This PDF file contains the front matter associated with SPIE Proceedings Volume 11638 including the Title Page, Copyright information, and Table of Contents.

Welcome and Introduction to SPIE Photonics West BiOS conference 11638: Biophotonics in Exercise Science, Sports Medicine, Health Monitoring Technologies, and Wearables II

Skin-interfaced wireless wearables for physiological monitoring: Applications in syndromic tracking of COVID19

We have developed a wearable Near Infrared Spectroscopy (NIRS) device to measure the placental oxygenation. The device comprises of six source-detector distances to probe the oxygenation at different tissues. We have measured NIRS signals and tissue thickness in 12 healthy, singleton, pregnant volunteers (week 33.3±3.6 pregnancy). The placental oxygenation calculated for this group ranges from 68% to 89%. However, we found that the calculated placental oxygenation is positively correlated with the thickness of the fat layer. Hence, we are now performing a Monte Carlo simulation on a five-layer model to correct the effect of fat on placental oxygenation.

Fiber optic sensor technology is considered as a promising candidate for the monitoring of biophysical parameters due to its sensitivity to strain and temperature, immunity to electromagnetic interference, lightweight and opportunity to be mounted on the textiles. Therefore, this paper suggests using one of the fiber optic technologies, namely Fiber Bragg Grating (FBG) sensors, for the respiratory rate monitoring of the hospital patients or sportsmen. Two FBG arrays consisting of 5 sensors each have been sewed to two elastic belts. The belts have been put on volunteer‘s chest and abdomen because the expansion of those regions causes the elastic belts to elongate and, as a result, FBG arrays experience strain changes. The use of ten FBGs located in different regions is required to use the diversity technique, which allows increasing the accuracy of the result by combining output from multiple sensing points. Therefore, a special algorithm has been used to analyze the strain pattern detected by all ten FBGs and to reconstruct the respiratory rate based on them. The obtained breathing rate of the volunteer has been compared with the reference rate measured by a mobile application. Several sets of experiments have been performed in order to identify the influence of the volunteer‘s position and speed of breathing on the accuracy of the measurements.

Nowadays many tasks such as medical correlation, surgery and so on almost depend on manpower. Because of occlusions and environmental impacts, artificial intelligence method can help little. For this situation, we design a multicamera stereo vision system which can be used in poor situation to catch and reconstruct certain object. To reduce the environmental impact, infrared devices like cameras, complement lamps and infrared reflection target balls are selected. The system reconstructs object through detecting target balls set on the key position of object instead of directly detect the whole object. When working, the self-adaptive system can choose all or part cameras due to occlusion and lighting conditions to capture pictures containing target spheres. To verify the feasibility and positioning accuracy of this system, we design a 4-DOF mechanical arm and arrange a set of experiments shown in this paper. The whole system can be applied as a real-time and precise auxiliary approach to many object detection tasks such as surgery navigation, position detection and object tracking.

Mechanical ventilation is used to assist spontaneous breathing in critically ill patients such as those suffering from severe cases of COVID-19. There is a need for new technologies to monitor inspiratory muscle pathophysiology during mechanical ventilation to preserve muscle function and improve weaning success. Here we explore the feasibility of using our custom frequency domain diffuse optical spectroscopy platform to extract the oxygenation of the sternocleidomastoid (SCM), an accessory muscle of inspiration. We will present Monte Carlo simulation results of the neck region where the SCM is located as well as initial results from a normal volunteer study.

Wearable devices, with Photoplethysmography (PPG)-based sensors, are helping patients to monitor chronic health conditions outside the clinic. The prime source of PPG signals is the blood volume change in the dermal vasculature. Here, we present a novel approach of using a skin model, containing double vascular layer within the dermis to investigate the pulsatile contribution from the region. Finite Element Method (FEM) is used to design vessels and PPG signals from the wrist are extracted by studying light transport through Monte Carlo simulations. By assessing PPG sensors in common wearables, the influence of obesity on the PPG signals are also investigated.

Heart failure (HF) has a significant impact on patient outcomes and health care costs. Objective monitoring of pitting edema level of a HF patient may help clinicians reduce the volume of patient re-admissions. To address this, ChemImage is developing a Molecular Chemical Imaging (MCI) device for noninvasive measurement of peripheral edema level in HF patients. In an initial clinical study, edema grade was predicted in HF patients with 86% accuracy. Results from a follow-up clinical trial demonstrating the capability of MCI to monitor changes in a HF patient’s peripheral edema over time during the course of treatment will be presented.

