A filamentary soft robotic probe for multimodal in utero monitoring of fetal health.

*Department of Anesthesia, Children’s Hospital, Harvard Medical School, Boston, MA,**Department of Anesthesiology and Critical Care, The Children’s Hospital of Philadelphia,University of Pennsylvania School of Medicine, Philadelphia and †Department of Anesthesia andCritical Care, The Hospital of the University of Pennsylvania, University of Pennsylvania Schoolof Medicine, Philadelphia, PA, USA

The potential benefits of fetal cardiac intervention (FCI) have been realized for many years. In 1975, Eibschitz et al1 reported intrapartum treatment of fetal ventricular tachycardia by administering propranolol to the mother, and as early as 1986, in utero pacing was attempted for complete heart block in a human fetus.2 Recently, however, interest in FCI has accelerated.3–18 As with other fetal interventions,19,20 FCI can only become a highly useful clinical tool if it is applied to conditions in which a feasible mode of therapy is available and either the fetus is at risk for demise as a result of the condition or intervention may alter the evolution of the condition such that the severity of the postnatal disease is substantially reduced (Table 1). For conditions in which the fetus is at high risk for prenatal or neonatal death, the rationale for FCI is obvious, to improve survival. If death is not imminent but the disease is likely to have major lifelong morbidity, the rationale is that FCI will modify the course of cardiac growth, function, and/or development in utero sufficiently to alter postnatal outcome and justify the potential risks of the procedure. Prenatal intervention may also allow the fetus to recover in the supportive in utero environment, during a developmental period when there is enhanced wound healing and the capacity for myocyte proliferation.21,22 View this table: Table 1. Congenital Cardiovascular Anomalies Potentially Amenable to FCI This construct rightfully emphasizes death or significant morbidity as therapeutic targets. FCI can entail substantial short-term risk to the fetus, uncertain long-term risk to the fetus and child, and at least some risk to the mother. There are no known medical benefits to the mother. With that risk profile, FCI will not be embraced by the maternal-fetal medicine and cardiology communities unless it …

Real time monitoring of physiological parameters is very important to safeguard Athlete’s life time from severe life-threatening diseases and injuries during training and competitions. Now a day, sensors play a pivotal role in sports for online monitoring of physiological and movement parameters. To improve the performance of athletes, continuous monitoring of physiological parameters and providing feedback are more important. This study mainly concentrates on javelin throw, which is one of the track and field events. Due to poor training and lack of best coaches, javelin athletes do not shine in the Olympics. Javelin athletes have to balance both physiological and movement parameters to achieve maximum distance while throwing the javelin. We design a hardware using sensors and Arduino controller to monitor physiological parameters such as blood pressure, heart rate and electrocardiogram. Using SQL database and internet of things the measured parameters are stored in web server for further analysis and providing feedback to athletes. The aim of this study is to bridge the gap between Engineering and sports technology and provide a collaborative platform for the sharing of knowledge, so that both Coaches and athletes can get the benefited.

Monitoring and telemedicine support in remote environments and in human space flight

consent process that accompanies these procedures. Maternal–fetal surgery when properly performed by trained individuals in well-structured centers typically proceeds without the mother requiring admission to an intensive care unit. Nevertheless, familiarity with critical care considerations for the obstetric patient is helpful. Even in the best centers, significant maternal complications may arise at subsequent pregnancies, especially following open fetal surgery. On the other hand, the fetus is at risk for procedurerelated complications, preterm delivery, and the morbidity associated with the underlying anomaly. These and other factors should be discussed in a nondirected manner during the informed consent process. This is an area in which the intensivist should actively participate. Newborns who have undergone fetal surgery have had the natural history of their anomalies altered. The physiologic consequences of these alterations may or may not be predictable, challenges for which the neonatologist should be prepared. Fetuses that undergo procedures, especially shortly before birth, may manifest physiologic changes not typical of the average newborn. For example, drainage of large intrathoracic, cervical, or sacrococcygeal cystic lesions just before delivery may result in significant fluid shifts that need to be accounted for during the early newborn period. Expanding fetal surgical indications and a wide variety of interventions present new challenges for the neonatologist and other practitioners in the intensive care setting. A larger number of centers perform percutaneous procedures in utero. Although the vast majority of these are diagnostic and do not typically affect the well-being of the mother or fetus, increasing numbers of percutaneous therapeutic procedures are also being performed at many centers. Fetoscopic procedures require a higher skill set and special The intrigue and mystique of fetal surgery have moved from the realm of science fiction to medical reality. Since the initial attempts at fetal surgery in the 1960s, extensive preclinical studies coupled with advances in imaging technology and surgical instrumentation have resulted in a rapidly growing field. No longer is the womb a barrier to addressing some anomalies that plague newborn infants. Initially developed by perinatologists using needle-based interventions, fetal surgery has expanded to involve fetal/pediatric surgeons performing operations through a partially opened uterus. Minimal access surgery has also found its way into the fetal realm with fetoscopic interventions, which permit endoscopic visualization of the fetus and placenta. With markedly improved optics in recent years, fetoscopy has undergone a resurgence, especially for placenta-based procedures. However, limitations in instrumentation haverestricted its use for correction of structural anomalies (at least for now). Fetal surgical procedures affect the mother and fetus. The mother is typically an innocent bystander who assumes a significant amount of risk with minimal or no direct medical benefit. Many mothers would be willing to do whatever they can for the benefit of their fetus or baby, even putting themselves at undue risk. Understanding the expected benefit of the fetal intervention and the possible risks to the mother is therefore a critical part of the informed

