This PDF file contains the front matter associated with SPIE Proceedings Volume 12375, including the Title Page, Copyright information, Table of Contents and Conference Committee lists.

We propose a novel continuous blood pressure monitoring system which is based on an autonomic nervous system, and which considers blood volume simultaneously since both affect blood pressure. An autonomic nervous system regulates blood pressure while blood volume is known to be proportional to the photoplethysmography (PPG) signal. To overcome the limitation of taking blood pressure using a conventional cuff inflating instrument, we designed a system which can achieve continuous blood pressure monitoring. In this research, we used a set of near-infrared light source (940nm) to create a divergent light which was collimated as a uniform beam incident to a wrist surface through a Fourier optics designed transfer lens. We found that the signals became more stable due to the uniform illumination and could be received by a detector. From the signals, we found that the blood volume when converted from blood velocity as measured by an ultrasound probe, showed a strong correlation with the signals. The heart rate variability analyzed from the signals, including time-domain (HR and SDNN) and frequency-domain (LF and HF) indices, could be viewed as physical models since these indices reflect the functions of an autonomic nervous system. Moreover, the research derived regression models can estimate blood pressure. Although it is not common to assess blood pressure from the perspective of an autonomic nervous system and blood flow simultaneously, our research approach seems logical. Our results show the potential for this novel system to be used for blood pressure health monitoring.

Normal brain function is dependent on stable cerebral blood flow and autoregulation. Even when blood pressure fluctuates, cerebral blood flow is maintained. However, the microcirculation of the cortex has not been thoroughly investigated during rapidly induced hypotension. This study aimed to determine oxyhemoglobin (O2Hb) levels, indicative of cortical blood flow changes, during hypotension induced by thigh cuff release. Twenty-one healthy students participated in this study. Each participant was seated in a recumbent position in a quiet room for 5 minutes. Cuffs of digital tourniquets were placed on both thighs and inflated to 250 mmHg for 5 minutes. Following sudden deflation, the participants were observed for 5 minutes. Right (R) and left (L) prefrontal cortex (PFC) O2Hb levels were measured using a multichannel near-infrared spectroscopy system. Using photoplethysmography, the beat-to-beat mean arterial pressure (MAP) was recorded by finger pulse volume. O2Hb and MAP were averaged 1-second epoch throughout the study. MAP decreased from 95.2 ± 9.9 mmHg to 63.5±9.0 mmHg after cuff release. The time from release to the lowest O2Hb was significantly slower than the time from release to the lowest MAP (p < 0.01); time difference, 3.6 ± 2.2 s in the L-PFC and 3.5 ± 1.8 s in the R-PFC. These results suggest that hypotension induced by thigh cuff release decreases the O2Hb levels in both L and R-PFC with a 3.5–3.6 s delay.

A modern application of NIRS moves towards implantable methods to overcome the limitation. In implantable NIRS, the sensor is implanted adjacent to the organ of interest. The implant's mechanical structure, shape, and total volume are crucial to ensuring usability and minimizing invasiveness. Since thinner and smaller implant encapsulation reduces the distance between the electronic circuit of the sensor and the tissue, the equivalent capacitance between the tissue and the implantable system (consisting of the sensor and controller) can increase dramatically. The CMV (Common-Mode Voltage) is a voltage on the patient's body due to electromagnetic and electrical coupling. CMV is an essential noise source for recording biological signals; however, implantable NIRS sensors can induce a more significant noise because of the higher capacitance effect. During the preamplifier, the CMV can appear and be transformed to differential voltage, contaminating the original signal and decreasing the signal-to-noise ratio. Electromagnetic Shielding and a high CMRR (Common-Mode Rejection Ratio) amplifier are conventional methods for preventing noise contamination with common-mode voltage. However, these methods are not robust enough to protect the signal of interest in the presence of high-amplitude CMV. We proposed the active CMV reduction technique to eliminate the effect of CMV and improve the SNR of the NIRS signal. It can measure and eradicate induced CMV by injecting a minimal amount of electric current into the patient non-invasively. This paper proposes an ANC (Active noise cancellation) electronic circuit that eliminates CMV.

Progressive development and innovation have led to a growing number of applications of near infrared spectroscopy (NIRS) becoming clinically relevant. The ability of NIRS technologies to monitor oxygenation and hemodynamic parameters relevant to ensuring that the brain and spinal cord are adequately perfused and oxygenated to meet varying metabolic demands is a key example. Just as the inclusion of pulse oximetry became the standard of care for surgical anesthesia when the importance of the real-time data this new technology provided was recognized 50 years ago, so nowadays cerebral oxygenation monitoring is increasingly widely employed in this context. In parallel, comparable NIRS technologies are now relied on as adjuncts to aid central nervous system monitoring during intensive care of both critically ill patients, and the smallest, most immature premature infants. Such monitoring offers the prospect not only of improving care during critical illness, but also minimizing secondary injury following situations such as intrapartum asphyxia and traumatic spinal cord injury, where the initial neural injury is all too often compounded by secondary damage from intracellular energy failure or ischemia to compromised but potentially recoverable brain cells and neural tissue. The advances that have led to effective NIRS monitoring systems have most often come about because of the willingness of scientists, clinicians and other end-users to collaborate. In this way the most pressing clinical issues are identified and novel solutions generated using the latest physics concepts, newest materials, and increasingly innovative approaches. Key lessons learned in this way, and what several historic advances in biophotonics can teach us are the subject of this review, as they are relevant to the further evolution of NIRS applications in medicine, both to address ongoing complexities of care, and also if we are to take advantage of the opportunities provided by the growing trend for monitoring personal health data as a way to continue to improve health and wellbeing.

