecular level and guided the preparation of MPN. At the structural level, we achieved high sensitivity (35.02 kPa^-1) and a broad response range (0-18 kPa) based on a pyramid-like bilayer microstructure with different upper and lower surfaces. A 27-channel (3 × 9) high-density sensor array was integrated at the device level, which can extract the spatial and temporal distribution information on a pulse. Furthermore, two intelligent algorithms were developed for extracting six-dimensional pulse information and automatic pulse recognition (the recognition rate reaches 97.8%). The results indicate that intelligent disease diagnosis systems have great potential applications in wearable healthcare devices.

SUBMITTER: Liu T

PROVIDER: S-EPMC10062340 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Multichannel Flexible Pulse Perception Array for Intelligent Disease Diagnosis System.

Liu Tiezhu T Gou Guang-Yang GY Gao Fupeng F Yao Pan P Wu Haoyu H Guo Yusen Y Yin Minghui M Yang Jie J Wen Tiancai T Zhao Ming M Li Tong T Chen Gang G Sun Jianhai J Ma Tianjun T Cheng Jianqun J Qi Zhimei Z Chen Jiamin J Wang Junbo J Han Mengdi M Fang Zhen Z Gao Yangyang Y Liu Chunxiu C Xue Ning N

ACS nano 20230130 6

Pressure sensors with high sensitivity, a wide linear range, and a quick response time are critical for building an intelligent disease diagnosis system that directly detects and recognizes pulse signals for medical and health applications. However, conventional pressure sensors have limited sensitivity and nonideal response ranges. We proposed a multichannel flexible pulse perception array based on polyimide/multiwalled carbon nanotube-polydimethylsiloxane nanocomposite/polyimide (PI/MPN/PI) sa ...[more]

PMID: 36716225

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Project description:Background: Currently, Parkinson's disease (PD) diagnosis is mainly based on medical history and physical examination, and there is no objective and consistent basis. By the time of diagnosis, the disease would have progressed to the middle and late stages. Pilot studies have shown that a unique smell was present in the skin sebum of PD patients. This increases the possibility of a noninvasive diagnosis of PD using an odor profile. Methods: Fast gas chromatography (GC) combined with a surface acoustic wave sensor with embedded machine learning (ML) algorithms was proposed to establish an artificial intelligent olfactory (AIO) system for the diagnosis of Parkinson's through smell. Sebum samples of 43 PD patients and 44 healthy controls (HCs) from Fourth Affiliated Hospital of Zhejiang University School of Medicine, China, were smelled by the AIO system. Univariate and multivariate methods were used to identify the significant volatile organic compound (VOC) features in the chromatograms. ML algorithms, including support vector machine, random forest (RF), k nearest neighbor (KNN), AdaBoost (AB), and Naive Bayes (NB), were used to distinguish PD patients from HC based on the VOC peaks in the chromatograms of sebum samples. Results: VOC peaks with average retention times of 5.7, 6.0, and 10.6 s, respectively, corresponding to octanal, hexyl acetate, and perillic aldehyde, were significantly different in PD and HC. The accuracy of the classification based on the significant features was 70.8%. Based on the odor profile, the classification had the highest accuracy and F1 of the five models with 0.855 from NB and 0.846 from AB, respectively, in the process of model establishing. The highest specificity and sensitivity of the five classifiers were 91.6% from NB and 91.7% from RF and KNN, respectively, in the evaluating set. Conclusions: The proposed AIO system can be used to diagnose PD through the odor profile of sebum. Using the AIO system is helpful for the screening and diagnosis of PD and is conducive to further tracking and frequent monitoring of the PD treatment process.

Project description:Recent advances in flexible pressure sensors have fueled increasing attention as promising technologies with which to realize human epidermal pulse wave monitoring for the early diagnosis and prevention of cardiovascular diseases. However, strict requirements of a single sensor on the arterial position make it difficult to meet the practical application scenarios. Herein, based on three single-electrode sensors with small area, a 3 × 1 flexible pressure sensor array was developed to enable measurement of epidermal pulse waves at different local positions of radial artery. The designed single sensor holds an area of 6 × 6 mm2, which mainly consists of frosted microstructured Ecoflex film and thermoplastic polyurethane (TPU) nanofibers. The Ecoflex film was formed by spinning Ecoflex solution onto a sandpaper surface. Micropatterned TPU nanofibers were prepared on a fluorinated ethylene propylene (FEP) film surface using the electrospinning method. The combination of frosted microstructure and nanofibers provides an increase in the contact separation of the tribopair, which is of great benefit for improving sensor performance. Due to this structure design, the single small-area sensor was characterized by pressure sensitivity of 0.14 V/kPa, a response time of 22 ms, a wide frequency band ranging from 1 to 23 Hz, and stability up to 7000 cycles. Given this output performance, the fabricated sensor can detect subtle physiological signals (e.g., respiration, ballistocardiogram, and heartbeat) and body movement. More importantly, the sensor can be utilized in capturing human epidermal pulse waves with rich details, and the consistency of each cycle in the same measurement is as high as 0.9987. The 3 × 1 flexible sensor array is employed to acquire pulse waves at different local positions of the radial artery. In addition, the time domain parameters including pulse wave transmission time (PTT) and pulse wave velocity (PWV) can be obtained successfully, which holds promising potential in pulse-based cardiovascular system status monitoring.

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Multichannel Flexible Pulse Perception Array for Intelligent Disease Diagnosis System.

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Multichannel Flexible Pulse Perception Array for Intelligent Disease Diagnosis System.

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