Multimodal biomedical measurement methods to study brain functions simultaneously with functional magnetic resonance imaging

Abstract Multimodal measurements are increasingly being employed in the study of human physiology. Brain studies in particular can draw advantage of simultaneous measurements using different modalities to analyse correlations, mechanisms and relationships of physiological signals and their dynamics in relation to brain functions. Moreover, multimodal measurements help to identify components of physiological dynamics generated specifically by the brain. This thesis summarizes the study, design and development of non-invasive medical instruments that can be utilized in conjunction with magnetic resonance imaging (MRI). A key challenge in the development of measurement methods is posed by the extraordinary requirements that the MRI environment poses - all materials need to be MR-compatible and the selected instruments and devices must not be affected by the strong magnetic field generated by the MRI scanner nor the MRI by the instruments placed within its scanning volume. The presented methods allow simultaneous continuous measurement of heart rate (HR) and metabolism from the brain cortex as well as pulse wave velocity (PWV) and blood pressure measurements in synchrony with electroencephalography (EEG) and MRI. Furthermore, the thesis explored the reliability and accuracy of the responses gathered by the developed instruments and, using new experimental methods, estimated the propagation of near-infrared light in the human brain. The goal of the novel multimodal measurement environment is to provide more extensive tools for medical researchers, neurologists in particular, to acquire accurate information on the function of the brain and the human body. Measurements have been performed on more than 70 persons using the presented multimodal setup to study such factors as the correlation between blood oxygen level-dependent (BOLD) data and low-frequency oscillations (LFOs) during the resting state.Tiivistelmä Multimodaalisia kuvantamismenetelmiä käytetään enenevässä määrin ihmisen fysiologian ja elintoimintojen tutkimisessa. Erityisesti aivotutkimuksessa samanaikaisesti useammalla modaliteetilla mittaaminen mahdollistaa erilaisten fysiologisten mekanismien ja niiden korrelaatioiden tutkimisen kehon ja aivotoimintojen välillä. Lisäksi multimodaaliset mittaukset auttavat yksilöimään fysiologiset komponentit toisistaan ja identifioimaan aivojen tuottamia fysiologisia signaaleja. Tämä väitöskirja kokoaa tutkimustyön sekä laite- ja instrumentointisuunnittelun ja sen kehittämistyön ei-invasiivisesti toteutettujen lääketieteen mittausmenetelmien käyttämiseksi magneettikuvauksen aikana. Erityishaasteena työssä on ollut magneettikuvausympäristö, joka asettaa erityisvaatimuksia mm. mittalaitteissa käytettäville materiaaleille sekä laitteiden häiriönsiedolle magneettikuvauslaitteen aiheuttaman voimakkaan magneettikentän takia. Kehitettävät mittausmenetelmät eivät myöskään saa aiheuttaa häiriöitä magneettikuvauslaitteen tuottamalle kuvainformaatiolle. Väitöskirjassa esitettävät mittausmenetelmät tekevät mahdolliseksi mitata magneettikuvausympäristössä ihmisen sydämen sykettä, veren virtauksen kulkunopeutta ja verenpaineen vaihteluja sekä aivokuoren metaboliaa - kaikki synkronissa aivosähkökäyrän mittaamisen ja magneettikuvantamisen kanssa. Lisäksi väitöskirjassa tutkitaan kehitettyjen mittausmenetelmien antamaa mittaustarkkuutta sekä arvioidaan lähi-infrapunavalon etenemistä ihmisen aivoissa uudenlaisella menetelmällä. Kehitetyllä multimodaalisella mittausympäristöllä on tavoitteena antaa lääketieteen alan tutkijoille, erityisesti neurologeille, käyttöön mittausmenetelmiä, joiden avulla voidaan tutkia ihmisen aivojen ja kehon välisiä toimintoja aiempaa kattavammin. Laitekokonaisuudella on tutkittu jo yli 70:tä henkilöä. Näissä mittauksissa on tutkittu mm. veren happitasojen hitaita vaihteluja ihmisen aivojen ollessa lepotilassa, ns. resting state -tilassa

Recent technical progression in photoacoustic imaging:towards using contrast agents and multimodal techniques