Consumer adoption of portable and wearable electronic devices is increasing, particularly for monitoring human health and wellness. Current devices rely on a set of established light emitting diodes that are limited in terms of spectral range, resolution, power efficiency, and signal strength, which collectively hinder the ability to quantify a next generation of biomarkers in a wearable format. A novel photonic platform is proposed, whereby analytical information is captured by using a set of silicon-photonics-based III-V semiconductor lasers operating over near infrared wavelengths. A first step in the analytical utility of this photonic platform is assessed by collecting spectroscopic data for a series of gelatin-based tissue-simulating phantoms. Laser-based diffuse reflectance spectra are collected for a set of seven unique phantom matrixes over a range of temperatures from 20-24 °C. In all, 700 spectra are collected and PLS calibration models are developed for the independent measurements of water content and temperature across this array of phantoms. Standard errors of prediction are 0.30 weight-percent for water content measurements and 0.22 °C for phantom temperature. These initial findings support efforts to follow a path from analytical sensing element to a fully integrated non-invasive wearable electronic device.

Cortical spreading depression (SD), a pathological cortical negative DC potential, is associated with various brain abnormalities. SD is a significant transient and localized relocation of ions within the neurons and spreads slowly like a wave in the brain tissue. SD results from a high extracellular K+ concentration, increasing neuronal excitability and, consequently, brain oxygen consumption. In our previous studies, we developed an electroencephalography (EEG) system capable of recording the SD from the surface scalp of epileptic patients. We demonstrated that SD is associated with seizures in patients with medically intractable epilepsy. In this paper, in addition to EEG measurements, near-infrared spectroscopy (NIRS) was used to measure local brain oxygen consumption during SD and seizures. NIRS is a non-invasive method to measure the hemodynamics of the tissue, such as oxy and deoxyhemoglobin concentrations, representing the gray matter's local neuronal metabolisms. By applying two or more wavelengths in the near-infrared window and measuring the attenuation variations of the relative change in the concentration of deoxyhemoglobin (HHb) and oxyhemoglobin (HbO2), the local oxygen consumption can be estimated. Method: We recorded SD and NIRS simultaneously during epileptiform EEG activities from twelve epileptic patients. Main result: SD occurred in the scalp of epileptic patients and preceded seizures with a varying time lag (0-30 minutes). HHb concentration increased during the SD duration. While HbO2 concentration decreased during the SD duration. Both returned to normal values after the SD event.

Background: Spinal cord injury (SCI) compromises bladder function, including the ability to sense the need to void. Overdistension leads to involuntary leakage and endangers health through upper renal tract pressure damage and autonomic dysreflexia. A monitor warning the bladder is full will allow optimal use of manual expression or intermittent catheterization. Methods: The wearable interface is a silicone sheet worn over the bladder, which incorporates a grid of 4 near-infrared LED transmitters with 3 wavelengths (2 at 950 nm for water detection and 2 of 760 and 850 nm for conventional monitoring of O2Hb and HHb). The system has 8 continuous-wave measurement channels and monitors at 2 different vertical levels to detect variation in bladder fullness; IOD’s of 30 and 40mm provide information at 2 depths. Associations between optical densities during bladder emptying and then during natural filling were compared. Results: Data from 4 male and one female subject were analyzed. The optical densities recorded at the lower vertical locations showed positive correlation with the voiding rate (ratio of scale signal), and O2Hb and HHb concentration changes at higher vertical locations revealed muscle activation prior to voiding. Discussion: This pilot study provides proof of the feasibility of using a 950nm wavelength incorporated into a wearable NIRS bladder monitoring system to transcutaneously and non-invasively detect changes in bladder volume in real-time. Conclusions: Ongoing research is warranted to further evaluate the system as the bladder fills naturally; and establish the clinical value of the data obtained to patients living with spinal cord injury

