Smart Design for UAVs: Understanding the Usage and Precautions of UAV Batteries
Reliability of wireless monitoring using a wearable patch sensor in high-risk surgical patients at a step-down unit in the Netherlands: a clinical validation study
by：CTECHi
2019-12-07
Background and purpose intermittent vital signs measurement is the current standard for hospital wards and is usually recorded every 8 hours.
Therefore, early signs of deterioration may be missed.
Recent innovations have led to the \"wearable\" sensor, which could capture the deterioration of patients in the early stages.
The aim of this study was to determine whether the wireless \"patch\" sensor was able to continuously and reliably measure breathing and heart rate at high humidity
Risk of surgery patients.
The second goal is to explore the potential of wireless sensors as security monitors.
In a comparative study of observational methods, patients were measured for at least 24 hours using wireless sensors and routine bedside standards.
University teaching hospital, single center.
Twenty participants
5 patients admitted to hospital after surgerydown unit.
Results measurement the main result measurement is the consistency and deviation limit of heart rate and respiratory frequency.
Secondary outcome measurements are sensor reliability, defined as the time before data loss occurs for the first time.
Results The analysis time of vital signs data was 1568 hours.
The deviation of heart rate and the consistency limit of 95% are-1. 1 (−8. 8 to 6. 5)
Beats per minute.
For respiratory rate, the deviation is-2.
3 breaths per minute, with a wide range of consent (−15. 8 to 11.
2 breaths per minute).
Median filtering within 15 minutes improves the consistency limit of breathing and heart rate.
63% of the measurements were made with data loss greater than 2 min.
Limited overall data loss (6% of time).
Conclusion the wireless sensor can measure the heart rate accurately, but the accuracy of the breathing frequency is beyond the acceptable range.
Remote monitoring may help early identification of high-risk patients.
Future studies should focus on the ability to detect deterioration of patients at home in low-care settings and after discharge.
Background and purpose intermittent vital signs measurement is the current standard for hospital wards and is usually recorded every 8 hours.
Therefore, early signs of deterioration may be missed.
Recent innovations have led to the \"wearable\" sensor, which could capture the deterioration of patients in the early stages.
The aim of this study was to determine whether the wireless \"patch\" sensor was able to continuously and reliably measure breathing and heart rate at high humidity
Risk of surgery patients.
The second goal is to explore the potential of wireless sensors as security monitors.
In a comparative study of observational methods, patients were measured for at least 24 hours using wireless sensors and routine bedside standards.
University teaching hospital, single center.
Twenty participants
5 patients admitted to hospital after surgerydown unit.
Results measurement the main result measurement is the consistency and deviation limit of heart rate and respiratory frequency.
Secondary outcome measurements are sensor reliability, defined as the time before data loss occurs for the first time.
Results The analysis time of vital signs data was 1568 hours.
The deviation of heart rate and the consistency limit of 95% are-1. 1 (−8. 8 to 6. 5)
Beats per minute.
For respiratory rate, the deviation is-2.
3 breaths per minute, with a wide range of consent (−15. 8 to 11.
2 breaths per minute).
Median filtering within 15 minutes improves the consistency limit of breathing and heart rate.
63% of the measurements were made with data loss greater than 2 min.
Limited overall data loss (6% of time).
Conclusion the wireless sensor can measure the heart rate accurately, but the accuracy of the breathing frequency is beyond the acceptable range.
Remote monitoring may help early identification of high-risk patients.
Future studies should focus on the ability to detect deterioration of patients at home in low-care settings and after discharge.
Although technological advances have brought many new diagnostic tools and treatment innovations, we still cannot identify the deterioration of patients in the general hospital ward in a timely manner.
This helps to avoid CPR and is not planned to enter the intensive care unit (ICU)
Increase in hospital costs and adverse effects on quality of life.
3-7 in order to detect patient deterioration in a timely manner, we may benefit from technical solutions that can continuously track the vital signs of patients.
Intermittent vital signs measurements are usually carried out in routine monitoring practices in general hospital wards, 8 hours per nurse shift.
Therefore, the deterioration of patients between measurements is easily missed.
In order to improve the detection of patient deterioration, early warning scores (EWS)
Most hospitals around the world have implemented agreements and medical emergency teams.
However, failureto-
Even with these systems, the rescue continues.
This phenomenon is also known as the failure of the \"incoming limit\" of the EWS system.
10-12 in addition to trying to improve the detection of deterioration of patients in the ward, there is also a tendency to shorten the length of hospital stay by returning home to patients discharged early, for example, in the programme \"strengthening recovery after recovery.
