Functional Near-Infrared Spectroscopy as a Personalized Digital Healthcare Tool for Brain Monitoring

The sustained growth of digital healthcare in the field of neurology relies on portable and cost-effective brain monitoring tools that can accurately monitor brain function in real time. Functional near-infrared spectroscopy (fNIRS) is one such tool that has become popular among researchers and clinicians as a practical alternative to functional magnetic resonance imaging, and as a complementary tool to modalities such as electroencephalography. This review covers the contribution of fNIRS to the personalized goals of digital healthcare in neurology by identifying two major trends that drive current fNIRS research. The first major trend is multimodal monitoring using fNIRS, which allows clinicians to access more data that will help them to understand the interconnection between the cerebral hemodynamics and other physiological phenomena in patients. This allows clinicians to make an overall assessment of physical health to obtain a more-detailed and individualized diagnosis. The second major trend is that fNIRS research is being conducted with naturalistic experimental paradigms that involve multisensory stimulation in familiar settings. Cerebral monitoring of multisensory stimulation during dynamic activities or within virtual reality helps to understand the complex brain activities that occur in everyday life. Finally, the scope of future fNIRS studies is discussed to facilitate more-accurate assessments of brain activation and the wider clinical acceptance of fNIRS as a medical device for digital healthcare.

Dielectrophoretic force measurement of red blood cells exposed to oxidative stress using optical tweezers and a microfluidic chip

Red blood cell (RBC) dysfunction is often associated with a pathological intervention, and it has been proposed as a critical risk factor for certain lethal diseases. Examining the cell viability of RBCs under various physiological conditions is essential and of importance for precise diagnosis and drug discovery in the field of medicine and pharmacy. In this paper, we report a new analytical method that employs dielectrophoretic (DEP) force measurements in absolute units to assess the viability, and potentially the functionality of RBCs. We precisely quantify the frequency-dependent DEP forces of the RBCs by using a micro-electrode embedded chip combined with optical tweezers. DEP characteristics are known to be well-correlated with the viability of biological cells, and DEP forces are measured in both fresh and long-term stored RBCs to investigate the effect that the storage period has on the cell viability. Moreover, we investigate the DEP behavior of RBCs when exposed to oxidative stress and verify whether EDTA protects the RBCs from an oxidant. From the experiments, it is found that the fresh RBCs without oxidative stress display very high DEP forces over the entire frequency range, exhibiting two cutoff frequencies. However, both the RBCs stored for the long-term period and exposed to oxidative stress reveals that there exist no significant DEP forces over the frequency range. The results indicate that the DEP forces can serve as a useful parameter to verify whether the RBCs in certain blood are fresh and not exposed to oxidative stress. Therefore, it is believed that our system can be applied to a diagnostic system to monitor the cell viability of the RBCs or other types of cells.

Application of Near-Infrared Spectroscopy in Neurological Disorders: Especially in Orthostatic Intolerance

Near-infrared spectroscopy (NIRS), a noninvasive optical method, utilizes the characteristic absorption spectra of hemoglobin in the near-infrared range to provide information on cerebral hemodynamic changes in various clinical situations. NIRS monitoring have been used mainly to detect reduced perfusion of the brain during orthostatic stress for three common forms of orthostatic intolerance (OI); orthostatic hypotension, neurally mediated syncope, and postural orthostatic tachycardia syndrome. Autonomic function testing is an important diagnostic test to assess their autonomic nervous systems for patients with symptom of OI. However, these techniques cannot measure dynamic changes in cerebral blood flow. There are many experimentations about study of NIRS to reveal the pathophysiology of patients with OI. Research using NIRS in other neurologic diseases (stroke, epilepsy and migraine) are ongoing. NIRS have been experimentally used in all stages of stroke and may complement the established diagnostic and monitoring tools. NIRS also provide pathophysiological approach during rehabilitation and secondary prevention of stroke. The hemodynamic response to seizure has long been a topic for discussion in association with the neuronal damage resulting from convulsion. One critical issue when unpredictable events are to be detected is how continuous NIRS data are analyzed. Besides, NIRS studies targeting pathophysiological aspects of migraine may contribute to a deeper understanding of mechanisms relating to aura of migraine. NIRS monitoring may play an important role to trend regional hemodynamic distribution of flow in real time and also highlights the pathophysiology and management of not only patients with OI symptoms but also those with various neurologic diseases.

Spontaneous Low-Frequency Cerebral Hemodynamics Oscillations in Restless Legs Syndrome with Periodic Limb Movements During Sleep: A Near-Infrared Spectroscopy Study

BACKGROUND AND PURPOSE: Periodic limb movements (PLM) during sleep (PLMS) are associated with cortical and cardiovascular activation. Changes in cerebral hemodynamics caused by cortical activity can be measured using near-infrared spectroscopy (NIRS). We investigated oscillatory components of cerebral hemodynamics during PLM and different sleep stages in restless legs syndrome (RLS) patients with PLMS. METHODS: Four female RLS patients with PLMS, and four age- and sex-matched normal controls were included. PLM and sleep stages were scored using polysomnography, while the spontaneous cerebral hemodynamics was measured by NIRS. The phase and amplitude of the cerebral oxyhemoglobin concentration [HbO] and the deoxyhemoglobin concentration [Hb] low-frequency oscillations (LFOs) were evaluated during each sleep stage [waking, light sleep (LS; stages N1 and N2), slow-wave sleep (stage N3), and rapid eye movement (REM) sleep]. In RLS patients with PLMS, the cerebral hemodynamics during LS was divided into LS with and without PLM. RESULTS: The cerebral hemodynamics activity varied among the different sleep stages. There were changes in phase differences between [HbO] and [Hb] LFOs during the different sleep stages in the normal controls but not in the RLS patients with PLMS. The [HbO] and [Hb] LFO amplitudes were higher in the patient group than in controls during both LS with PLM and REM sleep. CONCLUSIONS: The present study has demonstrated the presence of cerebral hemodynamics disturbances in RLS patients with PLMS, which may contribute to an increased risk of cerebrovascular events.

Study on an Image Reconstruction Algorithm for 3D Cartilage OCT Images (A Preliminary Study) / 의학물리

Recently, optical coherence tomography (OCT) has demonstrated considerable promise for the noninvasive assessment of biological tissues. However, OCT images difficult to analyze due to speckle noise. In this paper, we tested various image processing techniques for speckle removal of human and rabbit cartilage OCT images. Also, we distinguished the images which get with methods of image segmentation for OCT images, and found the most suitable method for segmenting an image. And, we selected image segmentation suitable for OCT before image reconstruction. OCT was a weak point to system design and image processing. It was a limit owing to measure small a distance and depth size. So, good edge matching algorithms are important for image reconstruction. This paper presents such an algorithm, the chamfer matching algorithm. It is made of background for 3D image reconstruction. The purpose of this paper is to describe good image processing techniques for speckle removal, image segmentation, and the 3D reconstruction of cartilage OCT images.