The rest period in between strength exercises determines how the short-term energy supplies in the muscles are replenished and metabolites are cleared. Near-InfraRed Spectroscopy (NIRS) is a proven method to study oxidative recovery kinetics following exercise. The goal of this study is to develop a model that predicts the oxygenated recovery state, this can help athletes optimize the resumption of exercise. 17 healthy subjects performed a sustained isometric hold in a hand gripper until volitional exertion, Tissue Saturation Index (TSI) was continuously monitored throughout and following exercise by a NIRS sensor (Train.Red PLUS). The oxygenated recovery state was manually categorized by three independent experts into four different phases of recovery; I - a pronounced increase, II - a gentle increase, III - the maximum oxygenated state, and IV - the return to baseline. A Recurrent Neural Network, inspired by Natural Language Processing, was trained and tested on this data, resulting in a model that predicts shifts between phases of recovery. A 5-fold cross-validation analysis resulted in the following average performance: • Recurrent Neural Network: Accuracy: 55.17%, categorical cross-entropy: 1.02351. • Multi-Layer Perceptron: Accuracy: 57.16%, categorical cross-entropy: 0.95201. • XGBoost: accuracy: 44.85%, categorical cross-entropy: 10.1119. In predicting the user’s current state of oxygenated recovery the MLP and RNN are similar in performance, however, the MLP shows erratic behavior, while the RNN generally follows the shift in phases of the ground truth. These capabilities could enable athletes with different fitness goals to design goal-tailored and therefore more efficient training.

Athletes can optimize training performance by measuring the oxygenation level in their muscles using Near-infrared spectroscopy (NIRS). NIRS allows athletes to measure local muscle oxygenation changes and assess performance indicators such as optimal pace or intensity during endurance activities and optimal recovery in endurance and strength activities. A novel NIRS sensor (Train.Red FYER) was developed to enable these measurements. In this this study the stability, accuracy, intra- and inter-variability of muscle oxygenation saturation (SmO2) in 10 sensors using two different phantoms and in-vivo tests, were SmO2 was defined as the percentage of the ratio of oxygenated to total hemoglobin. Stability of three sensors was tested during 3 hours on each phantom. Intra-variability of three sensors was assessed on four different days by two different operators by repositioning the sensor over the same location on both phantoms and on the forearm during resting position. Intra-variability was also assessed during vascular occlusion tests (VOT). Intervariability was assessed between 10 sensors on both phantoms on four different days. For analysis coefficient of variance (CV) was calculated. The sensor showed to be stable on both phantoms (<1% SmO2). Precision tests showed a larger inter-variability (<2% SmO2) than intra-variability (<1% SmO2). Inter-day and inter-operator variability on phantoms were also small (<4% SmO2). In vivo tests on the forearm and VOT showed higher variability (<5% SmO2) than on phantoms. It was shown a stable and precise NIRS sensor for the measurement of SmO2.

The anaerobic threshold (AT) is a point during intense exercise that can be used to predict muscular fatigue. Determining the AT non-invasively helps to adjust exercise intensity and prevent overuse injuries. Near-infrared spectroscopy (NIRS) is an optical technology that can provide real-time information about muscle oxidative metabolism. The objective of this pilot study was to investigate the relationship between NIRS parameters of muscle oxygenation and traditional measures of exercise monitoring, such as heart rate and relative body oxygen consumption (VO2). Healthy adults with moderate to high fitness levels participated in an incremental exercise protocol on a stationary bicycle. NIRS parameters were compared to ventilatory VO2 using a metabolic cart. Respiratory Exchange Ratio (RER) < 1.0 was used as a proxy for determining the AT. NIRS data were collected from the primary locomotor muscle (vastus lateralis - VL) and a control muscle (deltoid) using two wearable NIRS sensors. Heart rate data were collected by a wearable ECG sensor. The NIRS data showed a significant decline in VL muscle oxygenated hemoglobin (O2Hb) concentration (p<0.05) at one exercise stage after the AT was identified. Muscle O2Hb did not show a significant decrease in the deltoid at the AT. Furthermore, there were no noticeable changes in heart rate at the AT. Our results indicate that a wearable NIRS sensor can predict the AT in exercising muscles and may provide a localized measure of muscular fatigue during exercise.

Background: Free tissue transfer (FTT) is a surgical procedure that involves taking tissue from one area of the body and transplanting it to a surgical wound. Near-infrared spectroscopy (NIRS) has the potential to provide continuous and non-invasive monitoring of FTT hemodynamics. A novel NIRS system with a miniaturized implantable sensor was developed for FTT monitoring in head and neck surgery. The objectives of this study were to obtain post-operative NIRS measurements on a cohort of patients undergoing FTT surgery for head and neck cancer and to evaluate the patient’s and clinician’s experience with the novel NIRS monitoring method. Methods: The NIRS sensor was fixed over the FTT for 72 hours post-operatively to provide tissue oxygenation parameters, including oxygenated (O2Hb), deoxygenated (HHb), and tissue saturation index (TSI). After 72 hours, the patient and clinicians completed a questionnaire to evaluate their experience with the NIRS system. All patients undergoing FTT surgery had a successful operation with no complications to the FTT. Results: The NIRS data showed visible pulsatile O2Hb signals, indicating the proper microvascular function of the FTT. Furthermore, TSI calculations provided an estimated measure of the oxygenation status of the FTT. The questionnaire indicated that the NIRS sensor did not cause additional discomfort or inconvenience to the patients or clinicians. Conclusions: Our results suggest that the novel NIRS sensor can monitor the FTT continuously and non-invasively for 72 hours with minimal interference to patient care. Incorporating a novel NIRS biosensor into FTT monitoring can improve post-operative care and decrease FTT failure rates.