An Efficient Emergency Patient Monitoring based on Mobile Ad Hoc Networks

Medical sensors are implanted within the vital organs of human body to record and monitor the vital signs of pulse rate, heartbeat, electrocardiogram, body mass index, temperature, blood pressure, etc. to ensure their effective functioning. These are monitored to detect patient’s health from anywhere and at any time. The Wireless Sensor Networks are embedded in the form of Body Area Nets and are capable of sensing and storing the information on a digital device. Later this information could be inspected or even sent to a remotely located storage device specifically (server or any public or private cloud for analysis) so that a medical doctor can diagnose the present medical condition of a person or a patient. Such a facility would be of immense help in the event of an emergency such as a sudden disaster or natural calamity where communication is damaged, and the potential sources become inaccessible. The aim of this paper is to create a mobile platform using Mobile Ad hoc Network to support healthcare connectivity and treatment in emergency situations.

Feasibility of Chest Wall and Diaphragm Proprioceptive Neuromuscular Facilitation (PNF) Techniques in Mechanically Ventilated Patients

Physical therapy is part of the treatment for patients admitted to ICU. Proprioceptive neuromuscular facilitation (PNF) is one of the physiotherapy concepts including manual techniques and verbal stimulation. The purpose of this paper is to examine the feasibility of PNF techniques in mechanically ventilated (MV) ICU patients. Another aim is to verify whether the technique using resistance during the patient’s inhalation will have a different effect than the technique used to teaching the correct breathing patterns. Methods: Patients admitted to tertiary ICU were enrolled in this study, randomly divided into two groups, and received four 90-second manual breathing stimulations each. The following vital signs were assessed: HR, SBP, DBP, and SpO2. Results: 61 MV ICU adult patients (mean age 67.8; 25 female and 36 male) were enrolled in this study. No significant differences in HR, SBP, and DBP were observed both for two techniques measured separately and between them. Statistically significant differences were noticed analysing SpO2 in the rhythmic initiation technique (RIT) group (p-value = 0.013). Conclusions: Short-term PNF interventions did not influence clinically relevant vital parameters among MV patients and seem to be feasible in this group of ICU patients.

Contactless Measurement of Vital Signs Using Thermal and RGB Cameras: A Study of COVID 19-Related Health Monitoring

In this study, a contactless vital signs monitoring system was proposed, which can measure body temperature (BT), heart rate (HR) and respiration rate (RR) for people with and without face masks using a thermal and an RGB camera. The convolution neural network (CNN) based face detector was applied and three regions of interest (ROIs) were located based on facial landmarks for vital sign estimation. Ten healthy subjects from a variety of ethnic backgrounds with skin colors from pale white to darker brown participated in several different experiments. The absolute error (AE) between the estimated HR using the proposed method and the reference HR from all experiments is 2.70±2.28 beats/min (mean ± std), and the AE between the estimated RR and the reference RR from all experiments is 1.47±1.33 breaths/min (mean ± std) at a distance of 0.6–1.2 m.

Shoreline change at Fort Matanzas National Monument: 2020–2021 data summary

In 2020 and 2021 the Southeast Coast Network (SECN) collected shoreline data at Fort Matanzas National Monument as a part of the NPS Vital Signs Monitoring Program. Monitoring was conducted following methods developed by the National Park Service Northeast Barrier Coast Network and consisted of mapping the high tide swash line using a global positioning system (GPS) unit in the spring of each year (Psuty et al. 2010). Shoreline change was calculated using the Digital Shoreline Analysis System (DSAS) developed by USGS (Theiler et al. 2008). Key findings from this effort: A mean of 2,255.23 meters (7,399 feet [ft]) of shoreline were mapped from 2020 to 2021 with a mean horizontal precision of 10.73 centimeters (4.2 inches [in]) at Fort Matanzas National Monument from 2020 to 2021. In the annual shoreline change analysis, the mean shoreline distance change from spring 2020 to spring 2021 was -7.40 meters (-24.3 ft) with a standard deviation of 20.24 meters (66.40 ft). The shoreline change distance ranged from -124.73 to 35.59 meters (-409.1 to 116.7 ft). Two erosion areas and one accretion area were identified in the study area beyond the uncertainty of the data (± 10 meters [32.8 ft]). The annual shoreline change from 2020 to 2021 showed erosion on the east and west sides of A1A where the Matanzas Inlet is located. Overall, the most dynamic area of shoreline change within Fort Matanzas National Monument appeared to be on the east and west side of A1A, along the Matanzas River inlet.

