Case 1:19-cv-11586-FDS Document 343-12 Filed 03/02/22 Page 1 of 8
`Case 1:19-cv-11586-FDS Document 343-12 Filed 03/02/22 Page 1 of8
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`EXHIBIT AL
`EXHIBIT AL
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`Case 1:19-cv-11586-FDS Document 343-12 Filed 03/02/22 Page 2 of 8
`Case 1:19-cv-11586-FDS Document 343-12 Filed 03/02/22 Page 2 of8
`
`OriginalArticle
`
`Checkfor
`|
`updates,
`Page 1 of 7
`
`Assessing the ability of the Fitbit Charge 2 to accurately predict
`VOsmax
`
`Kaitlin A. Freeberg, Brett R. Baughman, Ted Vickey, Jeff A. Sullivan, Brandon J. Sawyer
`
`Departments of Kinesiology and Biology, Point Loma Nazarene University, San Diego, CA, USA
`Contributions: (I) Conception and design: All authors; (II) Administrative support: KA Freeberg, T Vickey, BJ Sawyer; (II) Provision of study
`materials or patients: KA Freeberg, BR Baughman; (IV) Collection and assembly of data: KA Freeberg, BR Baughman; (V) Data analysis and
`interpretation: KA Freeberg, BJ Sawyer; (VI) Manuscript writing: All authors; (VID Final approval of manuscript: All authors.
`Correspondence to: Brandon J. Sawyer, PhD. Point Loma Nazarene University, Department of Kinesiology and Biology, 3900 Lomaland Drive, San
`Diego, CA 92106, USA. Email: bsawyer@pointloma.edu.
`
`Background: Theaim of this study was to assess the ability of the Fitbit Charge 2 (FBC2) to accurately
`estimate VO,,,.. in comparison to both the gold standard VO;,,,,. test and a non-exercise VO),,.. prediction
`equation.
`Methods: Thirty healthy subjects (17 men, 13 women) between the ages of 18 and 35 (age =21.7+3.1 years)
`were given a FBC2to wearfor seven days and followed instructions on how to obtain a cardio fitness score (CFS).
`VOrmax WaS Measured with an incremental test on the treadmill followed by a verification phase. VO,,,.. was
`predicted via a non-exercise prediction model (N-Ex) using self-reported physicalactivity level.
`Results: Measured VO,,,.. was significantly lower than FBC2 predicted CFS (VO,,... =49.91+6.83; CFS
`=52.53+8.43, P=0.03). N-Ex prediction was significantly lower than CFS but notsignificantly lower than
`measured VO3... (N-Ex =48.79+6.32; CFS us. N-Ex: P=0.01; VO. vs. N-Ex: P=0.54). Relationships
`between both VO,,,.. vs. CFS and VOon2, vs. N-Ex were good ICC: VO,... vs. CFS=0.87, VOon. vs. N-Ex
`=0.87); Bland-Altman analysis indicated consistency of CFS measurement and lack of bias. The coefficient
`of variation (CV) and mean absolute percent error (MAPE) were greater with CFS than N-Ex (CV: CFS
`=6.5%+4.1%, N-Ex =5.6%+3.6%; MAPE: CFS =10.2%+6.7%, N-Ex =7.8%+5.0%). Heart rate (HR)
`estimated by the FBC2 was lower than estimated (Est) HR for pace based on HRextrapolation (FBC2
`=155+18 bpm, Est =183+15 bpm, P<0.001). The difference in CFS and VO,,,,, was inversely correlated with
`the difference in FBC2 HR and Estimated HR (r =-0.45, P<0.001).
`Conclusions: The FBC2 shows consistent, unbiased measurement of CFS while overestimating VO>,...
`in healthy men and women. The non-exercise VO,,,.. prediction equation provides a similar, slightly more
`accurate, VO>,,.. prediction than the CFS without the need for an exercise test or purchase ofa Fitbit.