The EWS protocol and vital signs monitoring are no longer available once the patient returns home.
Recovery in the patient\'s own home environment has many advantages, but inevitably, some surgical complications will now manifest in the home environment in the first place.
This increases the risk that patients deteriorate to be considered too late.
Prior to most adverse events, significant changes in vital signs occurred.
16-20 if continuous remote monitoring is available for-
Risk patients are in a \"low-care\" environment, such as a general hospital ward, or the first few \"critical\" days at home after discharge.
21. 22 recent technological innovations have led to lightweight \"wearable\" wireless sensors capable of recording and transmitting several vital signs such as heart rate (HR)
Breathing rate (RR)
Temperature and movement of the patient.
While most wearable sensors are \"consumers\" in a strict sense \"--
Some manufacturers have achieved European consistency (CE)
Food and Drug Administration (FDA)
Approved for use in a clinical setting.
However, the effectiveness and accuracy of these so-called \"medical care\"
In a real clinical setting, grade wearable devices are not widely evaluated.
The two studies reported a satisfactory agreement between the HR, RR and their respective reference devices for wearable patch sensors.
However, these measurements were obtained from healthy participants under controlled conditions.
Another study showed that HRs and RRs using wearable patch sensors were reliable in most patients, but the data were limited to short-time measurements in patients with co-morbidity.
23-25 therefore, we cannot translate these findings accordingly to patients in a clinical setting at risk of complications.
The aim of this study was to determine whether the wireless adhesive \"patch\" sensor was able to continuously and reliably measure the patient\'s RR and HR after high loadrisk surgery.
Our aim is to verify whether wireless sensor technology is powerful and capable of detecting high
Risk assessment of patients before introducing wireless vital signs monitoring into clinical practice.
The second goal is to explore the potential of wireless sensors as a safety monitor in clinical practice.
Materials and Methods Research Design and setup we conducted a comparative study of methods and observation design in which patients were in high
The procedure of surgery to restore the initial risk surgery-down unit (SDU)
A large academic hospital at the University Medical Center in Utrecht, Netherlands.
The study was formally approved by the local ethics committee (no: 15/550).
Study participants were required to attend the SDU at the time of admission if the expected hospital stay was at least 24 hours.
These patients are considered for admission because they represent a high
Compared with patients in the general ward, a subset of the risk of patients with surgery is more prone to deterioration.
The exclusion criteria are for patients with heart implants, who are allergic to adhesives, who have wound or skin damage near the application site, or who are unable to give informed consent.
After obtaining written informed consent, the researchers applied the sensor to the patient\'s chest and started recording vital signs for 1-3 days using the wearable sensor and the conventional monitoring system described below.
Description of wireless wearable sensors
San Jose vitalep, California, USA)is a medical-
With lightweight, wireless and wearable adhesive sensors, multiple vital signs can be continuously measured: Single
ECG, heart rate variation, RR, skin temperature, body posture and number of steps.
It is designed to promote the long-term
Long-term remote monitoring of hospital environment and life signs and activity indicators at home after discharge.
The sensor consists of a one-time adhesive patch containing two ECG electrodes, a thermal resistor and a zinc-air coincell battery.
Reusable sensor modules include a three-axis accelerometer and Bluetooth Low-Energy (BLE)transceiver (
Appendix 1).
This patch can be applied to the patient\'s chest and the vital signs are continuously measured for up to 3 days (
4 days if its single continuous transmission
Disable lead ECG waveform).
The module processes incoming signals and transmits data to a relay device via BLE (
In this study, we used the iPad mini (
Apple, Cupertino, California, United States of America)
Use the health watch mobile app.
The application can display vital signs data in real time for research purposes, but is not designed for clinical monitoring systems.
Also, near real-
Time data can be viewed on the health watch web cloud-
Monitor for long time based on serverterm trends.
The researchers verified the quality of the sensor data several times during the data collection process.
Patient identity information is not entered on the mobile device to ensure privacy protection.
Supplementary Appendix 1]bmjopen-2017-020162-SP1. pdf]
Although the location can also be measured by wireless sensors, in this study we focus only on assessing the accuracy and reliability of RR and HR monitoring.
Sensors calculate HR using single-Analysislead ECG.
The algorithm is based on the automatic detection of ECG from the ECG waveform.
