DETERMINING CARDIOVASCULAR INTENSITY USING HEART RATE DATA
Embodiments provide physiological measurement systems, devices and methods for continuous health and fitness monitoring. A wearable strap may automatically and continually sense and collect data corresponding to the heart rate of a user, which may then be used to determine cardiovascular intensity experienced by the user. Specifically, the heart rate data may be transformed into a time series of heart rate reserve data which is then weighted according to a weighting scheme. The weighted heart rate reserve data may be the basis for programmatically generating an indicator of cardiovascular intensity experienced by the user, which is displayed for a user on the user interface of a display device.
1 . A computer program product comprising non-transitory computer executable code embodied in a non-transitory computer readable medium that, when executing on one or more computing devices, performs the steps of:
programmatically receiving, using a computer system, data corresponding to heart rate of a user during an exercise routine;
transforming the heart rate data to a time series of heart rate reserve data using a processing module of the computer system;
weighting the heart rate reserve data according to a weighting scheme using the processing module of the computer system;
programmatically generating, using the processing module of the computer system, an indicator of cardiovascular intensity based on the weighted heart rate reserve data; and
displaying, on a user interface rendered on a display device of the computer system, the indicator of cardiovascular intensity.
2 . The computer program product of claim 1 , wherein the weighting scheme uses a trained machine learning system implementing a machine learning algorithm embodied on one or more non-transitory computer-readable media, the machine learning system trained to correlate heart rate data to cardiovascular intensities.
3 . The computer program product of claim 2 , wherein the trained machine learning algorithm is retrained to adjust perceived difficulties of exercise routines as the user's fitness improves.
4 . The computer program product of claim 1 , wherein the weighting scheme accounts for cardiovascular efficiencies at different intensity levels.
5 . The computer program product of claim 1 , further comprising code that performs the step of:
displaying qualitative information associated with the intensity score.
6 . The computer program product of claim 5 , wherein the qualitative information comprises one or more of:
an indication of whether the user exceeded the user's anaerobic threshold during the exercise routine;
an indication of whether the user is likely to experience muscle soreness;
an indication of a level of recovery required after the exercise routine; and
an indication of one or more future alterations to the exercise routine that is required based on one or more health-related goals of the user.
7 . The computer program product of claim 1 , wherein the indicator corresponds to a perceived difficulty of the exercise routine by the user, the code further performing the step of:
displaying, on the user interface, the perceived difficulty of the exercise routine.
8 . The computer program product of claim 1 , further comprising code that performs the steps of:
based on the indicator of the intensity of the exercise, automatically altering an exercise plan according to one or more health goals of the user; and
displaying, on the user interface, the altered exercise plan.
9 . The computer program product of claim 1 , further comprising code that performs the steps of:
programmatically receiving data corresponding to heart rate of a second user during an exercise routine;
transforming the heart rate data to a time series of heart rate reserve data;
weighting the heart rate reserve data according to a weighting scheme;
programmatically generating a second indicator of cardiovascular intensity based on the weighted heart rate reserve data; and
displaying, on the user interface rendered on the display device, the indicator corresponding to the user and the second indicator corresponding to the second user.
10 . The computer program product of claim 9 , wherein the heart rate data of the user and the second user are obtained from different user-selected time periods.
11 . A wearable physiological measurement device comprising:
a wearable strap couplable to an appendage of a user configured to monitor and determine a heart rate of the user, the wearable strap including a processing module configured to:
programmatically receive data corresponding to the heart rate of a user during an exercise routine;
transform the heart rate data to a time series of heart rate reserve data;
weight the heart rate reserve data according to a weighting scheme;
programmatically generate an indicator of cardiovascular intensity based on the weighted heart rate reserve data; and
display, on a user interface rendered on a display device, the indicator of cardiovascular intensity.
12 . The wearable physiological measurement device of claim 11 , wherein the weighting scheme uses a trained machine learning system implementing a machine learning algorithm embodied on one or more non-transitory computer-readable media, the machine learning system trained to correlate heart rate data to cardiovascular intensities.
13 . The wearable physiological measurement device of claim 12 , wherein the trained machine learning algorithm is retrained to adjust perceived difficulties of exercise routines as the user's fitness improves.
14 . The wearable physiological measurement device of claim 11 , wherein the weighting scheme accounts for cardiovascular efficiencies at different intensity levels.
15 . The wearable physiological measurement device of claim 11 , wherein the processing module is further configured to:
display qualitative information associated with the intensity score.
16 . The wearable physiological measurement device of claim 15 , wherein the qualitative information comprises one or more of:
an indication of whether the user exceeded the user's anaerobic threshold during the exercise routine;
an indication of whether the user is likely to experience muscle soreness;
an indication of a level of recovery required after the exercise routine; and
an indication of one or more future alterations to the exercise routine that is required based on one or more health-related goals of the user.
17 . The wearable physiological measurement device of claim 11 , wherein the indicator corresponds to a perceived difficulty of the exercise routine by the user, and wherein the processing module is further configured to:
display, on the user interface, the perceived difficulty of the exercise routine.
18 . The wearable physiological measurement device of claim 11 , wherein the processing module is further configured to:
based on the indicator of the intensity of the exercise, automatically alter an exercise plan according to one or more health goals of the user; and
display, on the user interface, the altered exercise plan.
19 . The wearable physiological measurement device of claim 11 , wherein the processing module is further configured to:
programmatically receive data corresponding to heart rate of a second user during an exercise routine;
transform the heart rate data to a time series of heart rate reserve data;
weight the heart rate reserve data according to a weighting scheme;
programmatically generate a second indicator of cardiovascular intensity based on the weighted heart rate reserve data; and
display, on the user interface rendered on the display device, the indicator corresponding to the user and the second indicator corresponding to the second user.
20 . The wearable physiological measurement device of claim 19 , wherein the heart rate data of the user and the second user are obtained from different user-selected time periods.