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    PREPARE FOR THE SECOND WAVE OF FITNESS TRACKERS

    11/27/2014

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    Posted By Simon Montford on Nov 27, 2014
    There are well over a hundred fitness trackers on the market that monitor activity based on movement, and in some cases heartbeat. The problem is that keeping track of exercise, and its effect on the body, is a very complex process. As a gimmick, fitness trackers work just fine, but to be genuinely valuable, particularly to medical professionals, accuracy needs to be improved. Perhaps this is why over 50% of consumers in the States have ditched their trackers, myself included.
    One example of how confusing things can get is the difference between quantity and quality based on the level of exertion expended. For example, first generation trackers can’t tell the difference between a couple of hours of light running versus a short, but very intense, bout of CrossFit (exercise that involves diverse activities such as handstand walking, heavy weightlifting and climbing).

    Some studies have shown that weight training is more beneficial than cardio because muscles continue to burn calories well after the activity ceases, adding further complexity when it comes to activity tracking.

    The second wave of fitness trackers, however, claim to be able to resolve some, if not all, of these bugbears. Jawbone’s recently-announced Up3, the Basis Peak, Atlas and Moov all claim to be able to know what type of exercise the wearer is undertaking, which is a major step forward.

    Amiigo, however, seems to be the best of the bunch because it takes a different approach. In addition to measuring arm movement, the device comes with a shoelace attachment, so it can capture both lower and upper body movements.

    Furthermore, what makes Amiigo unique is that rather than predicting what exercise the wearer is doing, Amiigo learns from real-world activities. It does this by asking the wearer to do an exercise for half a minute or, in the case of sit-ups or weights, ten reps is all it requires. Once complete, the wearer is asked to ‘tag’ the exercise. From then on, Amiigo will automatically recognise what exercise is being performed and will also log the number of reps.

    In addition to accurately measuring movement via motion sensors and accelerometers, the Amiigo also features a sensor that measures skin temperature and an infrared sensor that monitors blood oxygen levels.

    The hope is that if the likes of Apple, Google, and Microsoft share their customers’ data (redacted to retain privacy), wide-ranging and hugely beneficial insights could be gleaned.

    Using a combination of human input and artificial intelligence (known as “mixed-initiative”) to analyse large datasets could, for example, enable medical professionals to change the way they treat people with chronic health conditions. In other words the medical profession could become revolutionized, particularly if the data could be combined with medical records.

    According to the Pew Foundation approximately 140m people in the US have at least one chronic condition, and in the UK the number is 15.4m – costing the British taxpayer £783 ($1250) per person for treatment, medication and operations!

    Instead of designing fitness trackers exclusively for elite athletes and healthy gym-goers, why don’t more startups create devices that are designed for people with critical illnesses? Not only would they be tapping into a hugely lucrative (and highly committed) consumer base but they would also help to improve the quality of millions of people’s lives!

    The only product that we know of that comes close is the Angel, which is a ‘white label’ fitness tracker designed to be ‘open’. It would, therefore, be the ideal platform for entrepreneurial developers who are willing to confront this challenge. Yes. I am aware that there are substantial compliance and legacy system issues associated with this project. but for those who are willing to ‘do the honors’, lucrative and noble rewards await- and not just for the developers, but for consumers as well.

    The article was a guest post for WearableWorldNews.com originally posted on Nov 8, 2014.



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      © Simon Montford (WEB3IOT), 2014-2019. Unauthorized use and/or duplication of this material without express and written permission from this blog’s author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Simon Montford and WEB3IOT with appropriate and specific direction to the original content at web3iot.com.

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