RR is derived from the combined information of three sources: the embedded algorithm uses the weighted average of the two features of the ECG signal :(1)
Amplitude modulation and (2)
Respiratory sinus arrhythmia; both ECG-
26 derivative signals change during inspiration and expiration, and the algorithm is used (3)
Accelerometer data generated by chest movement during breathing.
27 HR and RR are updated every 4 m/s, and the manufacturer indicates breathing 3 times per minute (breaths/min)
The respiratory range of RR is 4 to 42 times.
The specified accuracy of HR is 5 times per minute (
Beats/min or 10% (
Whichever is larger)
, In the range of 30-200 Beats/minutes.
Continuously monitor patient\'s bedside routine standard dhr and RR using wearable sensors, while using a multi-parameter bedside monitoring system designed specifically for icu and operating room (
XPREZZON, snoquarmi, Washington, DC, United States of America)
As a reference monitor.
This reference uses ECG for heart rate detection and RR is measured by chest impedance pulmonary angiography.
Signal analysis the raw data transmitted by the sensor containing the measured values and their associated timestamps is retrieved in CSV format.
Store and process data using Matlab (
Natick MathWorks, Massachusetts, USA).
Data is empty or invalid (not-a-number)
Was removed to obtain a continuous 2D vector of vital signs samples with corresponding timestamps.
Automatically retrieve data reports from the reference monitor.
These contain vital signs data sampled once a minute (
That is, save and transfer the measurement once per minute).
Therefore, the sensor data originally transmitted per 4S is re-sampled to once per minute (
That is, keep a sensor sample corresponding to the nearest time point of the reference monitor every minute)
Generate paired data points using the reference monitor.
In addition, the sensor data is synchronized with the reference data to ensure that their respective timestamps are aligned.
No artifact removal of the data was performed before the analysis.
In addition to the analysis of vital signs data transmitted per minute, median filters within 15 minutes were applied to study the effects on HR and RR outliers and to further explore the potential of wireless sensors in clinical practice.
This filtering was calculated as a median in the subsequent 15 minutes.
The main result is deviation and precision (
95% restrictions on the agreement (LoA))
HR and RR for wireless sensors compared to bedside monitors.
The reference standard report HR is ± 1% beats or 3 beats/min (
Whichever is larger)
And accuracy of ± 5% or 1 time/minute (
Whichever is larger)for RR.
28 we believe that HR and RR are clinically acceptable if 10% or 3 breaths/min or 5 times/min of the reference monitor.
The secondary endpoint is the reliability of testing truly critical clinical conditions such as brady retardation (HR
Therefore, early signs of deterioration may be missed.
Recent innovations have led to the \"wearable\" sensor, which could capture the deterioration of patients in the early stages.
The aim of this study was to determine whether the wireless \"patch\" sensor was able to continuously and reliably measure breathing and heart rate at high humidity
Risk of surgery patients.
The second goal is to explore the potential of wireless sensors as security monitors.
In a comparative study of observational methods, patients were measured for at least 24 hours using wireless sensors and routine bedside standards.
University teaching hospital, single center.
Twenty participants
5 patients admitted to hospital after surgerydown unit.
Results measurement the main result measurement is the consistency and deviation limit of heart rate and respiratory frequency.
Secondary outcome measurements are sensor reliability, defined as the time before data loss occurs for the first time.
Results The analysis time of vital signs data was 1568 hours.
The deviation of heart rate and the consistency limit of 95% are-1. 1 (−8. 8 to 6. 5)
Beats per minute.
For respiratory rate, the deviation is-2.
3 breaths per minute, with a wide range of consent (−15. 8 to 11.
2 breaths per minute).
Median filtering within 15 minutes improves the consistency limit of breathing and heart rate.
63% of the measurements were made with data loss greater than 2 min.
Limited overall data loss (6% of time).
Conclusion the wireless sensor can measure the heart rate accurately, but the accuracy of the breathing frequency is beyond the acceptable range.
Remote monitoring may help early identification of high-risk patients.
Future studies should focus on the ability to detect deterioration of patients at home in low-care settings and after discharge.
Background and purpose intermittent vital signs measurement is the current standard for hospital wards and is usually recorded every 8 hours.
Therefore, early signs of deterioration may be missed.
Recent innovations have led to the \"wearable\" sensor, which could capture the deterioration of patients in the early stages.
The aim of this study was to determine whether the wireless \"patch\" sensor was able to continuously and reliably measure breathing and heart rate at high humidity
Risk of surgery patients.
The second goal is to explore the potential of wireless sensors as security monitors.
In a comparative study of observational methods, patients were measured for at least 24 hours using wireless sensors and routine bedside standards.
