Wearables Predictions: Who to Watch for Prediction #4

This is the fourth post in a Wearable Industry Watch Series for each of the 10 Wearables Predictions.  Follow this blog or Twitter handle @WorkTechWork to be notified of each part of the series. To view all predictions and links to the other parts of the series, visit the Wearable Industry Watch Series.

Prediction #4:  Wearables will become more intelligent because of developments in sensor technology and the ability to translate data from these sensors into insight via analytics.

Developments in Sensor Technology:

One of the challenges of wearable electronics is the rigidity of the components and the resulting space requirements to manage ridged components.  Consumers want small, comfortable devices but the inherent rigidity of metal and silicon require that components be kept from bending or flexing or else they can becoming brittle and break, a particularly challenging issue wearable textiles.

Dr. Wenlong Cheng and a team of researchers at Monash University in Melbourne, Australia have come up with a sensor that can bend or be twisted without cracking (read more here).  I had the opportunity to talk with Dr. Cheng about this technology last week and the conversation has me excited for potential applications in the wearable industry, as well as the wider Internet of Things because of this material’s fast response times, high sensitivity and stability under lots of different situations.  This technology could disrupt how all wearable devices are designed in the Biosensing Wearables Landscape described by Rock Health. (image source Rock Health)

RockReportWearables4 from Rock Health

Ability to Translate Sensor Data to Insight via Analytics:

Knowing how many steps taken in a day is one thing, being able to detect anomalies in behavior that resulted in more or less steps, or understanding how the number of steps taken in a day affects behavior, particularly spending behavior, is another and data scientist are working hard to translate sensor data into insight.

It is no easy task.  The Cityzen Sciences team produces D-Shirt, a smart shirt that generates 200,000 data points in one hour.   Big data suddenly became humongous data with such finite data for the quantified self.  Fortunately, the team also offers the Cityzen Data platform which enables data collection and storage so that value, created through analytics, can be created from sensor data.

Cityzen is not alone in analyzing wearable data.  Empath Analytics acquires data from multiple wearable devices and is positioned as a Backend-as-a-Service API to help developers create apps leveraging data from wearable devices.  Empath Analytics can collect, parse, and clean data as well as apply machine learning techniques enabling developers the luxury to focus on generating value for users and improving user experience.

Moreover, big players in the space including Google, Facebook, Microsoft, and others are acquiring sophisticated analytics producing companies with skilled data scientists almost as quick as they can incorporate and build websites.  All that glitters is not gold, though, because it is easy for a bus dev team member to say, “We can turn data into actionable insight” and difficult for a team to actually deliver on that promise.

On a lighter note, what is good for man may also be good for man’s best friend.  Pet wearable players like Whistle  and  Voyce are enabling the quantified pet and using data analytics to enrich the lives of both pets and pet owners.

Lastly, I’ll mention a point on the immense quantities of raw data (recall 200,000 data points and hour from one smart shirt!).  With large data sets, it becomes challenging to identify features in raw data that are meaningful.  Deep learning  may find attributes in quantified self data that humans simply cannot detect.

Are you aware of developments in sensor technology or are you working to translate sensor data into insight?  If so, I want to hear about it so express your thoughts in the comments below or reach out on the contact page.

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Wearables Predictions: Who to Watch for Prediction #3

This is the third post in a Wearable Industry Watch Series for each of the 10 Wearables Predictions.  Follow this blog or Twitter handle @WorkTechWork to be notified of each part of the series. To view all predictions and links to the other parts of the series, visit the Wearable Industry Watch Series.

Prediction #3: Companies that combine the information of multiple sensors in multiple wearable devices will create more value for their consumers than producers of single wearable devices.

Wearable Alpha:

It goes without saying that part of the reason for the platform announcements covered in Who to Watch for Prediction #2 is that these companies are motivated to create these platforms because there is greater value created if multiple devices integrate.  Machine to Machine (M2M) communication generates value because humans don’t have to be involved in passing information from one machine to another, something we used to do by hand, which was error prone, or with tapes and floppy disks, which was time consuming.  With wearable devices, the additional value that results combining wearable device information is what I call Wearable Alpha.  Wearable Alpha results when two wearables create more value for a user when integrated than when unintegrated.  Additional Wearable Alpha is created if the two wearable devices are also integrated with other IoT devices and services.

Wearable Alpha by WorkTechWork


While players in the wearable space, as well as the greater Internet of Things, should execute focused strategies leveraging their strengths to develop technology, players should not forget that integrated solutions will create more value than unintegrated solutions.  Moreover, players should build business models that extract part of the Wearable Alpha to generate returns for shareholders and investors.

Wearable to Wearable Integrators:

Wearable devices are still nascent technologies, with years to go before the market is fully mature.  We do not know today which wearable device solutions will be on the market in one year and new wearable solutions are coming out all the time.  With so much change it is hard to find companies working to gather data from two separate wearable devices, let alone communicate between them.

Sensoria:  People don’t usually wear more than one watch, but people do wear more than one article of clothing so some low hanging fruit in the multiple wearable space is smart clothing for fitness tracking.  Sensoria Fitness Socks  provide the most accuracy of any step counting wearable to also count altitude changes, distance and, more importantly for the expert runners, cadence, foot landing technique and weight distribution on the foot.  Sensoria also produces a sports bra and a tshirt for heart rate monitoring.  With smart socks and a heart rate monitor, an athlete is on the way to reaping the benefits of Wearable Alpha.

ThisPlace: ThisPlace created a software solution called MindRDR that combines the NeuroSky EEG brainwave sensor with Google Glass to control photo taking and sharing.  In other words, you can take a picture and post it online just by thinking.  Today there are only a few people who will benefit from the Wearable Alpha generated by this particular wearable to wearable integration scenario; however, this opens a whole plethora of opportunities for mind controlling IoT devices.

Sensum:  Sensum provides a platform that integrates data streams from multiple wearable devices and health sensors to analyze the emotional response to events.  This generates tremendous amounts of Wearable Alpha when analyzing marketing and other forms of digital media because now, instead of just watching responses through tinted windows and asking questions, observers can capture an accurate reading of emotional response.

Do you integrate sensor information from multiple wearable devices?  If so,  tell me about it in the comments below or reach out here and lets meet up and chat about your technology.

Wearable to Smart Phone Integration:

There are many solutions that connect a wearable device to the smart phone.  The smart phone itself is becoming in some instances a hub with wearable devices connected to it and in other instances a stepping stone from wearable to cloud.  Smart phones are being built with more and more sensors, some of the same sensors built into wearable devices.  As mentioned in Who to Watch for Prediction #1, smart phones can run apps such as the Moves App and gather information from these sensors.  For the “multiple sensors in multiple devices” portion of this prediction to be fulfilled with a smart phone integration, information generated from smart phone sensors must be used and result in Wearable Alpha.  As of this posting, I have not found a company doing this.  Do you integrate information from both wearable device and a smart phone sensors?

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