`
`Keywords: Cardiorespiratory; VO2max; exercise; heart; rate; Fitbit; cardio; fitness; score
`
`Received: 22 May 2019; Accepted: 23 August 2019; Published: 23 September 2019.
`doi: 10.2 1037/mhealth.2019.09.07
`
`View thisarticle at: http://dx.doi.org/10.21037/mhealth.2019.09.07
`
`Introduction
`
`VOromex testing is known as the gold standard for measuring
`cardiorespiratory fitness and is frequently used in research
`settings to determine the efficacy of training program
`interventions (1). Exercise physiology laboratories regularly
`use VOome testing to evaluate the cardiorespiratory health
`of individuals as well as develop exercise prescriptions (1).
`
`Furthermore, VO,,,. is a strong predictor of cardiovascular
`disease (CVD)risk and overall CVD mortality (2). Maximal
`exercise testing has become the standard for measuring
`functional capacity, evaluating therapy, estimating risk, and
`organizing transplantation candidacy in patients with heart
`failure (3). Maximal exercise testing is also important in
`diagnosing and assessing coronary artery disease, peripheral
`
`© mHealth.All rights reserved.
`
`mealth 2019;5:39 | http://dx.doi.org/10.21037/mhealth.2019.09.07
`
`PNA-FB0016682
`
`

`

`Case 1:19-cv-11586-FDS Document 343-12 Filed 03/02/22 Page 3 of 8
`Case 1:19-cv-11586-FDS Document 343-12 Filed 03/02/22 Page 3of8
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`Page 2 of 7
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`mHealth, 2019
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`Table 1 Descriptive statistics ofall participants (n=30)
`Subject characteristic Outcome, mean + SD
`
`
`
`Age (yr)
`
`21.743.1
`
`23.542.6
`BMI (kg/m’)
`Body fat (%) 20.5+7.1
`
`
`
`accurately estimate VO;,,., in comparison to both the
`gold standard VO,,,,, test and a non-exercise VOomax
`prediction equation. We hypothesized that the FBC2 would
`overestimate VO,,,, due to its reduced HR monitoring
`accuracy at increased exercise intensities (6-9).
`
`arterial disease, heart failure, valvular heart disease, and
`unexplained exertional dyspnea (3). Use of exercise testing
`by physicians and non-physicians has grown extensively,
`resulting in the administration of millions of tests (4).
`Despite the accuracy and proliferation of maximaltesting,
`there are difficulties involved that make this type of testing
`2max
`less accessible to the general population. VO,,,,,
`testing
`requires maximal effort and thus puts tremendousstrain on
`the body. Furthermore, maximal testing requires access to
`a lab and specific equipment necessary for assessing oxygen
`uptake, single tests of which can be expensive for the general
`population. Fitbit has released the Charge 2 watch [Fitbit
`Charge 2 (FBC2)], which is advertised to predict VOzn.. by
`displaying a userfriendly “cardio fitness score” (CFS). Using
`the relationship between running pace and heart rate (HR),
`the watch calculates a score comparable to one’s VOzmax in
`mL/kg/min. To our knowledge, Fitbit has not released
`research on how the FBC2 specifically predicts VOxm, thus
`the level of prediction accuracy is unclear. The accurate
`prediction of VO
`amex DY a wrist worn device is appealing due
`to the lower cost, less strenuous testing methodology, and
`potential for more widespread awareness of cardiovascular
`health.
`Other companies, such as Garmin, have created wearable
`personal fitness devices to estimate VOx,01. One study
`soughtto validate the use of the Garmin Forerunner 920XT
`watch in VO,,... estimation (5). Sixteen subjects were
`instructed to jog or run for ten minutes around a football
`field wearing HR monitors and the GPS Garmin watch and
`perform a treadmill VO,,,., test 2-5 days later (5). Results
`showednosignificant differences between the mean VOspe
`from the Garmin watch and the treadmill test as well as a
`high Pearson correlation coefficient (r=0.84), suggesting the
`Garmin Forerunner 920XT provides a relatively accurate
`prediction of VO,,.., (5). However, to our knowledge, no
`studies have been performed to evaluate the accuracy of the
`estimation.