Non-contact physiological monitoring of post-operative patients in the intensive care unit

Prolonged non-contact camera-based monitoring in critically ill patients presents unique challenges, but may facilitate safe recovery. A study was designed to evaluate the feasibility of introducing a non-contact video camera monitoring system into an acute clinical setting. We assessed the accuracy and robustness of the video camera-derived estimates of the vital signs against the electronically-recorded reference values in both day and night environments. We demonstrated non-contact monitoring of heart rate and respiratory rate for extended periods of time in 15 post-operative patients. Across day and night, heart rate was estimated for up to 53.2% (103.0 h) of the total valid camera data with a mean absolute error (MAE) of 2.5 beats/min in comparison to two reference sensors. We obtained respiratory rate estimates for 63.1% (119.8 h) of the total valid camera data with a MAE of 2.4 breaths/min against the reference value computed from the chest impedance pneumogram. Non-contact estimates detected relevant changes in the vital-sign values between routine clinical observations. Pivotal respiratory events in a post-operative patient could be identified from the analysis of video-derived respiratory information. Continuous vital-sign monitoring supported by non-contact video camera estimates could be used to track early signs of physiological deterioration during post-operative care.

MATURE TESTICULAR TERATOMA IN PEDIATRIC PATIENT: A CASE REPORT

Objective: To report our experience on management of testicular teratoma in pediatric patient. Case(s) presentation: A 2-years-old boy presented with progressive mass in his left testis. The mass was found 3 months ago but became larger in a few days. The patient had no other genitourinary complaint. Vital signs were within normal limits. A hard and tender mass in the left scrotum sized 5x4x2.5 cm was palpated from the physical examination. An imaging study with Computed Tomography (CT) Scan revealed an enhancement in the left scrotum mass area. There was no ring enhancement in pelvic and paraaortic lymph nodes. The laboratory examination within normal limit. Inguinal radical orchiectomy was performed, and histopathological examination revealed a mature testicular teratoma of the left testis. Discussion: Testicular teratoma in children is usually benign. Testicular germ cell tumors generally have a good prognosis with current therapy. Post-orchiectomy management depends on the histology type, staging, and tumor markers. Conclusion: Testicular teratoma is a rare case and can cause minimal symptoms until it grows significantly. Testicular teratoma should be considered in the differential diagnosis of non-traumatic painless progressive scrotal mass. Inguinal radical orchiectomy may be considered as the primary management.

The association between vital signs and clinical outcomes in emergency department patients of different age categories

BackgroundAppropriate interpretation of vital signs is essential for risk stratification in the emergency department (ED) but may change with advancing age. In several guidelines, risk scores such as the Systemic Inflammatory Response Syndrome (SIRS) and Quick Sequential Organ Failure Assessment (qSOFA) scores, commonly used in emergency medicine practice (as well as critical care) specify a single cut-off or threshold for each of the commonly measured vital signs. Although a single cut-off may be convenient, it is unknown whether a single cut-off for vital signs truly exists and if the association between vital signs and in-hospital mortality differs per age-category.AimsTo assess the association between initial vital signs and case-mix adjusted in-hospital mortality in different age categories.MethodsObservational multicentre cohort study using the Netherlands Emergency Department Evaluation Database (NEED) in which consecutive ED patients ≥18 years were included between 1 January 2017 and 12 January 2020. The association between vital signs and case-mix adjusted mortality were assessed in three age categories (18-65; 66-80; >80 years) using multivariable logistic regression. Vital signs were each divided into five to six categories, for example, systolic blood pressure (SBP) categories (≤80, 81–100, 101–120, 121–140, >140 mm Hg).ResultsWe included 101 416 patients of whom 2374 (2.3%) died. Adjusted ORs for mortality increased gradually with decreasing SBP and decreasing peripheral oxygen saturation (SpO2). Diastolic blood pressure (DBP), mean arterial pressure (MAP) and heart rate (HR) had quasi-U-shaped associations with mortality. Mortality did not increase for temperatures anywhere in the range between 35.5°C and 42.0°C, with a single cut-off around 35.5°C below which mortality increased. Single cut-offs were also found for MAP <70 mm Hg and respiratory rate >22/min. For all vital signs, older patients had larger increases in absolute mortality compared with younger patients.ConclusionFor SBP, DBP, SpO2 and HR, no single cut-off existed. The impact of changing vital sign categories on prognosis was larger in older patients. Our results have implications for the interpretation of vital signs in existing risk stratification tools and acute care guidelines.

