Prototyping Sensor Network System for Automatic Vital Signs Collection

2013 ◽  
Vol 52 (03) ◽  
pp. 239-249 ◽  
Author(s):  
H. Noma ◽  
C. Naito ◽  
M. Tada ◽  
H. Yamanaka ◽  
T. Takemura ◽  
...  
Keyword(s):  
Sensor Network ◽  
Vital Sign ◽  
Paired Comparison ◽  
Estimation Error ◽  
Vital Signs ◽  
Position Estimation ◽  
University Hospital ◽  
Network System ◽  
Sensing System ◽  
Proximity Sensing

SummaryObjective: Development of a clinical sensor network system that automatically collects vital sign and its supplemental data, and evaluation the effect of automatic vital sensor value assignment to patients based on locations of sensors.Methods: The sensor network estimates the data-source, a target patient, from the position of a vital sign sensor obtained from a newly developed proximity sensing system. The proximity sensing system estimates the positions of the devices using a Bluetooth inquiry process. Using Bluetooth access points and the positioning system newly developed in this project, the sensor network collects vital sign and its 4W (who, where, what, and when) supplemental data from any Blue-tooth ready vital sign sensors such as Continua-ready devices. The prototype was evaluated in a pseudo clinical setting at Kyoto University Hospital using a cyclic paired comparison and statistical analysis.Results: The result of the cyclic paired analysis shows the subjects evaluated the proposed system is more effective and safer than POCS as well as paper-based operation. It halves the times for vital signs input and eliminates input errors. On the other hand, the prototype failed in its position estimation for 12.6% of all attempts, and the nurses overlooked half of the errors. A detailed investigation clears that an advanced interface to show the system’s “confidence”, i.e. the probability of estimation error, must be effective to reduce the oversights.Conclusions: This paper proposed a clinical sensor network system that relieves nurses from vital signs input tasks. The result clearly shows that the proposed system increases the efficiency and safety of the nursing process both subjectively and objectively. It is a step toward new generation of point of nursing care systems where sensors take over the tasks of data input from the nurses.

RF Vital Sign Sensing under Free Body Movement

2021 ◽  
Vol 5 (3) ◽  
pp. 1-22
Author(s):  
Jian Gong ◽  
Xinyu Zhang ◽  
Kaixin Lin ◽  
Ju Ren ◽  
Yaoxue Zhang ◽  
...  
Keyword(s):  
Vital Sign ◽  
Estimation Error ◽  
Body Movement ◽  
Vital Signs ◽  
Motion Artifacts ◽  
Body Parts ◽  
Training Scheme ◽  
Pattern Movement ◽  
Free Body ◽  
Average Estimation Error

Radio frequency (RF) sensors such as radar are instrumental for continuous, contactless sensing of vital signs, especially heart rate (HR) and respiration rate (RR). However, decades of related research mainly focused on static subjects, because the motion artifacts from other body parts may easily overwhelm the weak reflections from vital signs. This paper marks a first step in enabling RF vital sign sensing under ambulant daily living conditions. Our solution is inspired by existing physiological research that revealed the correlation between vital signs and body movement. Specifically, we propose to combine direct RF sensing for static instances and indirect vital sign prediction based on movement power estimation. We design customized machine learning models to capture the sophisticated correlation between RF signal pattern, movement power, and vital signs. We further design an instant calibration and adaptive training scheme to enable cross-subjects generalization, without any explicit data labeling from unknown subjects. We prototype and evaluate the framework using a commodity radar sensor. Under a variety of moving conditions, our solution demonstrates an average estimation error of 5.57 bpm for HR and 3.32 bpm for RR across multiple subjects, which largely outperforms state-of-the-art systems.

scholarly journals Reliability of a wearable wireless patch for continuous remote monitoring of vital signs in patients recovering from major surgery: a clinical validation study from the TRaCINg trial

BMJ Open ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. e031150 ◽  
Author(s):  
Candice Downey ◽  
Shu Ng ◽  
David Jayne ◽  
David Wong
Keyword(s):  
Monitoring System ◽  
Vital Sign ◽  
Vital Signs ◽  
University Hospital ◽  
Secondary Outcome ◽  
Major Surgery ◽  
Limits Of Agreement ◽  
Temperature Bias ◽  
Vital Signs Monitoring ◽  
Recorded Data