`FBC2 in VOsing
`This study aimed to assess the ability of the FBC2 to
`
`Methods
`
`Experimental design
`
`Thirty subjects (17 men, 13 women) were given the FBC2
`to wear for seven days and followed instructions on how
`to obtain a CFS. Subjects came into the laboratory on two
`separate occasions. VOsma, Was predicted on their first visit
`via a non-exercise prediction model (N-Ex) using selt-
`reported physical activity level (10) and subjects performed
`submaximal exercise to become familiar with the maximal
`exercise equipment. VO}... was measured at their second
`visit via an incremental test on the treadmill followed by a
`verification phase. Body composition was also assessed to
`determine accurate subject characteristics. Participants were
`advised to perform their individual runs at least 48 hours
`apart and abstain from physical activity 48 hours prior to
`their measured VO,,,,, test.
`
`Participants
`
`On the basis of previously published data (11), we calculated
`that completing 27 subjects in our study would yield 95%
`powerto detect a 2% difference in VO... between CFS
`and measured VOomex (at a two-tailed alpha level of 0.05).
`Planning for subject attrition, we enrolled 34 subjects.
`‘Two subjects dropped out due to time constraints and two
`subjects were excluded from data analysis due to failure to
`adhere to instructions on how to obtain a CFS,resulting
`in a final sample size of 30. Physical characteristics of the
`participants who completed the study are shown in Table 1.
`Inclusion criteria were healthy, non-sedentary individuals
`aged 18-35 years old. Non-sedentary individuals were those
`who answered above a zero on the self-reported physical
`activity questionnaire (12). The study was approved by the
`university institutional review board; all subjects provided
`written informed consent and completed a Physical Activity
`Readiness Questionnaire (PAR-Q)before initiating the study
`to determine if the subject was healthy enough to exercise.
`Answering “yes” to any questions on the PAR-Q would
`immediately disqualify anyone from participation in the study.
`
`© mHealth.All rights reserved.
`
`mealth 2019;5:39 | http://dx.doi.org/10.21037/mhealth.2019.09.07
`
`PNA-FB0016683
`
`

`

`Case 1:19-cv-11586-FDS Document 343-12 Filed 03/02/22 Page 4 of 8
`Case 1:19-cv-11586-FDS Document 343-12 Filed 03/02/22 Page 4 of 8
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`miieaith, 2019
`
`Assesswentofbody composition
`
`Body composition measurement was performed using air
`displacement plethysmography (Bod Pod Cosmed, Rome,
`Ttaly) (13). Subjects were fasted and refrained from exercise
`12 hours priorto testing. Wearing minimal clothing(spandex
`shorts or swimsuit) and a swim cap, subjects were weighed
`on a calibrated digital scale and height was recorded from
`a wall-mounted stadiometer (Seca, Birmingham, UK). The
`subject was then instructed to sit quietly within the BOD
`PODchamber for two measurements of body volume, each
`lasting about 45 seconds. Uf these two measurements apreed
`within 150 mL, they were averaged. If the two measurements
`did not agree within 150 mL,a third measurement was taken
`and the two values that were the closest and met criteria for
`apreement were averaged. Usingthe data collected for body
`mass and body volume as well as the predicted thoracic lung
`volume, body density and percent body fat were calculated
`using the Siri equation (14).