To lower the incidence and severity of fetal cardiovascular depression during maternal fetal surgery under general anesthesia. We hypothesized that supplemental intravenous anesthesia (SIVA) with propofol and remifentanil would lower the need for high-dose inhalational anesthesia and provide adequate maternal depth of anesthesia and uterine relaxation. SIVA technique would minimize prolonged fetal exposure to deep inhalational anesthetics and significant intraoperative fetal cardiovascular depression. Fetal hypoxia and significant fetal hemodynamic changes occur during open fetal surgery because of the challenges such as surgical manipulation, hysterotomy, uterine contractions, and effects of anesthetic drugs. Tocolysis, a vital component of fetal surgery, is usually achieved using volatile anesthetic agents. High concentrations of volatile agents required to provide an appropriate degree of uterine relaxation may cause maternal hypotension and placental hypoperfusion, as well as direct fetal cardiovascular depression. We reviewed medical records of 39 patients who presented for ex utero intrapartum treatment and mid-gestation open fetal surgery between April 2004 and March 2009. Out of 39 patients, three were excluded because of the lack of echocardiographic data; 18 patients received high-concentration desflurane anesthesia and 18 patients had SIVA with desflurane for uterine relaxation. We analyzed the following data: demographics, fetal medical condition, anesthetic drugs, concentration and duration of desflurane, maternal arterial blood pressure, intraoperative fetal echocardiogram, presence of fetal bradycardia, and need for intraoperative fetal resuscitation. Adequate uterine relaxation was achieved with about 1.5 MAC of desflurane in the SIVA group compared to about 2.5 MAC in the desflurane only anesthesia group (P = 0.0001). More fetuses in the high-dose desflurane group compared to the SIVA group developed moderate-severe left ventricular systolic dysfunction over time intraoperatively (P = 0.02). 61% of fetuses in the high-dose desflurane group received fetal resuscitative interventions compared to 26% of fetuses in the SIVA group (P = 0.0489). SIVA as described provides adequate maternal anesthesia and uterine relaxation, and it allows for decreased use of desflurane during open fetal surgery. Decreased use of desflurane may better preserve fetal cardiac function.

This review explores the relationships between physiological parameters and emotions, as well as the potential value and applications of the use of machine learning to facilitate emotion recognition. First, the relationships between physiological parameters (such as heart rate, respiration, blood pressure, galvanic skin response, electroencephalography, and heart rate variability [HRV]) and emotions are discussed. The impacts of emotional states on these physiological parameters represent a crucial aspect of emotion research. For example, the increased heart rates and faster breathing resulting from excitement or anxiety are physiological changes that cannot be ignored. Subsequently, models used for emotion recognition are introduced. These models employ techniques such as machine learning or deep learning and are trained to detect emotional states on the basis of changes in physiological parameters. These techniques have important applications in clinical psychology, including by helping doctors assess patients' status, diagnose emotional disorders, and guide treatment. In the context of managing emotional disorders such as depression, anxiety, bipolar disorder, and borderline personality disorder, emotion recognition technologies can facilitate accurate emotional monitoring and early intervention, thereby reducing the risk of disease recurrence. These models can be used in the contexts of emotion management and health monitoring, thus helping individuals understand and cope with emotional changes more effectively and improving their quality of life. This paper identifies HRV, which reflects an individual's ability to adapt to stress, emotions, and physical conditions, as a key indicator that can be used in the contexts of emotion recognition and physiological parameter analysis. By incorporating HRV parameters into relevant models, emotional changes can be analyzed more precisely, thereby providing more effective emotion management and health monitoring tools, which can enhance individuals' quality of life. However, the use of these physiological parameters entails many challenges, including those pertaining to the collection of physiological data, privacy and security concerns, and the need for personalized adjustments as a result of the variability observed among individuals in this context. These challenges require continuous efforts on the part of technical experts and researchers to advance the development and application of emotion recognition technologies. Finally, this paper presents an in-depth investigation of the associations between physiological parameters and emotions, and it explores the potential value and challenges associated with the use of machine learning to facilitate emotion recognition. The results of these studies suggest that emotion recognition technology can be used more widely in the contexts of mental health, emotional management, and health monitoring to provide individuals with better emotional support and care.