ObjectiveTo validate whether a wearable remote vital signs monitor could accurately measure heart rate (HR), respiratory rate (RR) and temperature in a postsurgical patient population at high risk of complications.DesignManually recorded vital signs data were paired with vital signs data derived from the remote monitor set in patients participating in the Trial of Remote versus Continuous INtermittent monitoring (TRaCINg) study: a trial of continuous remote vital signs monitoring.SettingSt James’s University Hospital, UK.Participants51 patients who had undergone major elective general surgery.InterventionsThe intervention was the SensiumVitals monitoring system. This is a wireless patch worn on the patient’s chest that measures HR, RR and temperature continuously. The reference standard was nurse-measured manually recorded vital signs.Primary and secondary outcome measuresThe primary outcomes were the 95% limits of agreement between manually recorded and wearable patch vital sign recordings of HR, RR and temperature. The secondary outcomes were the percentage completeness of vital sign patch data for each vital sign.Results1135 nurse observations were available for analysis. There was no clinically meaningful bias in HR (1.85 bpm), but precision was poor (95% limits of agreement −23.92 to 20.22 bpm). Agreement was poor for RR (bias 2.93 breaths per minute, 95% limits of agreement −8.19 to 14.05 breaths per minute) and temperature (bias 0.82°C, 95% limits of agreement −1.13°C to 2.78°C). Vital sign patch data completeness was 72.8% for temperature, 59.2% for HR and 34.1% for RR. Distributions of RR in manually recorded measurements were clinically implausible.ConclusionsThe continuous monitoring system did not reliably provide HR consistent with nurse measurements. The accuracy of RR and temperature was outside of acceptable limits. Limitations of the system could potentially be overcome through better signal processing. While acknowledging the time pressures placed on nursing staff, inaccuracies in the manually recorded data present an opportunity to increase awareness about the importance of manual observations, particularly with regard to methods of manual HR and RR measurements.

A MOBILE-CARE SYSTEM OVER WIRELESS SENSOR NETWORK FOR HOME HEALTHCARE APPLICATIONS

2007 ◽  
Vol 19 (02) ◽  
pp. 85-90 ◽  
Author(s):  
Ren-Guey Lee ◽  
Chien-Chih Lai ◽  
Shao-Shan Chiang ◽  
Hsin-Sheng Liu ◽  
Chun-Chang Chen ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Vital Sign ◽  
Vital Signs ◽  
Home Healthcare ◽  
Wireless Sensor ◽  
Chronic Patients ◽  
Healthcare Applications ◽  
Residential Gateway ◽  
Care System

In response to the home healthcare requirement of chronic patients, this paper proposes a mobile-care system integrated with a variety of vital-sign monitorings, where all the front-end vital-sign measuring devices are portable and have the ability of short-range wireless communication. In order to make the system suitable for home applications, wireless sensor network is introduced to transmit the captured vital signs to the residential gateway by means of multi-hop relay. Then the residential gateway uploads data to the care server via internet to carry out patient's condition monitoring and the management of pathological data. Furthermore, the system is equipped with the alarm mechanism, where the portable care device is able to immediately perceive the critical condition of the patient and send a warning message to medical and nursing personnels to achieve the goal of prompt rescue.

scholarly journals Accuracy of Vital Signs Measurements by a Smartwatch and a Portable Health Device: Validation Study

10.2196/16811 ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. e16811 ◽  
Author(s):  
Christina Hahnen ◽  
Cecilia G Freeman ◽  
Nilanjan Haldar ◽  
Jacquelyn N Hamati ◽  
Dylan M Bard ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Vital Sign ◽  
Vital Signs ◽  
Final Analysis ◽  
University Hospital ◽  
Health Concern ◽  
Absolute Difference ◽  
Mean Absolute Difference ◽  
The Mean ◽  
Performance Monitor