`
`Assessment ofsubmaximal HR and equipment
`familiarization
`
`Height and weight measurements were inserted into the
` sing self-reported physical activity level to predict
`VO ome (10). Subjects were equipped with an oronasal
`mask connected to a standard nonrebreathing valve (Hans
`Rudolph, Shawnee, KS, USA) for continous measurement
`of ventilation and respiratory gas exchange data usinga
`previously validated (15) metabolic measurement system
`(Parvo Medics TrueOne 2400; Parvo medics, Sandy, UT,
`USA). A standard 3-point calibration was performed
`before each test or every four hours per manufacturer
`recommendations. While measuring gas exchange and
`HRdata, subjects performed a submaximal treadmill run
`at 60, 70, 80, and 90%of their estimated VO,,,,, (10) to
`become familiar with the equipment. Subjects ran for
`three minutes at each intensity. Usingsteady state HR from
`each running pace, linear regression equations were created
`for each subject using running pace to estimate HR. These
`equations were subsequently used to estimate HR from the
`GPS measured running pace during the independent runs
`while wearing the FBC2. The estimated (Est) HR was then
`compared to the FBC2 measured HR.
`
`Assessment of CFS
`
`Subjects were assigned a FBC2 to wear for seven days. The
`
`Page 3 of 7
`
`FBC2s were updated with the latest firmware at the time
`of the study which was version 22.55.2. During the seven
`days, subjects were asked to complete two independent
`rans on flat terrain with the FBC2. Acceptable locations
`for running were recommended and GPS tracking from
`the watch confirmed participants ran on flat terrain. Hach
`of these runs consisted of a 5-minute warmup at a self-
`selected speed. With GPS and Bluetooth on and paired
`with their Firbir account on their smart phone, subjects
`then performed a 10-minute run. Based on the instructions
`from the manufacturer on how to obtain a CFS, subjects
`were instructed to run at as high of an intensity as could be
`continuously sustained for the full 10 minutes. Subjects then
`synced watch datato their phone application and a CFS was
`calenlated. Screenshots of the CFS, average pace, time, and
`average HR were sent to the primaryinvestigatorafter each
`ofthe tworuns.
`
`Assessinent of VOnas
`
`Subjects were set up with the same metabolic cart and
`procedures as during the familiarization visit. The
`incremental test protocol was chosen using an estimated
`VOand estimated speed and grade that were designed
`to elicit exhaustion in approximately 10 minutes (12). After
`collecting 2 minutes of resting data, subjects warmed up
`for five minutes at a speed of 3.5-4.0 mph and 0% grade
`on the treadmill (Trackmaster, Carrollton, TX, USA).
`After the warm-up phase, the speed increased to a constant
`based on the individualized protocol (4-7 mph) and
`treadmill grade increased continuously by 1% every minute
`until volitional exhaustion. After exhaustion was reached,
`the treadmill speed and grade were immediately reduced to
`2.5 mph and 0% grade for a 10-minute recovery period.
`The verification phase was then performed at 110%
`of peak work rate reached during the initial bout (16).
`VOono, Was confirmed if the verification phase attained
`a VO,max Value within 3% of the incremental test (17). Tf
`the verification phase yielded a VO... which was more
`than 3% below the VO2max value from the incremental
`test, subjects were required to come back and repeat their
`verification phase at the same intensity. If the verification
`phase was more than 3% above the incremental test
`VOomas WOrny Value from subjects were required to do
`test with both incremental and verification
`another VOona.
`
`phases until 3% criterion was achieved. VO,
`max TPOTM
`each test was determined by taking the average of the
`two highest consecutive 15 sec VO, values. Verbal
`
`© mHealth. All rights reserved.
`
`wiblealth 2019;5:39 | btep.//ds.doi.org/10.21037/mhealth.2019.09.07
`
`PNA-FB0016684
`
`

`

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`Page 4 of 7
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`mHealth, 2019
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`Table 2 Average VO.,,...
`
`2max
`
`values from each testing method (n=30)
`
`Measured VO.,,,, Cardio fitness Non-exercise
`
` Subject pool (mL/kg/min) score prediction
`
`
`Combined
`49.91+6.83
`52,.53°'48.43
` 48.79+6,32
`(mean + SD)
`
`Women(n=13)
`45.48+5.90
`46.384+5.97
`44.5643.87
`Men (n=17) 52.02+5.98 53.31+5.50 57.24+6.92
`
`*
`
`
`
`
`
`, significantly higher than measured VOsmax, P=0.03; *,
`significantly higher than Non-Ex, P<0.01.
