scholarly journals Wearable Sensors for Monitoring Vital Signs of Patients

2018 ◽  
Vol 7 (2.11) ◽  
pp. 62 ◽  
Author(s):  
Parminder Kaur ◽  
Hardeep Singh Saini ◽  
Bikrampal Kaur
Keyword(s):  
Pressure Pulse ◽  
Medical Condition ◽  
Wearable Sensors ◽  
Vital Signs ◽  
Blood Oxygen ◽  
New Disease ◽  
State Of Health ◽  
Blood Oxygen Saturation ◽  
Normal Ranges ◽  
Vital Parameters

Vital signs of a person are the indicator of basic bodily functions and provide critical information for accessing a patient's state of health. The four Vital signs are: Blood Pressure, Pulse Rate, Body temperature and Respiration Rate. In some cases, blood oxygen saturation is also measured. Vital signs help in identifying an already existing medical condition, diagnosing new disease and can also be very helpful in providing critical care to patients in time of emergency. Traditional ways of Vital sign monitoring are being replaced by more technical methods employing the use of wearable sensors. Not only are wearable sensors an aid for getting vital signs accurately but a multitude of parameters can be obtained by using an assembly of wearable sensors. With the help of wearable sensors, telemonitoring of patients has become a reality. This paper discusses the Vital parameters, their normal ranges and different wearable sensors to measure these parameters.  

Pulse Oximetry and Breathing Training1

Biofeedback ◽  
2012 ◽  
Vol 40 (4) ◽  
pp. 137-141 ◽  
Author(s):  
Christopher Gilbert
Keyword(s):  
Oxygen Saturation ◽  
Pulse Oximetry ◽  
Medical Condition ◽  
Noninvasive Monitoring ◽  
Control Of Breathing ◽  
Oxygen Absorption ◽  
Blood Oxygen ◽  
Blood Oxygen Saturation ◽  
Training Control ◽  
Pulse Oximeters

Small pulse oximeters have become widely available and can be useful for noninvasive monitoring of blood oxygen saturation by nonmedical personnel. When training control of breathing, an oximeter helps to reassure clients who hyperventilate that their oxygenation is adequate, offsetting their perception that they are not getting enough air. Low saturation may indicate a medical condition that impairs oxygen absorption. In that case, hyperventilation is a biological compensation that should not be tampered with.

scholarly journals Reliability of heart rate and respiration rate measurements with a wireless accelerometer in postbariatric recovery

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0247903
Author(s):  
Fleur Jacobs ◽  
Jai Scheerhoorn ◽  
Eveline Mestrom ◽  
Jonna van der Stam ◽  
R. Arthur Bouwman ◽  
...  
Keyword(s):  
Heart Rate ◽  
Respiration Rate ◽  
Gold Standard ◽  
Continuous Monitoring ◽  
Wearable Sensors ◽  
Vital Signs ◽  
Patient Monitor ◽  
Standard Patient ◽  
Bariatric Patients ◽  
Vital Parameters

Recognition of early signs of deterioration in postoperative course could be improved by continuous monitoring of vital parameters. Wearable sensors could enable this by wireless transmission of vital signs. A novel accelerometer-based device, called Healthdot, has been designed to be worn on the skin to measure the two key vital parameters respiration rate (RespR) and heart rate (HeartR). The goal of this study is to assess the reliability of heart rate and respiration rate measured by the Healthdot in comparison to the gold standard, the bedside patient monitor, during the postoperative period in bariatric patients. Data were collected in a consecutive group of 30 patients who agreed to wear the device after their primary bariatric procedure. Directly after surgery, a Healthdot was attached on the patients’ left lower rib. Vital signs measured by the accelerometer based Healthdot were compared to vital signs collected with the gold standard patient monitor for the period that the patient stayed at the post-anesthesia care unit. Over all patients, a total of 22 hours of vital signs obtained by the Healthdot were recorded simultaneously with the bedside patient monitor data. 87.5% of the data met the pre-defined bias of 5 beats per minute for HeartR and 92.3% of the data met the pre-defined bias of 5 respirations per minute for RespR. The Healthdot can be used to accurately derive heart rate and respiration rate in postbariatric patients. Wireless continuous monitoring of key vital signs has the potential to contribute to earlier recognition of complications in postoperative patients. Future studies should focus on the ability to detect patient deterioration in low-care environments and at home after discharge from the hospital.

