Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

The overall goal of the following protocol is to describe how continuous data tracking technology can be used to precisely measure adherence to a prescribed aerobic training intensity. This is achieved by first collecting the data using continuous data tracking technology. During an aerobic exercise training session, using data tracking software, a single file of raw data is obtained for each subject, for each training session, and then converted into an Excel format.

Next, statistical software is used to extract and combine data for a single file per subject, which allows for the achieved intensity to be compared to the target intensity results are obtained the show an adherence rate expressed as the percentage of time spent at the target intensity for a given individual or for a group session by session, or for the entire program. The main advantage of using this technique over existing methods like general attendance or completion rate, is the ability to record continuous measures of exercise intensity, which allows for a precise calculation of adherence to the prescribed training program. So this method can help answer key questions in the pulmonary rehabilitation field, such as which exercise training approach is associated with the best adherence rate in patients with obstructive lung disease.

Though this method can provide insight into adherence to exercise training using a target heart rate range. It can also be easily adapted to other definitions of adherence by replacing target heart rate range with target wattage level speed, or met level. Before beginning, turn off all wireless devices that may cause electrical interference and ensure that the heart rate monitors and equipment are at least one meter apart to minimize crosstalk.

When ready, place the heart rate transmitter onto the patient and turn on the data tracking software. Next, start the aerobic equipment and instruct the participant to reach their target intensity. In this example, participants are asked to train within plus or minus five beats per minute of their target heart rate.

Some examples of the data collected by CardioMEM include the subject ID, duration, level of intensity, distance, pace, heart rate, and metabolic equivalent of physical effort. After data collection, press stop on the aerobic equipment, save the data to cardio memory, in addition to exporting the document for further analysis. Since the CardioMEM software does not track distinct exercise training phases, the data obtained must be processed To eliminate the phases that are not of interest, merge the data files and determine the target intensity.

Open the statistical analysis software to import the newly created Excel file and save the data file before proceeding with the analysis to focus on the data collected during the training phase, the warmup phase needs to be eliminated. The first step is to recode the duration, make the necessary changes to create a variable to identify every second as one. The next step is to create a second temporary variable.

Name this variable tempo two. Once created, recode the new variable to begin at zero. After the variable has been recoded, sum the seconds starting from zero.

Once the sum is obtained, the first 10 minutes of the warmup phase can be eliminated by removing the tempo data that proceeds 599 seconds. Next, the cool down phase needs to be eliminated To do so, sort data in descending order for duration. A to bring the cool down phase to the top of the database.

Recode duration A to identify every second as one. Next, create a second temporary variable named tempo. A two recode the newly created variable to start at zero with the start point defined some the seconds of the tempo, a variable to eliminate the cool down phase, remove tempo data that proceeds 299 seconds.

Next, identify the session number associated with the data set by creating a new variable. Finally, save the modified SPSS document as a new file to merge all sessions for a single patient into a single SPSS database. Open the participant's first session.

Next, merge the remaining sessions into the current file. Once merged, add a column which contains the subject's id. Number next, add a column that contains the subject's target intensity.

Save the database under a different file name. Repeat this procedure for all of the remaining participants. At this point, each participant will have a database containing all sessions.

To group several participants into a single database, open the participant's file, merge the remaining participants to the current file, and save this information as a new database. After the data is prepared, the target intensity can be identified. To do this first, add a column that contains the difference between the heart rate and the target heart rate.

Then recode the variables to determine whether the heart rate lies below, above, or within the target heart rate range. The percent adherence is calculated by determining all seconds that patients were within the target range. Once a value is obtained, convert this into a percentage to obtain the adherence rate as the percentage of time spent within the target heart rate.

For each subject, for all sessions combined, substitute subject ID and session with only subject ID in the aggregate data window to obtain an adherence rate for each session. For all subjects combined, substitute subject ID and session with only session. Lastly, save the database under a different file name.

Ultimately, the data can be used to look at patterns of adherence over time in a given individual or in different groups, or to look at the mean adherence rate throughout the training program for individuals or groups. Once mastered, this procedure can be done in approximately five minutes per session for one subject. While attempting this procedure, it's important to remember to start the cardio memory software before the exercise equipment so that data can be tracked and subsequently recorded.

Secondly, sources of interference must be minimized to reduce the risk of crosstalk and or loss data. After watching this video, you should have a good understanding of how to use continuous data tracking technology to precisely measure adherence to prescribed aerobic training.Intensity.