`
`for bias and consistency in VOon.. estimation by CFS, N-Ex,
`and measured VO,,,,,. Pearson correlations were used to
`examine the relationship between the difference in VOsna.
`measures (measured VO,,,,, - CFS) and the difference in
`HR measured by the FBC2 and estimated by the linear
`regression equations.
`
`Results
`
`VOding, differences
`
`°
`
`aE
`
`3 1
`
`0
`
`‘
`-1.96 SD
`2
`a $158s
`0
`10
`20
`30
`40
`50
`60
`70
`Mean, VOsma, & CFS (mL/kg/min)
`
`‘There was a significant main effect for a difference in
`+1.96 SD
`Ig
`VO,across the three tests (P<0.01). Measured VO,,,,, Was
`iain vereavastecersracrecrcretcea re eserarecrearsra aratenn
`7.61
`>
`.
`°
`significantly lower than CFS (VO,,,,, =4+9.91+6.83 mL/kg/
`5
`x
`°
`°
`e
`min; CFS =52.53+8.43 mL/kg/min, P=0.03) (Iable 2). The
`oa
`wo
`2
`*
`0
`uw
`N-Ex prediction was significantly lower than the CFS
`* Mean
`2 °
`9
`a aa
`but not significantly lower than measured VOjme. (N-Ex
`E
`24
`°
`*
`SG -5
`gas *
`2.92
`%
`=48.7926.32 mL/kg/min; CFS vs. N-Ex: P<0.01; VOomas US.
`>
`+
`oe
`a
`*
`N-Ex: P=0.54. CVs were similar with CFS and N-Ex when
`compared to the gold standard measured VO}... value (CFS
`=6.5%#4.1%; N-Ex =5.6%+3.6%). MAPE waslarger for CFS
`than N-Ex when compared to VOomas (CFS =10.2%+6.7%;
`N-Ex =7.8%+5.0%). Bland-Altman analysis indicated
`consistent, unbiased measurement of CFS (Figure 1). ICCs
`between both VO),,,,, vs. CFS and VO3,,., vs. N-Ex were
`good (VOnmex US. CFS =0.87, VOsmax US. N-Ex =0.87).
`
`o?¢
`
`oa
`
`80
`
`Figure 1 Bland-Altman plot of mean and difference between
`measured VO,,,.. and FBC2 CFS. The solid line represents the
`mean difference of -2.92 mL/kg/min and the dashed lines are the
`95% limits of agreement. FBC2, Fitbit Charge 2; CFS, cardio
`fitness score.
`
`encouragement was given throughout all laboratory VOjn4.
`tests.
`
`Data analysis
`
`All data were analyzed using SPSS Software (SPSS 21.0;
`IBM Corp., Armonk, NY, USA). All data in text, tables, and
`figures are presented as means and standard deviations (SD)
`and significance was set at P<0.05. We tested the outcome
`variables for normality with the Shapiro-Wilk test to assure
`all variables met the assumptionsofthestatistical tests used.
`A repeated measuresanalysis of variance (RMANOVA)with
`a Bonferonni post-hoc test was used to test for ditterences
`measurement
`between the three methods of VO,,,,,
`(VOsinay CFS, and N-Ex). The assumption of sphericity was
`tested before interpreting the results of the RMANOVA.
`Coefficients of variation (CVs) and mean absolute percent
`error (MAPE) were calculated to determine prediction
`accuracy of the CFS and N-Ex. Bland-Altman plots and
`intraclass correlation coefficients (ICCs) were used to test
`
`AR differences
`
`HRestimated by the FBC2 was lower than Est based on
`HRextrapolation (FBC2 =155+18 bpm, Est =183+15 bpm,
`P<0.001) (Figure 2). The difference in CFS and VOonax
`(measured VO. - CFS) was inversely correlated with the
`difference in FBC2 HR and Est HR (Est HR - FBC2 HR)
`(r =-0.45, P<0.01) (Figure 3).