With the continuous development of science and technology, flexible wearable electronic products are flourishing in many fields, especially in the areas of health monitoring and medical improvement. In the realm of biomechanics, the human body is a complex mechanical system, and monitoring physiological parameters like body temperature has a unique connection to biomechanical research. Body temperature, as one of the most important physiological parameters of the human body, is not only important for health monitoring but also has implications in understanding the body’s mechanical-thermal balance. Biomechanics studies how forces and mechanical stress affect the body’s functions, and temperature can influence the mechanical properties of biological tissues. Researchers have extensively studied the various properties of wearable flexible temperature sensors, such as high precision, good biocompatibility, flexibility, agility, light weight, and high sensitivity, continuously improving real-time and sensitive detection of temperature in various parts of the human body. This article reviews the research progress of high-sensitivity flexible temperature sensors for monitoring body temperature changes. Firstly, the commonly used active materials for flexible temperature sensors were summarized. Secondly, the imaging manufacturing method and process of flexible temperature sensors were introduced. Then, the performance of flexible temperature sensing was comprehensively discussed, including temperature measurement range, sensitivity, response time, and temperature resolution. Additionally, the article explores the potential of flexible sensors in biomechanical applications, such as monitoring joint angles, muscle activation patterns, and pressure distribution during movement. Finally, the challenges faced by flexible temperature sensors in the future were summarized and discussed. By combining temperature sensing with biomechanical data collection, this study highlights the potential of flexible wearable technologies to revolutionize health monitoring and motion analysis.

27 Background: Exosomal RNAs mediate cellular communication, reflect dynamic physiological and pathological changes. Unlike tissue biopsies, which may introduce confounding variables, exosomal RNA provides real-time insights into tumor activity. Standard GI cancer surveillance—using CEA, CA19-9, imaging, and endoscopy—has limitations: CEA may remain normal during relapse, CA19-9 can be elevated in benign conditions, and CT imaging sensitivity for peritoneal metastases is low (28.3%). CTOAM’s Liquid RNA (L-RNA) assay capitalizes on tumor-derived exosomal RNA. Unlike relatively static DNA, RNA expression dynamically reflects cellular and functional changes, providing real-time biological insights. Methods: A retrospective analysis was conducted on 21 patients using CTOAM’s L-RNA assay, which qualifies and quantifies exosomal RNA in blood via Genestudio S5 Prime with Ampliseq RNA NGS. Its proprietary method quantifies exosomal RNA expression in blood, enabling clear separation of interpatient variability in normal tissue from tumor-related variability. Results: Of 21 patients, 12 had results correlating with GI carcinoma (Colorectal-6, Pancreatic-4, Cholangiocarcinoma-2), 1 was inconclusive, and 8 were true negatives. The L-RNA assay demonstrated: Sensitivity: 100% (95% CI: 75.8–100); Accuracy: 87% (95% CI: 67.9–95.5); Precision (PPV): 80% (95% CI: 54.8–93); AUC: 86.4 (95% CI: 56.8–95.1). Tumor cell activity correlated with CPS values ranging from 367 (low) to 5,290 (high). Importantly, disease progression was detected 1–10 weeks earlier than with standard imaging (median lead time gain: 5 weeks). Conclusions: CTOAM’s L-RNA biopsy serves as a complement to biopsy or imaging and tissue/blood analyses. By monitoring disease progression and providing earlier prognostic insights, it may significantly improve clinical decision-making in GI cancers. CTOAM’s blood-based exosomal L-RNA analysis provides a non-invasive, earlier signal for tumor cell activity and relapse risk, often weeks ahead of conventional imaging. Further validation in larger cohorts is warranted. L-RNA data. Metric L-RNA vs Biopsy+Imaging+Blood (%) 95% CI L-RNA vs Blood biomarkers (%) 95% CI Sensitivity 100 (75.8-100) 100 (70.1-100) Specificity 72.7 (43.4-90.3) 72.7 (43.4-90.3) PPV (Precision) 80 (54.8-93) 75 (46.8-91.1) NPV 100 (67.6-100) 100 (67.6-100) Accuracy 87 (67.9-95.5) 85 (64-94.8) F1 Score 88.9 (63.6-96.3) 85.7 (56.1-95.3) AUC 86.4 (56.8-95.1) 86.4 (56.8-95.1)