We present an innovative, wearable, fiber-free, near-infrared diffuse speckle contrast flowmetry (DSCF) probe that is fixed on the skull for continuous monitoring of cerebral blood flow (CBF) variations in mice during anesthesia, awake, and freely behaving. Results show a small surge when the animal waked up, a mild decrease after the isoflurane washed off, a 37 ± 9% increase during 10%CO₂ inhalation (n = 3), and mild elevations during grooming and walking. These CBF variations are consistent with clinical observations when recovery from anesthesia and impacts by isoflurane, hypercapnia (CO2), and activity-induced cortical excitations.

Cerebral blood flow (CBF) dysregulation has been implicated in a wide variety of conditions. Cerebrovascular reactivity (CVR) to CO₂ may be a biomarker of CBF dysregulation. NIRS-measured regional cerebral tissue oxygen saturation (rSO₂) is a non-invasive measurement made with portable and relatively inexpensive devices. We previously reported that monitoring rSO2 can identify changes in cerebrovascular dynamics in response to hypercapnic breathing challenges. The present study builds on this work, employing rSO₂ to characterize changes in CBF correlates during hypercapnic breathing challenges, with a new focus on correlations with NIRS-measured vital signs. A custom breathing circuit was used to deliver a series of hypercapnic breathing challenges and recovery periods to healthy young adult subjects grouped into three exercise factors. Change in rSO₂ from intra- to pre-challenge (ΔrSO₂) correlated positively with change in heart rate (ΔHRhyp). Athletes showed higher ∆HRhyp than casual and non-exercisers. We previously established that athletes showed higher ΔrSO₂ responses to hypercapnic breathing challenges. While the relationships between ΔrSO₂ and ΔHRhyp and change in end tidal CO₂ (ΔPETCO₂) in response to hypercapnic breathing challenges appears to be in tact in the healthy young adults studied, and more pronounced in athletes, these relationships may not be preserved in cases of compromised CVR. Change in respiration rate correlated negatively with ΔPETCO₂. Establishing baseline values of rSO₂, PETCO₂, HR, and RR may be useful in identifying changes in an individual’s CVR. Combined monitoring of rSO₂, PETCO₂, HR, and RR presents a portable, inexpensive, noninvasive NIRS-based modality for detecting changes in cerebrovascular health.

Wearable devices have found widespread application in recent years as consumer electronics for sports and health tracking. A metric of health which is overlooked in currently available technology is the measurement of oxygen in living tissue, a key component in the cellular energy production. We report on the development of an optical wireless wearable prototype for transcutaneous oxygen monitoring based on the phosphorescence emission of a highly breathable oxygen sensing film. The device is truly wearable, weighs under 20 grams,is completely self-contained, requires no external readout electronics and is highly sensitive to oxygen in the physiological range.

We examined whether brown adipose tissue density (BAT-d), estimated by the total hemoglobin concentration in the supraclavicular region ([total-Hb]sup), and the season of conception, classified into warmer (SW) and colder (SC) seasons, were linked to body mass index (BMI) in adult humans (108 men and 178 women). BMI was significantly higher in low BAT-d participants than in their high BAT-d counterparts, but was not significantly different between SC and SW subjects. BAT-d was significantly higher in SC subjects than in SW subjects. In conclusion, the level of BAT-d is related to the season of conception and BMI in adult humans.

The aim of this study was to investigate the relationship between brown adipose tissue density (BAT-d) and muscle strength, one of the major parameters relating to physical fitness. The total hemoglobin concentration ([Total-Hb]) , an index of BAT-d in the supraclavicular region using near-infrared time-resolved spectroscopy, handgrip strength, and leg-extension strength were measured in winter in healthy adults (n = 27). BAT-d was not correlated with handgrip strength (r = 0.18, p = 0.37), but with 1-RM leg extension (r = 0.41, p < 0.05). A higher leg muscle strength was associated with a higher BAT-d.

