The normal pulse for healthy adults ranges from 60 to beats per minute. The pulse rate may fluctuate and increase with exercise, illness, injury, and emotions. Females ages 12 and older, in general, tend to have faster heart rates than do males. Athletes, such as runners, who do a lot of cardiovascular conditioning, may have heart rates near 40 beats per minute and experience no problems.
As the heart forces blood through the arteries, you feel the beats by firmly pressing on the arteries, which are located close to the surface of the skin at certain points of the body. The pulse can be found on the side of the neck, on the inside of the elbow, or at the wrist. For most people, it is easiest to take the pulse at the wrist. If you use the lower neck, be sure not to press too hard, and never press on the pulses on both sides of the lower neck at the same time to prevent blocking blood flow to the brain.
When taking your pulse:. Using the first and second fingertips, press firmly but gently on the arteries until you feel a pulse. Count your pulse for 60 seconds or for 15 seconds and then multiply by four to calculate beats per minute. If your doctor has ordered you to check your own pulse and you are having difficulty finding it, consult your doctor or nurse for additional instruction.
The respiration rate is the number of breaths a person takes per minute. The rate is usually measured when a person is at rest and simply involves counting the number of breaths for one minute by counting how many times the chest rises. Respiration rates may increase with fever, illness, and other medical conditions.
When checking respiration, it is important to also note whether a person has any difficulty breathing. Normal respiration rates for an adult person at rest range from 12 to 16 breaths per minute. Blood pressure is the force of the blood pushing against the artery walls during contraction and relaxation of the heart.
Each time the heart beats, it pumps blood into the arteries, resulting in the highest blood pressure as the heart contracts. When the heart relaxes, the blood pressure falls.
Two numbers are recorded when measuring blood pressure. The higher number, or systolic pressure, refers to the pressure inside the artery when the heart contracts and pumps blood through the body.
The lower number, or diastolic pressure, refers to the pressure inside the artery when the heart is at rest and is filling with blood. Both the systolic and diastolic pressures are recorded as "mm Hg" millimeters of mercury. This recording represents how high the mercury column in an old-fashioned manual blood pressure device called a mercury manometer or sphygmomanometer is raised by the pressure of the blood.
Today, your doctor's office is more likely to use a simple dial for this measurement. High blood pressure , or hypertension, directly increases the risk of heart attack, heart failure, and stroke. With high blood pressure, the arteries may have an increased resistance against the flow of blood, causing the heart to pump harder to circulate the blood.
Elevated blood pressure is systolic of to and diastolic less than Stage 1 high blood pressure is systolic is to or diastolic between 80 to Stage 2 high blood pressure is when systolic is or higher or the diastolic is 90 or higher.
These numbers should be used as a guide only. A single blood pressure measurement that is higher than normal is not necessarily an indication of a problem. Your doctor will want to see multiple blood pressure measurements over several days or weeks before making a diagnosis of high blood pressure and starting treatment. Ask your provider when to contact him or her if your blood pressure readings are not within the normal range.
For people with hypertension, home monitoring allows your doctor to monitor how much your blood pressure changes during the day, and from day to day. This may also help your doctor determine how effectively your blood pressure medication is working. Either an aneroid monitor, which has a dial gauge and is read by looking at a pointer, or a digital monitor, in which the blood pressure reading flashes on a small screen, can be used to measure blood pressure.
The aneroid monitor is less expensive than the digital monitor. RR varies with age; for example some older people have a higher baseline RR, which may partly be due to deconditioning Renwick, Monitoring should be increased if the patient shows signs of deterioration.
In acute or critical care areas, RR may be monitored using impedance pneumography, which measures electrical activity in the chest during inhalation and exhalation. However, this method has limitations: patient movement or disconnected chest leads can cause inaccurate measurements, and obstruction to airflow may go undetected as chest wall movement will continue to register as a patient tries to breathe Wilkinson and Thanawala, Capnography monitors, which measure carbon dioxide levels breath by breath, may be a more accurate measurement of RR.
These devices are generally only available in critical care areas, where they are used primarily with patients who are intubated and sedated. On general wards, any patient activity such as talking can cause inaccurate measurements. This can lead to increased alarm fatigue. The observation of RR remains the method of choice, but requires skill and diligence. While other vital signs can be measured continuously using technology, RR often relies on visual observation of chest movement at periodic intervals.
There are limitations to intermittent measurement, which can be affected by issues such as anxiety and activity. Tagged with: Newly qualified nurses: practical procedures. This article has enlightened my knowledge about measuring RR.
Sign in or Register a new account to join the discussion. You are here: Respiratory. Respiratory rate 3: how to take an accurate measurement. Abstract A change in respiratory rate is arguably the first sign of patient deterioration, yet this vital sign is often poorly measured or omitted. The performance of the proposed method of respiratory rate measurement is comparable with current manual counting and other respiratory rate devices reported.
