Garmin Vivoactive HR for Rowing & Sculling

Vivoactive HR

Sculling and Rowing

I am a rower and sculler. I first cut my teeth in the sport over 30 years ago while at college rowing on the Charles River. I had been looking for the longest time for a device that I could use to track my heart, stroke rate, and also support GPS mapping of my workout while on the water. There are professional devices that track stroke rate and the like, such as Speed Coach GPSStroke Coach and Coxmate GPS. These are all excellent pieces of equipment, by the way. But, I am not in varsity rowing any more and I was looking for a piece of equipment that could support my rowing “habit” both for indoor and outdoor rowing (aside: I also possess a Concept 2 ergometer, which I love) while also serving the utilitarian purpose of being a good watch that can track heart rate full time.

When I row, however, I am really interested in being able to map the analytics to the motion. The Vivoactive HR enables me to do this as well as to post-process the data. I am into data. As a Chief Analytics Officer in the healthcare field for a medical device and real-time patient surveillance company, it is important to me to be able to access and understand the information collected during an activity. The connectivity and access to data provided by the Vivoactive HR are phenomenal.

Data view from Garmin Connect web site.





The figure above details an example analytics screen, which shows the map of the workout, heart rate, stroke rate, distance traveled at each measurement point, and allows tracking the entire workout with a cross-hair that is dynamic and interactive on the web screen. The unit supports many other types of workouts, including running, biking, pool, golf, walking, indoor rowing on ergometer, SUP rowing, XC skiing, indoor walking, indoor biking, and indoor running, and tracks sleep. The unit can be submerged in water and the battery life is amazing. I normally live with the unit on my wrist, and after 3 days of continuous use, battery is down to, perhaps 80%. I will take it off for an hour or so to charge, and it is good-to-go. I highly recommend this unit for the avid professional or veteran rower (like myself).

Update June 29th, 2017: Comparison among NK, Coxmate, Minimax

Robin Caroe of RowPerfect kindly left me a comment to this post last evening and provided an updated article on comparison among the NK, Coxmate GPS and Catapult Minimax which contains quite valuable data on performance related to these products. I have provided the hyperlink to the article above. Technological differences in sampling rate (e.g.: 5 Hz for NK versus 10 Hz for Coxmate) are important for accuracy. I must say that I was very close to purchasing the Coxmate GPS prior to investigating the Garmin. Upon reading the brochure for the Minimax S4, I am intrigued. The Minimax offers an update rate on the GPS that provides for precision in terms of location. In the Rowperfect article, of the key measures of performance identified, (1) heart rate & heart rate variability; (2) force and length of stroke; and, (3) GPS update rate are important measures for the elite athlete. In the case of the Minimax, GPS update on the order of 100 times per second (10 milliseconds) can reveal boat pitch, roll & yaw. Highly impressive. I would agree, though, that this level of accuracy and precision would be important for the competitive athlete. Yet, in my case (non-competitive, casual athlete), I still love my Garmin. I am able to see and track my position very accurately, monitor my stroke and heart rate, and in terms of heart rate variability, I can write an algorithm in R or Matlab to monitor that measure fairly directly.

As an added resource, has posted a comparison between best rowing machines for training and rowing experience. You can read that review at this link: The Best Rowing Machine: get a total-body workout on dry land.

Medical Device Integration, the Lomb-Scargle Periodogram, and Heart Rate Variability (HRV)

Medical Device Integration, HRV and Lomb-Scargle Periodogram — What’s the Connection?

Predicting the future accurately is a capability essential to the basic functioning of our lives. Many fields identify the benefits of forecasting behavior. These include, but are not limited to, weather, financial, sales, and defense. In these cases, the objective is to estimate with as high a degree of confidence as possible the expected outcome such that the estimated result will match the actual result, once the actual result occurs.

The accuracy of the predictions is, of course, dependent upon many factors. Some of these factors include the accuracy of the models used to predict the future events, the amount and fidelity of information these models require to ensure accuracy, and the length of time into the future over which the prediction is estimated to be valid.

Medical device integration provides access to the raw data collected for heart rate variability assessment (that is, raw ECG signals). The variability of these signals is well known in terms of diagnostic inference and, hence, the data provide the source for data analysis and predictive assessment. The HRV analysis of the raw signals in the case of the LSP focuses on determining the periodicity of the heart rate, how it changes over time, and given other observations, can be used in concert to assess weather there is an impending issue.

Signal processing of time-varying signals can produce information and knowledge that are useful in diagnosis and analysis of underlying ailments. Hence, one benefit of medical device integration is providing these time-varying signals at relatively high frequency. One technique for determining the frequency of events in measurements — periodic signal behavior — is the Lomb-Scargle Periodogram.

The LSP is a technique that is in a class of predictive analytic algorithms for detecting signal periodicity and identifying frequency occurrence of events in raw data

Lomb-Scargle Periodogram derived from Data Sourced through Medical Device Integration for HRV Assessment

The use of the Lomb-Scargle Periodogram (LSP) for the analysis of biological signal rhythms has been well-documented in the literature. I include a White Paper as the start of my analysis into Heart Rate Variability (HRV) and its calculation for the purpose of alert notification on change. Heart Rate Variability (HRV) has been used as an assessment of the autonomic nervous system, based on sympathetic and parasympathetic tone (SNS versus PSNS). High HRV is indicative of parasympathetic tone. Low HRV is indicative of sympathetic tone. Low HRV has been associated with coronary heart disease and those who have had heart attacks.