University teaching hospital, single center.
Twenty participants
5 patients admitted to hospital after surgerydown unit.
Results measurement the main result measurement is the consistency and deviation limit of heart rate and respiratory frequency.
Secondary outcome measurements are sensor reliability, defined as the time before data loss occurs for the first time.
Results The analysis time of vital signs data was 1568 hours.
The deviation of heart rate and the consistency limit of 95% are-1. 1 (−8. 8 to 6. 5)
Beats per minute.
For respiratory rate, the deviation is-2.
3 breaths per minute, with a wide range of consent (−15. 8 to 11.
2 breaths per minute).
Median filtering within 15 minutes improves the consistency limit of breathing and heart rate.
63% of the measurements were made with data loss greater than 2 min.
Limited overall data loss (6% of time).
Conclusion the wireless sensor can measure the heart rate accurately, but the accuracy of the breathing frequency is beyond the acceptable range.
Remote monitoring may help early identification of high-risk patients.
Future studies should focus on the ability to detect deterioration of patients at home in low-care settings and after discharge.
Although technological advances have brought many new diagnostic tools and treatment innovations, we still cannot identify the deterioration of patients in the general hospital ward in a timely manner.
This helps to avoid CPR and is not planned to enter the intensive care unit (ICU)
Increase in hospital costs and adverse effects on quality of life.
3-7 in order to detect patient deterioration in a timely manner, we may benefit from technical solutions that can continuously track the vital signs of patients.
Intermittent vital signs measurements are usually carried out in routine monitoring practices in general hospital wards, 8 hours per nurse shift.
Therefore, the deterioration of patients between measurements is easily missed.
In order to improve the detection of patient deterioration, early warning scores (EWS)
Most hospitals around the world have implemented agreements and medical emergency teams.
However, failureto-
Even with these systems, the rescue continues.
This phenomenon is also known as the failure of the \"incoming limit\" of the EWS system.
10-12 in addition to trying to improve the detection of deterioration of patients in the ward, there is also a tendency to shorten the length of hospital stay by returning home to patients discharged early, for example, in the programme \"strengthening recovery after recovery.
The EWS protocol and vital signs monitoring are no longer available once the patient returns home.
Recovery in the patient\'s own home environment has many advantages, but inevitably, some surgical complications will now manifest in the home environment in the first place.
This increases the risk that patients deteriorate to be considered too late.
Prior to most adverse events, significant changes in vital signs occurred.
16-20 if continuous remote monitoring is available for-
Risk patients are in a \"low-care\" environment, such as a general hospital ward, or the first few \"critical\" days at home after discharge.
21. 22 recent technological innovations have led to lightweight \"wearable\" wireless sensors capable of recording and transmitting several vital signs such as heart rate (HR)
Breathing rate (RR)
Temperature and movement of the patient.
While most wearable sensors are \"consumers\" in a strict sense \"--
Some manufacturers have achieved European consistency (CE)
Food and Drug Administration (FDA)
Approved for use in a clinical setting.
However, the effectiveness and accuracy of these so-called \"medical care\"
In a real clinical setting, grade wearable devices are not widely evaluated.
The two studies reported a satisfactory agreement between the HR, RR and their respective reference devices for wearable patch sensors.
However, these measurements were obtained from healthy participants under controlled conditions.
Another study showed that HRs and RRs using wearable patch sensors were reliable in most patients, but the data were limited to short-time measurements in patients with co-morbidity.
23-25 therefore, we cannot translate these findings accordingly to patients in a clinical setting at risk of complications.
The aim of this study was to determine whether the wireless adhesive \"patch\" sensor was able to continuously and reliably measure the patient\'s RR and HR after high loadrisk surgery.
Our aim is to verify whether wireless sensor technology is powerful and capable of detecting high
Risk assessment of patients before introducing wireless vital signs monitoring into clinical practice.
The second goal is to explore the potential of wireless sensors as a safety monitor in clinical practice.
Materials and Methods Research Design and setup we conducted a comparative study of methods and observation design in which patients were in high
The procedure of surgery to restore the initial risk surgery-down unit (SDU)
A large academic hospital at the University Medical Center in Utrecht, Netherlands.
The study was formally approved by the local ethics committee (no: 15/550).
Study participants were required to attend the SDU at the time of admission if the expected hospital stay was at least 24 hours.
These patients are considered for admission because they represent a high
Compared with patients in the general ward, a subset of the risk of patients with surgery is more prone to deterioration.