scholarly journals Trajectories of Key Physiological Parameters in COVID-19 Patients Using Continuous Remote Monitoring and Health AI

2020 ◽  
Author(s):  
Arik Eisenkraft ◽  
Yasmin Maor ◽  
Keren Constantini ◽  
Nir Goldstein ◽  
Dean Nachman ◽  
...  
Keyword(s):  
Remote Monitoring ◽  
Vital Signs ◽  
Blood Oxygen ◽  
Cardiorespiratory System ◽  
Blood Oxygen Saturation ◽  
Frequent Monitoring ◽  
Respiratory Parameters ◽  
Multi Center Study ◽  
First Time ◽  
Worse Prognosis

Abstract Coronavirus disease 2019 (COVID-19) exerts deleterious effects on the cardiorespiratory system, leading to worse prognosis in the most effected. The aim of this retrospective multi-center study was to describe the variability of key cardiopulmonary vitals amongst hospitalized COVID-19 patients, measured every 15 minutes using a novel wearable chest-monitor. A total of 492 patients were included, with >3 million measurements collected including heart rate, systolic and diastolic blood pressure, cardiac output, cardiac index, systemic vascular resistance, respiratory rate, blood oxygen saturation, and body temperature. We show differential trajectories of these vital signs, apparent within the first 24hrs of monitoring. Importantly, we show for the first time that cardiovascular deterioration appears early after admission and in parallel with changes in the respiratory parameters, and identify sub-populations at high risk. Combining frequent monitoring using wearable technology with advanced big data and AI analysis tools may aid early detection of deterioration of COVID-19 patients.

scholarly journals Clinical, Demographic, and Epidemiological Characteristics of Patients Diagnosed with COVID-19 in Zahedan, Southeastern Iran

2021 ◽  
Vol 18 (4) ◽  
Author(s):  
Behzad Shahi ◽  
Faeze Kazemi ◽  
Shahaboddin Mashaei ◽  
Mahdi Foroughian ◽  
Maryam Ziaei ◽  
...  
Keyword(s):  
Vital Signs ◽  
Descriptive Study ◽  
Descriptive Statistics ◽  
Health Centers ◽  
Blood Oxygen ◽  
Shortness Of Breath ◽  
Abo Blood Groups ◽  
Rt Pcr ◽  
Blood Oxygen Saturation ◽  
Epidemiological Characteristics

: As the epidemic spreads, COVID-19 poses a severe threat to the health of communities. Description of epidemiological characteristics of COVID-19 patients helps with the prevention and scientific control of the pandemic. This descriptive study was conducted to describe the clinical, demographic, and epidemiological characteristics of 65 patients suspected of having COVID-19. A research-made questionnaire was used for data collection. Moreover, the patient's vital signs were examined. The samples were classified into the two groups of subjects with positive and negative RT-PCR test. Descriptive statistics were used for the analysis of data. The most common manifestations were fever, shortness of breath, and dry cough. Moreover, the lowest proportion belonged to Rh-negative in all ABO blood groups. The patients were mainly male, about 44 years old, and their first and most common manifestations were fever, shortness of breath, and dry cough. In vital signs examination, reduction of blood oxygen saturation was the most important finding. Health centers need to consider these signs in treating COVID-19 patients.

scholarly journals DeePTOP: Personalized Tachycardia Onset Prediction Using Bi-Directional LSTM in a Medical-Grade Wearable Multi-Sensor System (Preprint)