Continuous Physiological parameter monitoring is essential for elderly and ill patients. There is a need for a Web-based Patient health monitoring system, when the patient is not in the Hospital. Such a system will enable the doctors to monitor the physiological parameters online and take necessary action in emergency. In this paper, a prototype of basic physiological parameter monitoring system based on Arduino and Raspberry Pi microcontroller boards is implemented. Various basic physiological parameters such as blood pressure, heartbeat, oxygen saturation in Blood (SPO2), body temperature and fall detection are measured using relevant sensors and sent to the Arduino microcontroller board for further processing. The computed parameters are then sent to a Raspberry Pi based Web server for display on the web page. ZigBee is used for communication between Arduino and Raspberry Pi. The necessary software is developed using Arduino IDE and Python language. The measured physiological parameters are updated every 60 seconds. The updated parameter values can be viewed from anywhere using an internet enabled device. Also, when the value of the physiological parameters exceeds certain threshold, the caretaker is alerted through SMS. This system is especially helpful for elderly and ill patients.

Plant growth regulators (PGRs) and plant growth promoting rhizobacteria (PGPRs) play an important role in mitigating abiotic stresses. However, little is known about the parallel changes in physiological processes coupled with metabolic changes induced by PGRs and PGPRs that help to cope with drought stress in chickpeas. The present investigation was carried out to study the integrative effects of PGRs and PGPRs on the physiological and metabolic changes, and their association with drought tolerance in two chickpea genotypes. Inoculated seeds of two chickpea genotypes, Punjab Noor-2009 (drought sensitive) and 93127 (drought tolerance), were planted in greenhouse condition at the University of Florida. Prior to sowing, seeds of two chickpea varieties were soaked for 3 h in 24 h old cultures of PGPRs (Bacillus subtilis, Bacillus thuringiensis, and Bacillus megaterium), whereas, some of the seeds were soaked in distilled water for the same period of time and were treated as control. Plant growth regulators, salicylic acid (SA) and putrescine (Put), were applied on 25 days old seedlings just prior to the induction of drought stress. Drought stress was imposed by withholding the supply of water on 25-day-old seedlings (at the three-leaf stage) and continued for the next 25 days until the soil water content reached 14%. Ultrahigh-performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) analysis concomitant with physiological parameters were carried out in chickpea leaves at two-time points i.e. 14 and 25 d after imposition of drought stress. The results showed that both genotypes, treated with PGRs and PGPRs (consortium), performed significantly better under drought condition through enhanced leaf relative water content (RWC), greater biomass of shoot and root, higher Fv/FM ratio and higher accumulation of protein, sugar and phenolic compounds. The sensitive genotype was more responsive than tolerant one. The results revealed that the accumulation of succinate, leucine, disaccharide, saccharic acid and glyceric acid was consistently higher in both genotypes at both time points due to PGRs and PGPRs treatment. Significant accumulation of malonate, 5-oxo-L-proline, and trans-cinnamate occurred at both time points only in the tolerant genotype following the consortium treatment. Aminoacyl-tRNA, primary and secondary metabolite biosynthesis, amino acid metabolism or synthesis pathways, and energy cycle were significantly altered due to PGRs and PGPRs treatment. It is inferred that changes in different physiological and metabolic parameters induced by PGRs and PGPRs treatment could confer drought tolerance in chickpeas.

In our response to, "Parental request for non-resuscitation in fetal myelomeningocele repair: an analysis of the novel ethical tensions in fetal intervention" by Wolfe and co-authors, we argue that parental authority should guide resuscitation decision-making for a fetus at risk for preterm delivery as a complication of fetal myelomeningocele (fMMC) repair. Due to the elevated morbidity and mortality risks of combined myelomeningocele, extreme prematurity, and fetal hypoxia, parents' values regarding the acceptability of possible outcomes should be elicited and their preferences honored. Ethical decision-making in these situations must also consider the broader context of the fetal-maternal dyad. Innovations in fetoscopic approaches to fMMC repair may pose additional complexity to these resuscitation decisions.

