POSTED 22.05.17 / BY HOTWASABI

Quantified Self

There has been a recent growth in the availability and development of sensor based wearable devices that aim to help the smartphone generation promote, support, and enhance an active lifestyle. The origins of the industry are rooted in the specific watches and clip-on devices used by runners to track their distance, time and relative performance to relation to various training methods. These devices then developed to include feature such as GPS, Bluetooth, and HR monitor (via separate chest band), and began linking to mobile apps available on smart devices (which in themselves were also being used as monitoring devices as well as location tracking and playing music).

 

  • The first real break from this to a more lifestyle type device was introduced by Nike with the Fuel band. Essentially a simple pedometer (motion) sensor which converted steps (and thus activity) into Nike fuel points, and allowed users to set goals, monitor their performance against these goals via a mobile app or on the web, and importantly compare their activity with others via social networks and the Nike community of Fuel band users.

 

The availability of miniature circuit boards with accelerometer sensors as a result of improvements in manufacturing techniques for smart phones and game console handsets, has allowed other companies to offer similar design-led products which use a single sensor function coupled with intelligent algorithms to measure activity in the form of steps or movement, and to present these results in a often intuitive and well crafted interface on smart phones and tablets. Examples of this are UP from Jawboneand Flex from Fitbit. Both use a motion sensor as the main data source and apply a set of algorithms to allow both monitoring of activity and also sleep (detecting the slight body movements during different sleep phases).

 

They have also used effective deign to allow users to keep the device on at all times (water resistant, surgical grade plastics, long battery life) and to provide feedback to wearers (Led lights, vibrations) and to link to iphone or Android smartphones (Bluetooth low energy or direct plug-in) to upload the data and then present in a user friendly way to track activity against goals, sleep patterns, and suggestions on how to improve your activity or sleep, and allow users to self-monitor their calorie intake by documenting images of food. Since they are based on a wrist-mounted motion sensor they have their limitations, only detecting more intense workouts e.g. running, gym exercise, or swimming, and rely on users manually inputing information about these activities into the mobile app.

 

In another bid to get people using sensors companies are looking to combine existing technology and products with sensors that offer the ability to capture additional data to aid performance. Once such device was the concept earphones from Valencell. As most people listen to music whilst training Valencell combined the earphone with sensors that measure the heart rate and interpret respiration from the blood flow to the ear lobes. So you can listen to your favourite music as well as monitoring your HR as you exercise, without using a separate chest strap, or wrist device. This technology was recently adopted by Samsung for their ICONX ear buds, and by crowdfunded company Bragi with The Dash.

 

Other products have been introduced with more medical based components, such as the BodyMedia device which users sensors to measure galvanic skin response (GSR) known to be related to valance (arousal/excitement <> relaxation) as a means to gauge calorie usage in a system devised to help with weight loss, as well as activity and performance. This has led to an outpouring of new wearable devices being crowd-funded on Kickstart and Indiegogo. In addition there are now several iPhone and Android mobile apps that can measure HR by using the camera to detect change in finger capillary colour as the blood pulses through the body. Some, like the Phillips Vital Signs app can do this using the face [actually the forehead] (rather than putting a finger over the camera lens), and measure the rise and fall of the users chest to interpret respiration rate. Each allowing the user to log, record, and share the data. Even more devices are set to join the market using even more varied biometric feedback to help users get more in-tune with their body, such as Melon; which uses Neurosky technology to measure wearers brainwaves using a very simple, stylish, and easy to wear headband, and through a companion iPhone app that uses brainwave data algorithms to help users improve concentration (attention) and relaxation (meditation).

 

All of this measurement, logging, sharing and uploading leads to ‘big data’ scenario and opportunities for additional apps and cloud services to support this data access and analysis. However just how effective will all this information be? and how will users respond to the range of devices and solutions available? and how elastic is this industry to all the new entrants, devices, and solutions?

 

It is certain that wearable computing (as indicated by the publicity surrounding Google glass project) including quantified-self devices is a potential growth market, hanging onto the coat tails of the rapid and continued growth of the smartphone market in a symbiotic relationship. As we move forward there will be winners and losers (e.g. this is Jawbone’s 2nd attempt to enter the market, their first was a complete flop with several technical problems) and recently Jawbone exited from the fitness tracker market. As seen by the smartphone market itself a key part of success will depend on effective & desirable design, simplicity, function, and how well the solution fits the needs of the user. It is good to see that many of the companies working on solutions today are taking time on the design of the product and companion app, rather than rushing the product to market. With all the hype surrounding wearables, they have yet to reach mass adoption at the level smartphone devices have. There is still a problem with addressing user needs/problems and understanding the value they offer. As products become more affordable, accurate, and inter-connected with the IoT eco system, then the potential exists to reach mass market status.

 

It is clear that these devices are not meant to be medical grade solutions, and accuracy will be within the wider tolerances of a consumer device (eg. a motion sensor worn on the wrist tends to over-estimate steps against a more reliable hip worn pedometer – and is also more prone to error  – picking up steps when simply shaking the wrist, or not picking up steps when pushing a pram). However, with perhaps the exception of the Scandu Scout device,  I do not think users are looking for precision, but as a means to track relative performance to ones own goals and those of a community using the same or similar device/app. In this respect the devices should be accurate enough, and then success will depend on how easily data can be captured, manipulated, presented, shared, analyzed, and used as a means to track daily activity to help maintain a healthy lifestyle, improve fitness, and help with attention or relaxation.

 

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