2020 ◽  
Author(s):  
Xiaoli Liu ◽  
Tongbo Liu ◽  
Po-Chih Kuo ◽  
Haoran Xu ◽  
Zhicheng Yang ◽  
...  
Keyword(s):  
Clustering Algorithm ◽  
Memory Function ◽  
Characteristic Curve ◽  
Wearable Sensors ◽  
Vital Signs ◽  
Predictive Performance ◽  
Diagnostic Procedures ◽  
Blood Oxygen Saturation ◽  
Large Dataset ◽  
Clinical Scenarios

BACKGROUND Without timely diagnosis and treatment, tachycardia, also named as tachyarrhythmia, could cause serious complications such as heart failure, cardiac arrest, and even death. OBJECTIVE The predictive performance of the conventional clinical diagnostic procedures needs improvement in order to assist physicians for the early risk detection. METHODS We propose a Deep Personalized Tachycardia Onset Prediction (DeePTOP) model based on a deep learning model (i.e. BiLSTM) and k-means clustering algorithm for the early individualized tachycardia diagnosis. DeePTOP leverages the vital signs including heart rate (HR), respiratory rate (RR), and blood oxygen saturation (SpO2) acquired continuously by wearable embedded systems and the electronic healthcare records (EHR) containing age, gender, admission type, first care unit, and the history of cardiovascular diseases. The model was trained by a large dataset from intensive care unit and was then transferred to a real-world scenario in general ward. In this study, three experiments including the individualized prediction characteristic, the temporal memory function, and different types of features combination were conducted and six metrics (area under the receiver operating characteristic curve (AU-ROC), precision-recall curve (AU-PR), sensitivity, specificity, accuracy and F1 score) were used for the evaluation of predictive performance. RESULTS Our DeePTOP outperformed the baseline models (AU-ROC: 0.806; AU-PR: 0.725, sensitivity: 0.743; specificity: 0.745; accuracy: 0.749; F1 score: 0.681) when predicting tachycardia onset (TO) six hours in advance on the large dataset. When predicting TO two hours in advance by the data acquired from our hospital using the transferred DeePTOP, the six metrics were 0.904, 0.843, 0.894, 0.898, 0.795, and 0.766, respectively. Among them, the best performance was achieved with comprehensive statistical information of vital signs (HR, RR, and SpO2). CONCLUSIONS DeePTOP is a personalized tachycardia prediction model using eight types of data recorded by wearable sensors and EHR. When validated by real clinical scenarios, the model achieved an outperforming prediction performance 0 - 6 hours before TO. Owing to our implementation and easily accessible data by wearable sensors, we suggest that the model can assist physicians to early discover the potential risks of patients in general wards and houses. CLINICALTRIAL No. S2018-095-01

scholarly journals Comparing the Effects of Suction and Routine Methods on Vital Signs, Arterial Blood Oxygen Saturation and Pain Level of Patients Hospitalized at the Intensive Care Unit

2016 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Aliakbar Keykha ◽  
Hasan Askari ◽  
Abbas Abbaszadeh ◽  
Hasan Enayatie ◽  
Bibi Mahdie Khodadadi Hosini ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Oxygen Saturation ◽  
Vital Signs ◽  
Blood Oxygen ◽  
Pain Level ◽  
Blood Oxygen Saturation ◽  
Arterial Blood ◽  
Arterial Blood Oxygen

scholarly journals A Comparison of Reflective Photoplethysmography for Detection of Heart Rate, Blood Oxygen Saturation, and Respiration Rate at Various Anatomical Locations

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1874 ◽  
Author(s):  
Sally K. Longmore ◽  
Gough Y. Lui ◽  
Ganesh Naik ◽  
Paul P. Breen ◽  
Bin Jalaludin ◽  
...  
Keyword(s):  
Heart Rate ◽  
Oxygen Saturation ◽  
Respiration Rate ◽  
Vital Signs ◽  
Ground Truth ◽  
Human Anatomy ◽  
Anatomical Location ◽  
Blood Oxygen ◽  
Blood Oxygen Saturation ◽  
Multiple Sensors