Abstract For combining optical and ultrasonic imaging methodologies, photoacoustic imaging (PAI) is the most important and successful hybrid technique, which has greatly contributed to biomedical research and applications. Its theoretical background is based on the photoacoustic effect, whereby a modulated or pulsed light is emitted into tissue, which selectively absorbs the optical energy of the light at optical wavelengths. This energy produces a fast thermal expansion in the illuminated tissue, generating pressure waves (or photoacoustic waves) that can be detected by ultrasonic transducers. Research has shown that optical absorption spectroscopy offers high optical sensitivity and contrast for ingredient determination, for example, while ultrasound has demonstrated good spatial resolution in biomedical imaging. Photoacoustic imaging combines these advantages, i.e., high contrast through optical absorption and high spatial resolution due to the low scattering of ultrasound in tissue. In this review, we focus on advances made in PAI in the last five years and present categories and key devices used in PAI techniques. In particular, we highlight the continuously increasing imaging depth achieved by PAI, particularly when using exogenous reagents. Finally, we discuss the potential of combining PAI with other imaging techniques

Discrete wavelet transforms-based analysis of accelerometer signals for continuous human cardiac monitoring

Abstract Measuring cardiac activity from the chest using an accelerometer is commonly referred to as seismocardiography. Unfortunately, it cannot provide clinically valid data because it is easily corrupted by motion artefacts. This paper proposes two methods to improve peak detection from noisy seismocardiography data. They rely on discrete wavelet transform analysis using either biorthogonal 3.9 or reverse biorthogonal 3.9. The first method involves slicing chest vibrations for each cardiac activity, and then detecting the peak location, whereas the other method aims at detecting the peak directly from chest vibrations without segmentation. Performance evaluations were conducted on signals recorded from small children and adults based on missing and additional peaks. Both algorithms showed a low error rate (15.4% and 2.1% for children/infants and adults, respectively) for signals obtained in resting state. The average error for sitting and breathing tasks (adults only) was 14.4%. In summary, the first algorithm proved more promising for further exploration

Photoplethysmography signal analysis to assess obesity, age group and hypertension

Abstract Photoplethysmography (PPG) provides a simple, convenient and noninvasive method to assess pulse oximetry. Several attempts have been made to use PPG also to estimate blood pressure and arterial stiffness. This paper attempts to assess obesity classes, age group, and hypertension classes using PPG measured from the finger. One set of features was derived from the normalized pulse width of PPG and the other from original PPG. The features were calculated based on the pulse decomposition analysis using five lognormal functions and the up-slope of the PPG pulse. Using kNN and SVM as classifiers, the results were validated using leave-one-out validation. Performances of both features sets have no significant difference, and the kNN outperformed the SVM. The best accuracies are 93%, 88%, and 92% for obesity (5 classes), age group (7 classes), and hypertension (4 classes) respectively. These three assessment targets have a strong relationship with arterial stiffness, therefore it also leads to a study about arterial stiffness using PPG. Width normalization to 1 second might affect some features points based on pulse decomposition analysis. This study also found that the up-slope analysis might give good indices when width normalization was employed. However, these findings still require more experiments to gain conclusions that are more comprehensive

Remote diagnostics and monitoring using microwave technique:improving healthcare in rural areas and in exceptional situations

Abstract Interests towards wireless portable medical diagnostics and monitoring systems, which could be used outside hospital e.g. during pandemic or catastrophic situations, have increased recently. Additionally, portable monitoring solutions could partially address widely recognized challenges related to healthcare equality in rural areas. Microwave based sensing has recently been recognized as emerging technology for portable medical monitoring and diagnostics devices since they may enable development of safe, reliable, and low-cost solutions for future’s telemedicine. The aim of this paper is to present the basic idea of microwave -based medical monitoring and discuss its possibilities, advantages, and challenges. In particular, we show that microwaves could be exploited in three pre-diagnostics applications: 1) Detection of abnormalities in the brain with a helmet type of monitoring device, 2) Detection of breast cancer with a self-monitoring vest, 3) Detection of blood clots in leg with an antenna band. The technique is based on detecting differences in radio channel responses caused by the abnormalities having different dielectric properties than the surrounding tissues. Our results of realistic simulations and experimental measurements show that even small-sized abnormalities, e.g. tumors, can change channel characteristics in detectable level

Combined surface electromyography, near-infrared spectroscopy and acceleration recordings of muscle contraction:the effect of motion

