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Wide Deviation in Fitness Data Estimates by Smart Watches – Deviation Could Exceed 70% in Calories Burnt for Running & Cycling
Smart watches or fitness trackers with their enticing functions in fitness data and body monitor are rising in popularity with consumers. But in a test on 11 models of these devices, the Consumer Council found significant deviation between the estimated and actual fitness data. For example, the deviation in the estimated step counts in daily activities reached 59% and the estimated calories burnt for cycling and running deviated even up to 72%. Consumers should beware that the fitness data presented by smart watches and tracking bands are collected indirectly based on user wrist movements, but not measured by professional instruments. The accuracy of such fitness data, therefore, could deviate easily and should be used for reference only.
The test was conducted in coordination with the International Consumer Research and Testing, the Council released the test results on 11 of the models which are available in the Hong Kong market, including 9 smart watches priced between $1,298 and $5,699, and 2 fitness watches/bands for $598 and $898. Their overall rating was between 2.5 points and 4 points, in accordance with their test performance on mainly: fitness data, smart features, ease of use, associated Apps, battery life and versatility.
In comparing the fitness data estimated by the models with the actual data measured by precision measuring equipment, all models were shown to fare unsatisfactorily in their estimated calories burnt. 4 models deviated in their estimated calories burnt for walking, running, cycling and daily life by over 10%. The most significant deviation was found in the estimated calories burnt for cycling, with deviation in 8 models from 16% to 72% less than the actual data. 8 models also deviated from 16% to 26% less in calories burnt for running. Consumers in slimming mode might feel misled or discouraged if counting on the estimated data which are less than the actual ones. In 7 models, however, their estimated calories burnt for walking turned out with deviation of 12% to 55% higher than the actual data while 1 model was unsatisfactory with deviation of 22% lower.
In the test measuring number of steps of walking, running and daily life, only 4 models were able to achieve good accuracy with the top rating of 5 points. For the rest, 1 model was found with deviation exceeding 10% in all step counts; 6 models with deviation from 11% up to 59% in simulated daily life step counts; 2 models with deviation of 11% and 22% respectively in estimated running steps while 2 models with deviation of 13% and 14% in estimated walking steps.
Furthermore, in the test measuring distance of walking and running, winding routes and paths with occasional absence of GPS signals were selected for the purpose. Only 4 models were less than 10% deviation in estimating both walking and running distance. For the rest, 1 model performed the worst with deviation of 20% and 30% in the estimated distance of walking and running respectively. Moreover, 4 models estimated distance of running with deviation from 11% to 30%; 4 models estimated walking distance with deviation from 11% to 23%.
Among the 10 models with heart rate measurement feature, only 3 models were able to keep deviation within 10% of all test measurements. 1 model scored only 2 points due to low stability of the fitness data, it was found with deviation of 20% and 15% respectively in the heart rates measured in static and low intensity exercise and, under different exercises with repeated heart rate measurements, showed a deviation of 9%. Among the 5 models capable of measuring elevation, 2 models were found with deviation exceeding 15%, with a low 2 points rating. Similarly, 1 out of 7 models with GPS feature was found with deviation in distance measurement of a high 28%, also scored 2 points only.
Consumers should note that while GPS can operate more accurately in open space to pinpoint the location but its use in measuring distance may be affected by factors such as winding routes and location tracking frequency, resulting in wider deviation.
Battery performance is another area of concern to consumers. Except the 1 fitness band model using non-rechargeable button cell with claims that each fresh replacement could last up to 18 months, the test found the time needed to fully recharge the battery for all models ranged from 1.4 hours to 2.9 hours, a onefold difference; and the battery life after fully charged even varied by nearly 10 times, from 1.5 days to 16.3 days, which is something frequent users of smart watches should pay heed.
On evaluation of their smart functions, all models were found to perform well in general, scored either 4 or 4.5 points. All were able to send a clear vibration signal on reception of SMS or messages, but none could send out an effective alert in response to notification from the social media Facebook. The screens of 2 models were susceptible to scratches thus given only 2 points in this specific test item.
The smart watch or fitness band models were evaluated also for ease of use. On the whole their performance was satisfactory and quite similar between 4 or 4.5 points. On software design, 3 models were unable to install App for device with smart phones, receiving only 2 points due to inconvenience of use.
New models of smart watches and fitness tracking bands emerge in the market with all the time. Consumers are advised to choose according to their personal preference and actual needs, bearing in mind that such innovative multi-functional gadgets are not precision measurement instruments and could provide at best data based on estimates. Consumers in need of collecting fitness data for health assessment should consult professional healthcare personnel.
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