Monitoring of vital signs is critical for patient triage and management. Principal assessments of patient conditions include respiratory rate heart/pulse rate and blood oxygen saturation. However, these assessments are usually carried out with multiple sensors placed in different body locations. The aim of this paper is to identify a single location on the human anatomy whereby a single 1 cm × 1 cm non-invasive sensor could simultaneously measure heart rate (HR), blood oxygen saturation (SpO2), and respiration rate (RR), at rest and while walking. To evaluate the best anatomical location, we analytically compared eight anatomical locations for photoplethysmography (PPG) sensors simultaneously acquired by a single microprocessor at rest and while walking, with a comparison to a commercial pulse oximeter and respiration rate ground truth. Our results show that the forehead produced the most accurate results for HR and SpO2 both at rest and walking, however, it had poor RR results. The finger recorded similar results for HR and SpO2, however, it had more accurate RR results. Overall, we found the finger to be the best location for measurement of all three parameters at rest; however, no site was identified as capable of measuring all parameters while walking.

scholarly journals PSIX-9 Impacts of bunk management on feedlot performance, carcass characteristics, hydrogen sulfide concentration and blood oxygen saturation in steers fed 25 or 50% modified distillers grains plus solubles

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 422-422
Author(s):  
Rebecca L Moore ◽  
Cierrah J Kassetas ◽  
Leslie A LeKatz ◽  
Bryan W Neville
Keyword(s):  
Hydrogen Sulfide ◽  
Oxygen Saturation ◽  
Management Strategy ◽  
Distillers Grains ◽  
Feed Ratio ◽  
Sulfide Concentration ◽  
Blood Oxygen ◽  
Blood Oxygen Saturation ◽  
Feedlot Performance ◽  
Arterial Blood

Abstract One hundred and twenty-six yearling angus steers (initial body weight 445.87 ± 7.13 kg) were utilized in a 2 x 2 factorial design to evaluate the impacts of bunk management and modified distillers grains plus solubles (mDGS) inclusion on feedlot performance, hydrogen sulfide concentrations and blood oxygen saturation. Treatments included bunk management strategy either control bunk management (CON; clean bunks at the time of next day’s feeding) or long bunk management (LONG; feed remaining at time of next day’s feeding), and two inclusion rates of mDGS either 25% or 50% (DM Basis). On d 0, 7, 14, 21, 28 and 35 rumen gas samples were collected via rumenocentesis, and arterial blood samples were collected on two steers from each pen. No differences (P ≥ 0.09) were observed for dry matter intake, average daily gain and gain-to-feed ratio for bunk management or mDGS inclusion. Hot carcass weight, ribeye area, marbling score and quality grade were not affected (P ≥ 0.48) by either bunk management or mDGS inclusion. Back fat was greater (P = 0.04) for CON steers compared to LONG (1.30 vs 1.12 ± 0.05cm, respectively), but was not affected (P = 0.59) by mDGS inclusion. Steers on CON had greater (P = 0.03) yield grades compared to LONG (3.21 vs 2.96 ± 0.11, respectively). Bunk management strategy did not impact hydrogen sulfide concentrations or blood oxygen saturation (P = 0.82). Hydrogen sulfide concentrations increased (P < 0.001) with increasing mDGS inclusion. Blood oxygen saturation was influenced by day of sampling (P = 0.01). Blood oxygen saturation was not affected (P = 0.07) by mDGS inclusion. The fact that ruminal hydrogen sulfide concentrations increased while blood oxygen saturation remained similar raises questions about the quantity of hydrogen sulfide and metabolic fate of excess hydrogen sulfide in the blood of ruminant animals.

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