`
`Discussion
`
`Our study found that the FBC2 produces a consistent,
`2max
`unbiased estimate of VO,,,..
`(CFS) while significantly
`overestimating VO}... when compared to the gold-standard
`value obtained from the incremental test with verification.
`Interestingly, the value predicted by the N-Ex model is
`not significantly different from the measured VO... and
`therefore slightly more accurate than the FBC2 CFS
`in predicting VOzn.. This suggests that an individual
`who does not want to perform a maximal exercise test or
`purchase a FBC2 maystill benefit from completing a non-
`
`© mHealth.All rights reserved.
`
`mealth 2019;5:39 | http://dx.doi.org/10.21037/mhealth.2019.09.07
`
`PNA-FB0016685
`
`€
`

`

`Case 1:19-cv-11586-FDS Document 343-12 Filed 03/02/22 Page 6 of 8
`Case 1:19-cv-11586-FDS Document 343-12 Filed 03/02/22 Page 6 of8
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`mHealth, 2019
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`Page 5 of 7
`
`220
`pm) 200
`
`===&aaQooOoO
`
`MeasuredHeartRate(b 2=
`Fitbit
`
`=i QoO
`100
`
`120
`
`180
`160
`140
`Extrapolated Heart Rate (bpm)
`
`200
`
`220
`
`Figure 2 HR values from FBC2 and extrapolation. Thelineis the
`line of identity. FBC2, Fitbit Charge2.
`
`
`
`VOsmaxdifference:measuredVO,,..,-CFS
`
`
`
`
`
`= °
`
` R’=0.1815
`
`-20
`
`80
`60
`40
`20
`0
`Heart Rate Difference: Extrapolated-Fitbit Measured
`
`100
`
`fitness watch against a laboratory test of aerobic capacity (19).
`Eighteen college-age students completed a VOzn.. test on the
`treadmill and performed a Polar fitness test (19). The Polar
`fitness test required that the subject report their physical
`activity level from the last three months based on descriptions
`provided by Polar, then lie supine for five minutes while the
`Polar HRstrap recorded data (19). At the end of thetest, the
`watch would display a VOzn.. value based on the subject’s age,
`height, weight, sex, activity level, maximum HR,and seated
`HR (19). The paired samples T-test showed nosignificant
`differences between the Polar VO,,,,, value and the metabolic
`cart value (Polar: 47.67 mL/kg/min vs. Metabolic Cart:
`44.09 mL/kg/min, P=0.111) (19). Both the Garmin and
`Polar wrist worn fitness devices were not significantly
`different from metabolic cart values, suggesting they may be
`appropriate means of measuring aerobic capacity for those
`not requiring the accuracy of laboratory equipment.
`Difficulty with the Fitbit measuring an accurate HR
`during runs may play a crucial role in the accuracy of
`the CFS (8,9). Wallen ez a/. found that among the Apple
`Watch, Fitbit Charge HR, Samsung Gear S and Mio
`Alpha, all devices underestimated HR in comparison
`to electrocardiography (8). However, it is important to
`note that these underestimations are not always clinically
`significant and may only reach significance under certain
`situations. For example, studies show that as exercise
`intensity increases, there is greater underestimation of HR
`(6,9). Our study discovered an inverse relationship between
`the difference in CFS and VO,,,,, and the difference in
`FBC2 HRandindividual subject extrapolated HR. In other
`words, the more the FBC2 underestimated HR, the more
`it overestimated VO)...
`. Thus, if the FBC2 underestimates
`HR during a run then it will most likely overestimate
`VOomaxy assuming the lower measured HRfora given paceis
`evidence of higherfitness level.
