Study of wrist pulse signals using time domain spatial features

Rangaprakash, D.; Dutt, D. Narayana

doi:10.1016/j.compeleceng.2014.12.016

Cited by 47 publications

(25 citation statements)

References 15 publications

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“…A typical wrist pulse signal has two peaks in general. 33 Similarly, the measured radial artery pulse exhibits two clearly distinguishable peaks as shown in Figure 2g: systolic and diastolic peaks marked 'a' and 'b,' respectively. Important parameters such as reflection index (RI) and stiffness index (SI) can be calculated as follows: (1) RI = magnitude of diastolic peak (b)/ magnitude of systolic peak (a) × 100 (%) and (2) arterial SI = subject height (h)/transit time (ΔT DVP ).…”

Section: Resultsmentioning

confidence: 99%

Polyurethane foam coated with a multi-walled carbon nanotube/polyaniline nanocomposite for a skin-like stretchable array of multi-functional sensors

Hong

Park

et al. 2017

NPG Asia Mater

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Body-attachable sensors can be applied to electronic skin (e-skin) as well as safety forewarning and health monitoring systems. However, achieving facile fabrication of high-performance, cost-effective sensors with mechanical stability in response to deformation due to body movement is challenging. Herein we report the material design, fabrication and characteristics of a skin-like stretchable array of multi-functional (MF) sensors based on a single sensing material of polyurethane foam coated with multi-walled carbon nanotube/polyaniline nanocomposite, which enables simultaneous detection of body temperature, wrist pulse and ammonia gas. These sensors exhibit high sensitivity, fast response and excellent durability. Furthermore, the fabricated sensor array shows stable performance under biaxial stretching up to 50% and attachment to skin owing to the use of directprinted Galinstan liquid metal interconnections. This work proposes a facile method for fabrication of high-performance, stretchable MF sensors via appropriate selection of sensor design and functional materials that are applicable to e-skin and health monitoring systems. NPG Asia Materials (2017) 9, e448; doi:10.1038/am.2017.194; published online 17 November 2017 INTRODUCTIONWearable electronics have attracted considerable attention for use in electronic skin (e-skin) and health monitoring systems in order for a comfortable and secure life. 1-5 e-Skin is a human interactive device that can simultaneously sense signals from the body and respond to the environment. Thus it should be capable of measuring the five types of senses (taste, sight, hearing, olfactory and touch sensation) with high sensitivity and show mechanical stability against deformation due to skin movement. As a result, e-skin is required to be very thin and have a strain-relaxed design. 6 Because of the increasing importance of e-skin, extensive efforts have been undertaken to develop various sensors with high sensitivity. 7 Beyond the conventional sensor that can detect a single stimulus, novel advanced sensors for simultaneous monitoring of multiple stimuli (multi-functional (MF) sensors) have been actively investigated. 8,9 For practical application of such MF sensors, it is necessary to eliminate the interference between different stimuli that is commonly observed in conventional MF sensors, 10 in addition to fabricating cost-effective sensors on a deformable substrate. Development of MF sensors that transduce different stimuli into separate signals can intrinsically minimize signal interference, thus allowing for sensitive detection of multiple parameters, such as temperature and pressure, in a single device without decoupling analysis. Many power-

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Section: Resultsmentioning

confidence: 99%

Polyurethane foam coated with a multi-walled carbon nanotube/polyaniline nanocomposite for a skin-like stretchable array of multi-functional sensors

Hong

Park

et al. 2017

NPG Asia Mater

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“…A matched comparison environment is setup to compare the performance between algorithms in organ inflammations classification. Repeated simulation is carried out for [10,11,14,32] while using the identical datasets and 10-fold cross validation. It is concluded that the proposed MOGA-SVM improves the Acc from 6.9% to 13.4%.…”

Section: Comparison Between Proposed and Related Workmentioning

confidence: 99%

“…Raw comparison between proposed and related work[10,11]. Matched comparison between proposed and related work[10,11,32].…”

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confidence: 99%

A Novel MOGA-SVM Multinomial Classification for Organ Inflammation Detection

Chui

Lytras

2019

Applied Sciences

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Wrist pulse signal (WPS) contains crucial information of humans’ health condition. It can serve as an alternative method for diagnosing of organ inflammation instead of traditional clinical measurement. In this paper, a novel multi-objective genetic algorithm based support vector machine (MOGA-SVM) has been proposed for the multinomial classification of the inflammations of appendix, pancreas, and duodenum. A customized similarity kernel (KCS) has been optimally designed. The performance of multinomial classification using KCS is compared with five types of kernels, linear, radial basis function (RBF), polynomial and sigmoid kernel, as well as mixtures of polynomial and RBF, to verify the effectiveness of KCS. The sensitivity, specificity and accuracy (Acc) of the proposed method are 92%, 91.2%, and 91.6% respectively. The results have demonstrated that KCS improves the accuracy of classification from 8.9% to 59.6%. When compared to related work, the proposed method increases the performance by more than 10%. It is believed that WPS can serve as alternative measures to diagnose organ inflammations.

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“…Dimin Wang et al observed variations in the width of a pulse indicated relaxed or tensed state of subjects [18]. Recurrence plot, Multi scale entropy and approximate entropy methods were applied to analyses pulse variabilities of a wrist pulse [28][29][30][31][32][33]…”

Section: Time Domain Analysismentioning

confidence: 99%

“…Research group measured pulse variability by nonlinear dynamic analysis called approximate entropy (ApEn) and observed that PSD of ApEn of a cardiovascular subject were much lower. Amount of variation in ApEn value used to distinguish various types cardiovascular disease and their physiological adaptabilities [30,31]. Wang et al distinguished Rhythmic and Arrhythmic pulse based on Variation Range (VR) and Variation Coefficient (VC) of pulse interval of time series.…”

Section: Hypertensionmentioning

confidence: 99%

A review of wrist pulse analysis

Gc¹,

Veerabhadrappa²

2019

biomedicalresearch

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In present scenario, the human health condition is being diagnosed by various advanced sophisticated equipments. Moreover, the process of diagnosis is becoming expensive and painful. In ancient Indian Ayurveda and Traditional Chinese Medicine (TCM), wrist pulse was used to diagnose the health status of the subject and to envision the root cause of a disease. According to Ayurveda, a person's health status depends on three essential components and the imbalance of a component is the symptom of a disease. Practitioner determines the unhealthiness of a subject, based on the wrist pulse parameters such as pulse strength, amplitude shape, vega, rhythm, pulse width and transition period. Evaluation of the vital information of the components depends exclusively upon the perception of the practitioner and varies from practitioner to practitioner based on his/her expertise or experience. No modern technique can determine the pathological condition of a subject. The paper presents a review of wrist pulse parameters for diseases like diabetics, hypertension, gastritis, etc.

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Study of wrist pulse signals using time domain spatial features

Cited by 47 publications

References 15 publications

Polyurethane foam coated with a multi-walled carbon nanotube/polyaniline nanocomposite for a skin-like stretchable array of multi-functional sensors

Polyurethane foam coated with a multi-walled carbon nanotube/polyaniline nanocomposite for a skin-like stretchable array of multi-functional sensors

A Novel MOGA-SVM Multinomial Classification for Organ Inflammation Detection

A review of wrist pulse analysis

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