ABSTRACTWith the increasing prevalence of smartphones and advancements in sensors, smartphone‐based solutions for physiological parameter monitoring appear to offer notable advantages over traditional methods, potentially enhancing safety, convenience and efficiency. This paper aims to present a systematic survey of smartphone sensor‐based physiological parameter monitoring apps, with particular discussions of gaps between their current functional capabilities and recent advances. We conducted a systematic analysis of relevant apps available on the App Store and Google Play, mainly focusing on four vital signs: heart rate (HR), blood pressure(BP), body temperature (BT) and respiratory rate (RR), as well as oxygen saturation (), blood glucose (BG) and haemoglobin (Hb). The analysis revealed that HR measurement apps were the most prevalent, while BP, , BT and RR measurement apps were comparatively fewer, and no smartphone sensor‐based BG measurement apps were identified. The contact photoplethysmography method is widely adopted by current apps, while non‐contact approach holds potential. Novel techniques require further investigation beyond laboratory settings to enhance robustness. Smartphone‐based measurement of physiological parameters shows promise, though further research and development are needed to bridge the gap between current capabilities and the demands of accurate, real‐world health monitoring.

ABSTRACTIntroduction:Preterm birth, delivery before 37 weeks of gestation, represents a critical global health challenge. With approximately 15 million premature births annually, these infants are predisposed to various health complications, significantly impacting under-five mortality rates. This study aims to evaluate the effectiveness of Kangaroo Mother Care (KMC) in improving physiological parameters and maternal experiences in neonatal intensive care units (NICU).Objectives:Determine the impact of kangaroo mother care on the physiological parameters among preterm neonate babies admitted in NICU and explore the health experience of primigravida mothers on Kangaroo Mother Care.Methods and Materials:This study employed an Explanatory Sequential mixed-method approach, with a quasi-experimental one-group pre-test post-test design, focusing on 60 preterm infants at the Institute of Child Health and Hospital for Children, Chennai. Initial physiological parameters such as heart rate, respiratory rate, oxygen saturation, body temperature, weight, and sleep were documented. Following the KMC intervention, these parameters were reassessed. The qualitative phase explored the emotional and psychological impacts on six primigravida mothers using KMC through unstructured interviews and thematic content analysis. Data tools were validated for accuracy and reliability, and ethical considerations were meticulously observed, including informed consent from all participants.Results:Post-KMC, significant enhancements in physiological parameters were noted: 70% of infants showed improved heart rate stability, respiratory rates normalized in 33.33% of the cases, and 25% reached optimal oxygen saturation levels. Furthermore, 70% of neonates achieved normal weight gain standards. Qualitative analysis revealed themes and subthemes such as ’Improvements in Mental Health’ (Enhanced Confidence, Increased Happiness), ’Knowledge’ (Training, Realization, Sharing), ’Support’ (Hospital care, Family support), ’Bonding’ (Altruistic Actions, Identifying with Others), and ’Physiological Changes’ (Enhanced Immunity, Heartbeat Regulation, Improvement in Sucking, Weight Management). These themes were pivotal in understanding the comprehensive benefits of KMC. Additionally, there was a notable association between the infants’ physiological improvements and maternal sociodemographic factors, with a marked correlation in outcomes among mothers under 20 years old and those employed in unskilled or semi-professional roles.Conclusion:Kangaroo Mother Care significantly enhances the physiological parameters of preterm neonates while providing substantial psychosocial benefits to mothers. The findings advocate for the integration of KMC into standard neonatal care, particularly in resource-limited settings, to mitigate the complications associated with preterm births.

Telemedicine, as a new technical means and medical model, can truly realize the sharing and monitoring of telemedicine information, and ultimately ensure that everyone has equal access to medical and health resources. Based on the research on the status of telemedicine application and wireless communication technology, this paper proposes a multi-physical parameter wireless telemedicine health monitoring system solution, and analyzes the overall structure and functional requirements of the system. Human physiological parameters of the wireless remote medical system for health monitoring include body temperature, respiration, blood oxygen saturation, pulse, blood pressure, and electrocardiogram. In this paper, fabric electrodes are used to extract human bioimpedance signals, discrete Fourier transform algorithm is used to detect human respiratory signals, and respiratory rate is detected based on dynamic differential threshold peak detection technology. The reflection type photoelectric sensor is used to realize the reflection of the human pulse signal, and the continuous measurement of the cuff-free blood pressure based on the pulse wave conduction time is combined with the ECG (Electrocardiogram) data. A self-learning threshold algorithm based on near-infrared photo plethysmo graphy signal trough detection is designed on the reflective blood oxygen saturation calculation algorithm. The difference threshold method is used to extract the QRS band feature points. We tested the overall operation of the system. The results show that the collected human physiological signal data is accurate. After a series of tests, the validity and reliability of the collected physiological signals have been proven.