Abstract Noninvasive techniques, surface electromyography (sEMG) in particular, are being increasingly employed for assessing muscle activity. In these studies, local oxygen consumption and muscle metabolism are of great interest. Measurements can be performed noninvasively using optics-based methods such as near-infrared spectroscopy (NIRS). By combining energy consumption data provided by NIRS with muscle level activation data from sEMG, we may gain an insight into the metabolic and functional characteristics of muscle tissue. However, muscle motion may induce artifacts into EMG and NIRS. Thus, the inclusion of simultaneous motion measurements using accelerometers (ACMs) enhances possibilities to perceive the effects of motion on NIRS and EMG signals. This paper reviews the current state of noninvasive EMG and NIRS-based methods used to study muscle function. In addition, we built a combined sEMG/NIRS/ACM sensor to perform simultaneous measurements for static and dynamic exercises of a biceps brachii muscle. Further, we discuss the effect of muscle motion in response of NIRS and EMG when measured noninvasively. Based on our preliminary studies, both NIRS and EMG supply specific information on muscle activation, but their signal responses also showed similarities with acceleration signals which, in this case, were supposed to be solely sensitive to motions

Fractional amplitude of physiological fluctuations of resting state fNIRS in Alzheimer’s disease patient and healthy control

Abstract Functional magnetic resonance imaging (fMRI) is a common medical device to diagnose Alzheimer’s disease (AD), but it is not for all subjects due to its cost and other issues. We investigated the potential of functional near-infrared spectroscopy (fNIRS) to separate AD patients from controls as a pre-screening prior to more thorough examination using fMRI. For this purpose, two-channel fNIRS device with 690 nm and 830 nm, sampled at 10 Hz, was placed on the forehead with 3 cm distance between light source and detector to provide resting state fNIRS signals from both sides of pre-frontal cortex. We applied fractional amplitude of physiological fluctuation (fAPF), modified from fractional amplitude of low frequency fluctuation (fALFF), to oxy-, deoxy-, and total-hemoglobin in very low frequency (0.008‐0.1 Hz), respiratory (0.1‐0.6 Hz), and cardiac (0.6‐5 Hz) bands. A t-test at 0.05 significance level was used to evaluate if the fAPF score from AD patients and healthy controls is significantly different. We found that fAPF score of total hemoglobin from both side at cardiac band showed its potential to distinguish AD patients from healthy controls. This finding was in-line with the recent finding that heart failure may co-occur in AD patients with the prevalence of one third of cases

Optics based label-free techniques and applications in brain monitoring

Abstract Functional near-infrared spectroscopy (fNIRS) has been utilized already around three decades for monitoring the brain, in particular, oxygenation changes in the cerebral cortex. In addition, other optical techniques are currently developed for in vivo imaging and in the near future can be potentially used more in human brain research. This paper reviews the most common label-free optical technologies exploited in brain monitoring and their current and potential clinical applications. Label-free tissue monitoring techniques do not require the addition of dyes or molecular contrast agents. The following optical techniques are considered: fNIRS, diffuse correlations spectroscopy (DCS), photoacoustic imaging (PAI) and optical coherence tomography (OCT). Furthermore, wearable optical brain monitoring with the most common applications is discussed

An experimental study of the photoplethysmography waveform analysis on different vessel wall thickness

Abstract Photoplethysmography (PPG) waveform is primary formed by absorbance and scattering of light caused by blood volume changes in the microvascular bed of tissue. The volume of blood is constantly changing due to cardiac activity and various low frequency physiological components, such as, respiration and sympathetic nervous system. Importantly, elastic property of blood vessels and blood pressure also greatly affects the volume of blood and thus PPG waveform inversely contains information on vessel elasticity and pressure that has been studied using e.g., pulse decomposition analysis (PDA) models. We emulated PPG waveform by using a simplified mock circulatory loop mimicking human circulatory system to study how changing elasticity of 3D printed vessels and blood pressure affects the PPG waveform, aiming to validate presented pulse decomposition analysis model for estimating vessel stiffness and blood pressure. The circulatory system built for the study is controlled via custom-made LabView software. Pumping frequency, pressure and flow of blood mimicking liquid can be controlled and accurately measured for a reference. The main analysis relied on the PDA that extracted five log-normal pulses for further analysis. In particular, we focused on the centre parameter of each log-normal pulse and observed it changes depending on the emulated parameters