Functional near infrared spectroscopy (fNIRS) is used for brain hemodynamic assessment. Cortical hemodynamics are reliably estimated when the recorded signal has a sufficient quality. This is acquired when fNIRS optodes have proper scalp coupling. A lack of proper scalp coupling causes false positives and false negatives. Therefore, developing an objective algorithm for determining fNIRS signal quality is of great importance. In this study, we developed a machine learning-based algorithm for quantitatively rating fNIRS signal quality. Our promising results confirm the efficacy of the algorithm in determining fNIRS signal quality and hence decreasing misinterpretations.

Motion is disruptive to neuroimaging methods. Motion artefacts range from large amplitude and short frequency spikes to drifts in amplitude causing cofounds in the analysis or completely invalidating any analysis, leading to epoch exclusion of data. However, we can only acquire ecologically robust information if subjects are engaging in natural interaction with their environment. Even more so in the case of sports, infants or motor disorder afflicted populations, where movement will happen. We proposed to study the relationship between channel location and Inertial Measuring Unit (IMU) quantified head movements, in order to better understand their effects in fNIRS data. Cerebral oxygenated (O2Hb) and deoxygenated (HHb) haemoglobin were measured bilaterally in prefrontal to frontal and occipital to temporo-parietal regions of healthy individuals. All participants performed controlled head movements in four conditions: Up, Down, measured by pitch IMU values; and Left, Right, measured by yaw IMU values, in varying degrees of movement. We analysed amplitude and coefficient of determination of O2Hb and HHb, within conditions and channel coordinates across subjects. Our results show that smaller angle magnitude movements (bellow 60 degrees in rotation) are significantly different than larger angle magnitude movements (above 75 degrees in rotation) with a p value of 0.0073; and that the Up condition is significantly different than other movement directions with a p value of 0.0001. We conclude that movement artefacts do not depend on area of measurement for the movement conditions studied. We recommend the application of threshold values for the future with the use of the IMU, by ignoring the effects of lower magnitudes of movement, while correcting or removing larger magnitudes. In future motion artefact removal, we recommend using an IMU for optimal head motion correction of cerebral oxygenation signals.

Functional Near-Infrared Spectroscopy (fNIRS) is gaining popularity in detection and classification of cognitive and emotional states. In addition to hemodynamic responses arising from functional activity changes in the brain areas of interest, fNIRS signals contain components related to other physiological processes, such as respiration (frequency oscillations around 0.3 Hz) and cardiac pulsation (around 1 Hz). While heart rate and respiration measures have been successfully used as separate modalities to assess mental workload, these components are often discarded in fNIRS studies during the pre-processing. In this study, we examined whether including features related to heart and breathing rate improves the accuracy of mental workload level classification. Data collected with wearable fNIRS devices from 14 healthy participants performing mental workload task (n-back) were used to extract features for the classification. Machine learning classifiers were trained and tested using conventional features separately and in combination with the features derived from the oscillatory activity of respiration and heart pulsation. By comparing the performance, we demonstrated the effect of including proposed features on the classification accuracy of mental workload. In future studies, the examined features might be beneficial for other classification problems where modulations in heart and breathing rates are expected.

Brown adipose tissue (BAT) is negatively correlates with adiposity in adult humans. Near-infrared time-resolved spectroscopy has been used to noninvasively measure the density of BAT (BAT-d). We examined the relationship between body adiposity and total hemoglobin concentration in the supraclavicular region ([total-Hb]sup), that is a parameter for BAT-d, in healthy children (113 boys and 127 girls, aged 1 month to 5 years). Age and [total-Hb]sup were significant predictors of the Kaup index and subcutaneous adipose tissue thickness. BAT-d, determined by [total-Hb]sup, was negatively associated with body adiposity in infants, which is in line with the result found in adults.