The method has additional advantages that include ease-of-use, quick setup time, and being mobile for wider clinical use. The proposed method has the potential as a tool to measure respiratory rates in a number of use cases. Respiratory rate is one of the most predictive [ 1 , 2 , 3 ] and earliest vital signs [ 4 ] signaling change in clinical status of patients. Despite this, respiratory rate is also one of the most neglected [ 5 ], underutilized, and least recorded [ 6 ] vital signs.
Several reasons exist for this. Nurses do not often have time, due to heavy workloads and other concerns, to complete a full s measurement by manual counts [ 5 ]. Often, a s or s assessment that is multiplied by 2 or 4 is performed that leads to inaccuracies [ 7 , 8 ].
Poor visibility of the start and end of a breath, interruptions, moving patients, difficulty in counting, or remembering a count can lead to further errors [ 9 ]. Technologies to automate respiratory rate measurement can alleviate such issues associated with manual counting. Ginsburg et al. Most technologies however are yet to be adopted widely in general care due to their respective limitations. Inductance plethysmography, capnography, piezoelectric, or bioimpedance-based sensors can be used to measure respiratory rate directly.
They however can suffer from usability issues, for example, difficulty in getting patients to wear straps around the chest [ 11 ]. Acoustic-based sensors can also be used to measure respiratory rate directly. Their performance can however be influenced by environmental noise [ 12 ]. However, these methods can suffer from accuracy issues despite advancements in signal processing [ 13 ]. In this paper, we present a new method of respiratory rate measurement that combines a unique wearable platform for ease of measurement and an accurate and adaptive non-invasive optical approach based on the optical diffuse reflectance phenomenon [ 14 ].
The novelty of the presented approach is the use of a unique wearable platform and a non-invasive vertical-cavity surface-emitting laser VCSEL driven diffuse reflectance based method, to adaptively and directly measure respiratory rate.
The approach uses a VCSEL diode that emits coherent optical radiation on a rest position on chest at micro-Watt emission levels, and uses an integrated photodetector on a second nearby position on chest to sense a diffused collected signal intensity. The stretching of the skin due to thoracic movement results in a net path change and that causes a change in signal intensity at the detector, with a period that corresponds to the respiratory rate. An adaptive signal processing method is used to enhance the device respiratory rate measurements by splitting the signal processing optimizations across different respiratory rate bands.
A study was designed to benchmark the respiratory rate measure from the proposed method to manual counts number of breaths per minute. A total of adult inpatients were recruited from the Changi General Hospital, Singapore, between April 11, , and January 16, , in a single arm trial.
The patients recruited were diagnosed with respiratory diseases of asthma, chronic obstructive pulmonary disease COPD , or pneumonia from the general wards.
Out of the patients recruited, 4 patients had data corrupted during monitoring, while 14 patients had unexpected interruptions during all manual counts. The 4 corrupted data were due to saturation in the detected signal. This was remedied for subsequent patients. The 14 patients with interruptions over all manual counts were due to persistent coughing, hence, blocking line-of-sight. Interruptions occurred when another medical staff interrupted ongoing manual counts or when the patients coughed badly to block line-of-sight during manual counts.
Such interruptions were noted on case report forms. Eighty-two patients were finally selected for analysis. Minimum sample size was determined using a 1 sample, 2-sided t test. A first estimate of mean and standard deviation from 20 volunteers was determined as 1. Similar sizes were used in [ 15 ]. Manual counts were used as reference respiratory rates.
To ensure consistency and eliminate variations, a single dedicated and trained medical staff was deployed to observe and manually count respiratory rates. For every patient, electronic and manual recordings were started concurrently.
They were then benchmarked for comparative analysis. All manual counts and diagnosis were reported on case report forms by hospital medical staff. The method of respiratory rate measurement combined a unique wearable platform with a VCSEL driven optical diffuse reflectance approach to measure respiratory rate while breathing. The diffused light consisted of a vibrational component that corresponded to the stretching of the skin.
Figure 1 highlights this method. Optical diffuse reflectance approach that is used to extract respiratory rate from the diffused collected signal. For efficient clinical use, a unique wearable platform design was developed.
The wearable consisted of a sensor and a disposable patch. A disposable patch was used to allow light emission from the sensor to be in touch with the skin. One side of the patch was a medical-grade transparent adhesive that stuck to the skin and the other side was a hook-and-loop fastener that connected to the sensor.
In the center of the patch was a transparent window that allowed light emission and collection. Figure 2 a shows the patch and sensor module that had dimensions of 3. Figure 2 c shows the front-view use of the device. The average setup time of the device on a subject was Figure 3 a shows an example of the signal intensity at the output of the photo-sensor, after moving average and baseline removal. As can be seen, the signal corresponds to a breathing pattern at a rate equal to the respiratory rate.
This breathing pattern was a direct measurement of the thoracic movement. Figure 3 b shows the Fourier transform of the signal that verifies the respiratory rate as 0.
Plots of a signal from photo-sensor. Preprocessing operations were applied to the raw signal before respiratory rate was extracted. A moving average filter was used to remove high-frequency noise and a baseline filter was used to remove any baseline drifts.
A motion artifact filter using the Teagar operator [ 16 ] was used to identify and correct for motion.
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