`Onestrength of this study was that VO),,,, testing was
`performed with a verification phase, the current gold
`standard methodology for verifying if subjects reach a “true”
`VOrmax (20). All subjects in this study verified their maximal
`values within 3% and were required to repeattheir tests if
`values were not confirmed. Also, subjects performed two
`individual runs and an average CFS was used forstatistical
`analyses to assess intraclass reliability and assure the
`subjects first run did not skew results. Subjects wore the
`same FBC2 for all seven days of the study and the watch
`was worn for at least 2 nights before subjects performed
`their runs in order to allow the FBC2 to get accustomed to
`the individual’s resting HR. Although instruction was given,
`
`Figure 3 Differences between extrapolated HR and FBC2
`Measured HRin relation to differences between measured VOpimax
`and CFS. FBC2, Fitbit Charge 2; CFS, cardio fitness score.
`
`exercise self-reported physical activity questionnaire, which
`predicts VOjn. with good accuracy.
`A similar study was performed on the Garmin Forerunner
`920XT and found that the Garmin watch was highly
`correlated to aerobic capacity measurements obtained via
`open-circuit spirometry (Garmin: r=0.84) (5). Unlike our
`study, however, the Garmin watch was notsignificantly
`different from the measured aerobic capacity (5). This
`difference in significance between studies could be attributed
`to the different software and prediction equations within
`the watches, as Garmin uses a company called FirstBeat
`‘Technologies and Fitbit does not (18). Furthermore, the use
`of a HR monitor strap during the Garmin watch run may
`have provided more accurate HR data than was obtained
`from the Fitbit wrist worn HRsensor.
`
`A recent study tested the accuracy of the Polar RS300X
`
`© mHealth.All rights reserved.
`
`mealth 2019;5:39 | http://dx.doi.org/10.21037/mhealth.2019.09.07
`
`PNA-FB0016686
`
`

`

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`Page 6 of 7
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`mHealth, 2019
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`subjects were not supervised and no verbal encouragement
`was given during their individual runs. As such, some
`subjects had difficulties obtaining a CFS and may have
`performed better if given encouragement similar to that
`given during the VO,,,,, test. However, these user errors
`are a better depiction of the general population, as the
`average individual would likely not have a personal trainer
`encouraging them and confirming proper use of the FBC2.
`‘To improve our study, measurement of HR during the
`10-minute runs with a chest strap HR monitor would have
`been moreaccurate than extrapolating the data. Despite
`all subjects running on flat terrain, it would have been
`more controlled if individual runs were all recorded at a
`single location. Furthermore, darker skin tones and larger
`wrist circumferences have been associated with decreased
`accuracy of wearable devices (21,22), however, these
`data were not collected. The current study looked at the
`accuracy of VOzmestimation by the FBC2 in a group of
`healthy young men and women; subject race and ethnicity
`were not reported. Therefore, future studies should
`determine the accuracy of the FBC2 for predicting VOone
`in adults varying in age, race, and ethnicity to enhance the
`generalizability of ourresults.
`The results of our study suggest the FBC2 provides a
`consistent, unbiased prediction while overestimating VOomex
`in young, healthy men and women.A non-exercise prediction
`equation provides a similar, slightly more accurate, VOomex
`prediction than the CFS without the need to perform an
`exercise test or purchase a wearable device. The accuracy
`of the FBC2 CFS may belimited by its ability to correctly
`detect exercise HR at increased submaximalintensities.
`
`Acknowledgments
`
`None.
`
`Footnote
`
`Conflicts ofInterest: The authors have no conflicts of interest
`to declare.
`
`Ethical Statement: The authors are accountable for all
`aspects of the work in ensuring that questions related
`to the accuracy or integrity of any part of the work are
`appropriately investigated and resolved. The study was
`approved by the university institutional review board,all
`subjects provided written informed consent.
`
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`mealth 2019;5:39 | http://dx.doi.org/10.21037/mhealth.2019.09.07
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`PNA-FB0016688
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`