Space Station Human Factors Research Review. Volume 4: Inhouse Advanced Development and Research

A variety of human factors studies related to space station design are presented. Subjects include proximity operations and window design, spatial perceptual issues regarding displays, image management, workload research, spatial cognition, virtual interface, fault diagnosis in orbital refueling, and error tolerance and procedure aids

Precision medicine and artificial intelligence : a pilot study on deep learning for hypoglycemic events detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal

Precision medicine and artificial intelligence : a pilot study on deep learning for hypoglycemic events detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal

An ultra-fast digital diffuse optical spectroscopic imaging system for neoadjuvant chemotherapy monitoring

Up to 20% of breast cancer patients who undergo presurgical (neoadjuvant) chemotherapy have no response to treatment. Standard-of-care imaging modalities, including MRI, CT, mammography, and ultrasound, measure anatomical features and tumor size that reveal response only after months of treatment. Recently, non-invasive, near-infrared optical markers have shown promise in indicating the efficacy of treatment at the outset of the chemotherapy treatment. For example, frequency domain Diffuse Optical Spectroscopic Imaging (DOSI) can be used to characterize the optical scattering and absorption properties of thick tissue, including breast tumors. These parameters can then be used to calculate tissue concentrations of chromophores, including oxyhemoglobin, deoxyhemoglobin, water, and lipids. Tumors differ in hemoglobin concentration, as compared with healthy background tissue, and changes in hemoglobin concentration during neoadjuvant chemotherapy have been shown to correlate with efficacy of treatment. Using DOSI early in treatment to measure chromophore concentrations may be a powerful tool for guiding neoadjuvant chemotherapy treatment. Previous frequency-domain DOSI systems have been limited by large device footprints, complex electronics, high costs, and slow acquisition speeds, all of which complicate access to patients in the clinical setting. In this work a new digital DOSI (dDOSI) system has been developed, which is relatively inexpensive and compact, allowing for use at the bedside, while providing unprecedented measurement speeds. The system builds on, and significantly advances, previous dDOSI setups developed by our group and, for the first time, utilizes hardware-integrated custom board-level direct digital synthesizers (DDS) and analog to digital converters (ADC) to generate and directly measure signals utilizing undersampling techniques. The dDOSI system takes high-speed optical measurements by utilizing wavelength multiplexing while sweeping through hundreds of modulation frequencies in tens of milliseconds. The new dDOSI system is fast, inexpensive, and compact without compromising accuracy and precision

New intelligent network approach for monitoring physiological parameters : the case of Benin

Benin health system is facing many challenges as: (i) affordable high-quality health care to a growing population providing need, (ii) patients’ hospitalization time reduction, (iii) and presence time of the nursing staff optimization. Such challenges can be solved by remote monitoring of patients. To achieve this, five steps were followed. 1) Identification of the Wireless Body Area Network (WBAN) systems’ characteristics and the patient physiological parameters’ monitoring. 2) The national Integrated Patient Monitoring Network (RIMP) architecture modeling in a cloud of Technocenters. 3) Cross-analysis between the characteristics and the functional requirements identified. 4) Each Technocenter’s functionality simulation through: a) the design approach choice inspired by the life cycle of V systems; b) functional modeling through SysML Language; c) the communication technology and different architectures of sensor networks choice studying. 5) An estimate of the material resources of the national RIMP according to physiological parameters. A National Integrated Network for Patient Monitoring (RNIMP) remotely, ambulatory or not, was designed for Beninese health system. The implementation of the RNIMP will contribute to improve patients’ care in Benin. The proposed network is supported by a repository that can be used for its implementation, monitoring and evaluation. It is a table of 36 characteristic elements each of which must satisfy 5 requirements relating to: medical application, design factors, safety, performance indicators and materiovigilance

Investigations of Cerebral Hemodynamics in Infants with Critical Congenital Heart Disease Using Diffuse Optics

Congenital heart defects (CHD) are the most common type of birth defect, affecting approximately 30,000 children each year, one third of whom require cardiac surgery in their first year of life. Surgical advances have improved the cardiac outcomes for these children, and since the majority of these patients now reach school age, the research focus has shifted to address neurodevelopmental difficulties of survivors. A key physiological factor appears to be the high prevalence of hypoxic-ischemic white mater brain injury observed in these children. The exact timing of the injury occurrence, however, is difficult to ascertain due to limitations of the imaging modalities employed for this fragile, infant population. This thesis develops and explores the use of diffuse optical spectroscopy techniques for investigation of the risk factors for hypoxic-ischemic brain injury in these infants. The optical techniques utilize near-infrared (NIR) light and the diffusion approximation to model light transport in order to probe the static and dynamic properties of tissue. Frequency-domain diffuse optical spectroscopy (FD-DOS) is a technology, similar to widely used near-infrared spectroscopy (NIRS), that permits quantification of tissue oxygen saturation and total hemoglobin concentration. Diffuse correlation spectroscopy (DCS) is a relatively newer technique, centered on an idea similar to dynamic light scattering, which enables quantification of blood flow. Both FD-DOS and DCS are used in this research. The experiments presented in this thesis explore a variety of biophysics and biomedical questions. Arguably, the most important clinical findings to emerge from this dissertation are new risk factors associated with brain injury in infants with a certain form of CHD called hypoplastic left heart syndrome (HLHS). Using the aforementioned optical techniques, we found that longer time-to-surgery, lower cerebral oxygen saturation, and higher cerebral blood flow measured on the morning of surgery were associated with the risk of acquiring post-operative brain injury in this cohort. The results are novel for the community and shift our understanding of when these neonates are most at risk for acquiring brain injury. Most importantly, these results and the technology developed should improve current clinical care of this patient population