Background New consumer health devices are being developed to easily monitor multiple physiological parameters on a regular basis. Many of these vital sign measurement devices have yet to be formally studied in a clinical setting but have already spread widely throughout the consumer market. Objective The aim of this study was to investigate the accuracy and precision of heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and oxygen saturation (SpO2) measurements of 2 novel all-in-one monitoring devices, the BodiMetrics Performance Monitor and the Everlast smartwatch. Methods We enrolled 127 patients (>18 years) from the Thomas Jefferson University Hospital Preadmission Testing Center. SBP and HR were measured by both investigational devices. In addition, the Everlast watch was utilized to measure DBP, and the BodiMetrics Performance Monitor was utilized to measure SpO2. After 5 min of quiet sitting, four hospital-grade standard and three investigational vital sign measurements were taken, with 60 seconds in between each measurement. The reference vital sign measurements were calculated by determining the average of the two standard measurements that bounded each investigational measurement. Using this method, we determined three comparison pairs for each investigational device in each subject. After excluding data from 42 individuals because of excessive variation in sequential standard measurements per prespecified dropping rules, data from 85 subjects were used for final analysis. Results Of 85 participants, 36 (42%) were women, and the mean age was 53 (SD 21) years. The accuracy guidelines were only met for the HR measurements in both devices. SBP measurements deviated 16.9 (SD 13.5) mm Hg and 5.3 (SD 4.7) mm Hg from the reference values for the Everlast and BodiMetrics devices, respectively. The mean absolute difference in DBP measurements for the Everlast smartwatch was 8.3 (SD 6.1) mm Hg. The mean absolute difference between BodiMetrics and reference SpO2 measurements was 3.02%. Conclusions Both devices we investigated met accuracy guidelines for HR measurements, but they failed to meet the predefined accuracy guidelines for other vital sign measurements. Continued sale of consumer physiological monitors without prior validation and approval procedures is a public health concern.

A Novel and Smart Wireless Sensor Network System for Real Time Aquaculture Applications

2020 ◽  
Author(s):  
Lakshmi Narayana Thalluri ◽  
Jitendra Prasad Ayodhya ◽  
Yuva Raju Chava ◽  
Bhimeswara Anjaneya Prasad Tati
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Network System

Hospital sensor network system and pathogen inspection of incision infection after spinal surgery

2021 ◽  
Vol 81 ◽  
pp. 103759
Author(s):  
Shengjiang Lv ◽  
Jianwu Jia ◽  
Yanhua Feng ◽  
Jie Zhu
Keyword(s):  
Sensor Network ◽  
Spinal Surgery ◽  
Network System

scholarly journals Performance Analysis of a Full Order Sensorless Control Adaptive Observer for Doubly-Fed Induction Generator in Grid Connected Operation

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1254
Author(s):  
Gianluca Brando ◽  
Adolfo Dannier ◽  
Ivan Spina
Keyword(s):  
Sensorless Control ◽  
Estimation Error ◽  
Position Estimation ◽  
Adaptive Observer ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Rotor Position ◽  
Stator Flux ◽  
Doubly Fed ◽  
Rotor Position Estimation

This paper focuses on the performance analysis of a sensorless control for a Doubly Fed Induction Generator (DFIG) in grid-connected operation for turbine-based wind generation systems. With reference to a conventional stator flux based Field Oriented Control (FOC), a full-order adaptive observer is implemented and a criterion to calculate the observer gain matrix is provided. The observer provides the estimated stator flux and an estimation of the rotor position is also obtained through the measurements of stator and rotor phase currents. Due to parameter inaccuracy, the rotor position estimation is affected by an error. As a novelty of the discussed approach, the rotor position estimation error is considered as an additional machine parameter, and an error tracking procedure is envisioned in order to track the DFIG rotor position with better accuracy. In particular, an adaptive law based on the Lyapunov theory is implemented for the tracking of the rotor position estimation error, and a current injection strategy is developed in order to ensure the necessary tracking sensitivity around zero rotor voltages. The roughly evaluated rotor position can be corrected by means of the tracked rotor position estimation error, so that the corrected rotor position is sent to the FOC for the necessary rotating coordinate transformation. An extensive experimental analysis is carried out on an 11 kW, 4 poles, 400 V/50 Hz induction machine testifying the quality of the sensorless control.

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