Background: In sports medicine, near infrared spectroscopy (NIRS) is used to measure physiologic parameters of muscle function, and quantify the effects of exercise. Firstline treatment for urinary incontinence (UI) involves pelvic floor muscle (PFM) rehabilitation therapy (PFMT), but currently oxygen kinetic measures to quantify training effect are lacking. Methods: Half-recovery time of hemoglobin difference, HbDiff(½RT), following sustained maximal voluntary contraction (SMVC), is a validated, NIRS-derived, oxygen kinetic parameter used in exercise science and healthcare monitoring, shown previously to be applicable to the PFM in healthy women using a transvaginal NIRS interface. We evaluated if a PFMT training effect could be detected using HbDiff(½RT) measurement in symptomatic women with UI. Results: HbDiff(½RT) data sets were obtained from 7 symptomatic women prior to and following an 8-week, homebased PFMT regimen; these were compared in each individual and with data from 11 asymptomatic controls. A post training treatment effect was evident where HbDiff(½RT) shortened, indicating improved PFM metabolic function. Discussion: PFM NIRS monitoring proved feasible in a heterogeneous group of women with UI, provided a quantifiable kinetic parameter, and proved more comfortable than conventional perineal pressure measurements (perineometry). Importantly, in one subject with UI due to an incomplete spinal cord lesion, and no detectable PFM contractile ability on initial assessment, NIRS enabled a post-PFMT improvement to be detected using PFM oxygen kinetics. Conclusions: Calculation of HbDiff(½RT) following PFM SMVC allows a validated muscle reoxygenation parameter to be applied in evaluation of PFM dysfunction, and to measure training effect from rehabilitation exercise, potentially improving management of UI.

Introduction: Pulse oximetry is commonly used in critical care to monitor changes in arterial oxygen saturation (SpO₂). However, studies have reported that decreases in SpO₂ may lag behind the actual clinical event. Previous studies have demonstrated that cerebral oxygenation monitoring using near-infrared spectroscopy (NIRS) can detect alterations in oxygenation earlier than pulse oximetry. Here, we compare responses of NIRS monitoring of spinal cord tissue oxygenation (TOI) to pulse oximetry SpO₂ during hypoxia. Methods: During a study on optical monitoring of spinal cord hemodynamics in an animal model of spinal cord injury (SCI), episodes of acute (70-80% SpO₂) hypoxia were induced. Six anesthetized Yucatan miniature pigs were studied. A standard pulse oximeter was attached to the ear of the animal and a custom-made NIRS sensor was placed extradurally on the spinal cord. Hypoxia was induced by removing the ventilator from the animal and reattaching it once SpO₂ reached 70% or 80% as reported by the pulse oximeter. Results: 21 episodes of acute hypoxia were analyzed. Upon the start of hypoxia, NIRS TOI responded in 1.8 ± 0.5 seconds, while pulse oximetry SpO₂ responded in 11.4 ± 0.6 seconds (p > 0.0001). Conclusion: NIRS can detect the effects of hypoxia on spinal cord tissue earlier than pulse oximetry can detect arterial oxygenation changes in the periphery. The NIRS sensor may be used as an earlier detector of oxygen saturation changes in the clinical setting than the standard pulse oximeter.

Wide-area temperature monitoring and fever screening to mitigate COVID-19 using a long-wave infrared digital pixel focal plane array camera scanning system and real-time temperature estimation processing is presented. The s ystem enables multi-pose temperature readings of more than 20 people simultaneously over a 90° horizontal x 30° vertical field-of-regard at a 1 Hz update rate and +/- 0.6°F accuracy. The system has been operational in the MIT LL lobby since April 2020.

A newborn infant has an extraordinarily vulnerable and immature central nervous system, which is undergoing rapid structural and functional development. As these infants are pre-verbal and their neurological systems are immature, assessing accurately and treating effectively procedure-related pain is a significant challenge. The nociceptive signals caused by the pain are accompanied by changes in regional blood oxygenation and neuronal activity in the infant’s brain. In this study, we developed a dual-mode Near-Infrared Spectroscopy (NIRS) and electroencephalography (EEG) monitor that can measure regional brain oxygenation and neuronal activity concurrently (safe and non-invasive). The neuronal activity is measured by an innovative low-noise EEG amplifier in both conventional and ultra-low frequency bandwidths. This multimodal recording allows us to investigate the coupling of neuronal activity and the neurovascular system as never before. NIRS and EEG electrodes are miniaturized and unified in one sensor. This modification facilitates the use of a NIRS/EEG device for recording from neonatal subjects. Ten infants, born between 27-35 weeks gestational age, are being recruited from the NICU at BCWH. They are monitored during a single, routine blood draw required for clinical care. In this experiment, we investigate the change of cerebral hemodynamic across 3 phases of blood collection, baseline, heel lance, recovery. Variation of blood flow accompanied with the slow shift of EEG has been detected during the pain stimulus phase. Additionally, the increase of gamma-band correlated to a rise in blood flow is also observed