Cerebral Hemodynamics in High-Risk Neonates Probed by Diffuse Optical Spectroscopies

Advances in medical and surgical care of the critically ill neonates have decreasedmortality, yet a significant number of these neonates suffer from neurodevelopmentaldelays and failure in school. Thus, clinicians are now focusing on prevention ofneurologic injury and improvement of neurocognitive outcome in these high-risk infants. Assessment of cerebral oxygenation, cerebral blood volume, and the regulation of cerebral blood flow (CBF) during the neonatal period is vital for evaluating brain health. Traditional CBF imaging methods fail, however, for both ethical and logistical reasons. In this dissertation, I demonstrate the use of non-invasive optical modalities, i.e., diffuse optical spectroscopy and diffuse correlation spectroscopy, to study cerebral oxygenation and cerebral blood flow in the critically ill neonatal population. The optical techniques utilize near-infrared (NIR) light to probe the static and dynamic physiological properties of deep tissues. Diffuse correlation spectroscopy (DCS) employs the transport of temporal correlation functions of diffusing light to extract relative changes in blood flow in biological tissues. Diffuse optical spectroscopy (DOS) employs the wavelength-dependent attenuation of NIR light to assess the concentrations of the primary chromophores in the tissue, namely oxy- and deoxy-hemoglobin. This dissertation presents both validation and clinical applications of novel diffuse optical spectroscopies in two specific critically ill neonatal populations: very-low birth weight preterm infants,and infants born with complex congenital heart defects. For validation of DCS in neonates, the blood flow index quantified by DCS is shown to correlate well with velocity measurements in the middle cerebral artery acquired by transcranial Doppler ultrasound. In patients with congenital heart defects DCS-measured relative changes in CBF due to hypercapnia agree strongly with relative changes in blood flow in the jugular veins as measured by phase-encoded velocity mapping magnetic resonance. For applications in the clinic, CO2 reactivity in patients with congenital heart defects prior to various stages of reconstructive surgery was quantified; our initial results suggest that CO2 reactivity is not systematically related to brain injury in this population. Additionally, the cerebral effects of various interventions, such as blood transfusion and sodium bicarbonate infusion, were investigated. In preterm infants, monitoring with DCS reveals a resilience of these patients to maintain constant CBF during a small postural manipulation

Low-cost plastic optical fiber sensor embedded in mattress for sleep performance monitoring

[EN] In this study, we investigated plastic optical fiber (POF) pressure sensors embedded in mattresses to measure respiration and heart rate for sleep performance monitoring. The signal is amplified in the circuit using a two stage amplification scheme to collect weak respiration and heart rate signals while an algorithm was designed to obtain respiration and heart rate. We also propose a good reliability cutting-POF technology which can be used to improve pressure sensitivity. The experimental results indicate that the mattress can distinguish four behavioral states related to sleep (on bed, lying, moving and leaving bed) and can detect respiration and heart rate values in different positions and postures. Validation experiments on 10 participants showed that absolute error was less than one breath per minute and two beats per minute, making our approach suitable for household sleeping monitoring.National Natural Science Foundation of China (62003046) ; National Defense Basic Scientific Research Program of China (JCKY2018110B011) ; The Spanish Ministerio de Ciencia, Innovacion y Universidades RTI2018-101658-B-I00 FOCAL Project; Guangdong Recruitment Program of Foreign Experts (2020A1414010393) ; Guangdong Basic and Applied Basic Research Foundation (2021A1515011997) ; C. Marques acknowledges Fundacao para a Ciencia e a Tecnologia (FCT) through the CEECIND/00034/2018 (iFish project) and this work was developed within the scope of the project i3N, UIDB/50025/2020 &UIDP/50025/2020, financed by national funds through the FCT/MEC.Han, P.; Li, L.; Zhang, H.; Guan, L.; Marques, C.; Savovic, S.; Ortega Tamarit, B.... (2021). Low-cost plastic optical fiber sensor embedded in mattress for sleep performance monitoring. Optical Fiber Technology. 64:1-8. https://doi.org/10.1016/j.yofte.2021.102541186