Continuous Monitoring of Vital Signs With Wearable Sensors During Daily Life Activities: Validation Study

Background Continuous telemonitoring of vital signs in a clinical or home setting may lead to improved knowledge of patients’ baseline vital signs and earlier detection of patient deterioration, and it may also facilitate the migration of care toward home. Little is known about the performance of available wearable sensors, especially during daily life activities, although accurate technology is critical for clinical decision-making. Objective The aim of this study is to assess the data availability, accuracy, and concurrent validity of vital sign data measured with wearable sensors in volunteers during various daily life activities in a simulated free-living environment. Methods Volunteers were equipped with 4 wearable sensors (Everion placed on the left and right arms, VitalPatch, and Fitbit Charge 3) and 2 reference devices (Oxycon Mobile and iButton) to obtain continuous measurements of heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2), and temperature. Participants performed standardized activities, including resting, walking, metronome breathing, chores, stationary cycling, and recovery afterward. Data availability was measured as the percentage of missing data. Accuracy was evaluated by the median absolute percentage error (MAPE) and concurrent validity using the Bland-Altman plot with mean difference and 95% limits of agreement (LoA). Results A total of 20 volunteers (median age 64 years, range 20-74 years) were included. Data availability was high for all vital signs measured by VitalPatch and for HR and temperature measured by Everion. Data availability for HR was the lowest for Fitbit (4807/13,680, 35.14% missing data points). For SpO2 measured by Everion, median percentages of missing data of up to 100% were noted. The overall accuracy of HR was high for all wearable sensors, except during walking. For RR, an overall MAPE of 8.6% was noted for VitalPatch and that of 18.9% for Everion, with a higher MAPE noted during physical activity (up to 27.1%) for both sensors. The accuracy of temperature was high for VitalPatch (MAPE up to 1.7%), and it decreased for Everion (MAPE from 6.3% to 9%). Bland-Altman analyses showed small mean differences of VitalPatch for HR (0.1 beats/min [bpm]), RR (−0.1 breaths/min), and temperature (0.5 °C). Everion and Fitbit underestimated HR up to 5.3 (LoA of −39.0 to 28.3) bpm and 11.4 (LoA of −53.8 to 30.9) bpm, respectively. Everion had a small mean difference with large LoA (−10.8 to 10.4 breaths/min) for RR, underestimated SpO2 (>1%), and overestimated temperature up to 2.9 °C. Conclusions Data availability, accuracy, and concurrent validity of the studied wearable sensors varied and differed according to activity. In this study, the accuracy of all sensors decreased with physical activity. Of the tested sensors, VitalPatch was found to be the most accurate and valid for vital signs monitoring.

Home Telemonitoring of Patients With Type 2 Diabetes: A Meta-Analysis and Systematic Review

Telehealth has emerged as an evolving care management strategy that is playing an increasingly vital role, particularly with the onset of the coronavirus disease 2019 pandemic. A meta-analysis of 20 randomized controlled trials was conducted to test the effectiveness of home telemonitoring (HTM) in patients with type 2 diabetes in reducing A1C, blood pressure, and BMI over a median 180-day study duration. HTM was associated with a significant reduction in A1C by 0.42% (P = 0.0084). Although we found statistically significant changes in both systolic and diastolic blood pressure (−0.10 mmHg [P = 0.0041], and −0.07 mmHg [P = 0.044], respectively), we regard this as clinically nonsignificant in the context of HTM. Comparisons across different methods of transmitting vital signs suggest that patients logging into systems with moderate interaction with the technology platform had significantly higher reductions in A1C than those using fully automatic transmission methods or fully manual uploading methods. A1C did not vary significantly by study duration (from 84 days to 5 years). HTM has the potential to provide patients and their providers with timely, up-to-date information while simultaneously improving A1C.