The exclusion criteria are for patients with heart implants, who are allergic to adhesives, who have wound or skin damage near the application site, or who are unable to give informed consent.
After obtaining written informed consent, the researchers applied the sensor to the patient\'s chest and started recording vital signs for 1-3 days using the wearable sensor and the conventional monitoring system described below.
Description of wireless wearable sensors
San Jose vitalep, California, USA)is a medical-
With lightweight, wireless and wearable adhesive sensors, multiple vital signs can be continuously measured: Single
ECG, heart rate variation, RR, skin temperature, body posture and number of steps.
It is designed to promote the long-term
Long-term remote monitoring of hospital environment and life signs and activity indicators at home after discharge.
The sensor consists of a one-time adhesive patch containing two ECG electrodes, a thermal resistor and a zinc-air coincell battery.
Reusable sensor modules include a three-axis accelerometer and Bluetooth Low-Energy (BLE)transceiver (
Appendix 1).
This patch can be applied to the patient\'s chest and the vital signs are continuously measured for up to 3 days (
4 days if its single continuous transmission
Disable lead ECG waveform).
The module processes incoming signals and transmits data to a relay device via BLE (
In this study, we used the iPad mini (
Apple, Cupertino, California, United States of America)
Use the health watch mobile app.
The application can display vital signs data in real time for research purposes, but is not designed for clinical monitoring systems.
Also, near real-
Time data can be viewed on the health watch web cloud-
Monitor for long time based on serverterm trends.
The researchers verified the quality of the sensor data several times during the data collection process.
Patient identity information is not entered on the mobile device to ensure privacy protection.
Supplementary Appendix 1]bmjopen-2017-020162-SP1. pdf]
Although the location can also be measured by wireless sensors, in this study we focus only on assessing the accuracy and reliability of RR and HR monitoring.
Sensors calculate HR using single-Analysislead ECG.
The algorithm is based on the automatic detection of ECG from the ECG waveform.
RR is derived from the combined information of three sources: the embedded algorithm uses the weighted average of the two features of the ECG signal :(1)
Amplitude modulation and (2)
Respiratory sinus arrhythmia; both ECG-
26 derivative signals change during inspiration and expiration, and the algorithm is used (3)
Accelerometer data generated by chest movement during breathing.
27 HR and RR are updated every 4 m/s, and the manufacturer indicates breathing 3 times per minute (breaths/min)
The respiratory range of RR is 4 to 42 times.
The specified accuracy of HR is 5 times per minute (
Beats/min or 10% (
Whichever is larger)
, In the range of 30-200 Beats/minutes.
Continuously monitor patient\'s bedside routine standard dhr and RR using wearable sensors, while using a multi-parameter bedside monitoring system designed specifically for icu and operating room (
XPREZZON, snoquarmi, Washington, DC, United States of America)
As a reference monitor.
This reference uses ECG for heart rate detection and RR is measured by chest impedance pulmonary angiography.
Signal analysis the raw data transmitted by the sensor containing the measured values and their associated timestamps is retrieved in CSV format.
Store and process data using Matlab (
Natick MathWorks, Massachusetts, USA).
Data is empty or invalid (not-a-number)
Was removed to obtain a continuous 2D vector of vital signs samples with corresponding timestamps.
Automatically retrieve data reports from the reference monitor.
These contain vital signs data sampled once a minute (
That is, save and transfer the measurement once per minute).
Therefore, the sensor data originally transmitted per 4S is re-sampled to once per minute (
That is, keep a sensor sample corresponding to the nearest time point of the reference monitor every minute)
Generate paired data points using the reference monitor.
In addition, the sensor data is synchronized with the reference data to ensure that their respective timestamps are aligned.
No artifact removal of the data was performed before the analysis.
In addition to the analysis of vital signs data transmitted per minute, median filters within 15 minutes were applied to study the effects on HR and RR outliers and to further explore the potential of wireless sensors in clinical practice.
This filtering was calculated as a median in the subsequent 15 minutes.
The main result is deviation and precision (
95% restrictions on the agreement (LoA))
HR and RR for wireless sensors compared to bedside monitors.
The reference standard report HR is ± 1% beats or 3 beats/min (
Whichever is larger)
And accuracy of ± 5% or 1 time/minute (
Whichever is larger)for RR.
28 we believe that HR and RR are clinically acceptable if 10% or 3 breaths/min or 5 times/min of the reference monitor.
The secondary endpoint is the reliability of testing truly critical clinical conditions such as brady retardation (HR
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