Title in bold letters
Dr. Petteri AlahuhtaVTT Technical Research Centre of Finland
LtdSmash, Helsinki, 29th November 2016Always-on-Analytics the game
changer in sports!
Video is important but you can not beat measurements!
New wearables are introduced every day!A node for
measurements
Data Cloud Backend+Mobile datacollection app+
Everyday life in sports is more than training sessions onlya
relatively large number of student-athletes were found to show mild
sympoms of sport burnoutSorkkila M. et al, 2016,Psychology of Sport
and ExcersizeUnderstanding total load and stress level of an
athlete is a key to optimal training
Always-on-Analytics is the game changer in sport
Always-on-Analytics is challenging we are addressing wearability
and automated analytics
Wearability
Recent developments for improving wearability of
technologyStretchable electronics- Easy maintenanceLED-foil
integration into wristband in roll-to-roll printing process -
disposablewearablesFlexible LED-display- new functionalities
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VTT Flex NodeWireless chargingMultisensor supportBluetooth
LE
Integrated sensor set includes:Acceleration (3-axis),
Temperature, Relative humidity, Ambient pressureWirless
connectivity - BTLEOnline data streaming to mobile device64 Mbit
flash memory25 mAh rechargeable LiPo battery + Wireless
chargingSize: 20 x 90 mm2VTT Flex Node
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Automated analytics
Key challenges in Always-on-Analytics for sportsFusion of
related data - coverage, sources, time dependencies
Sports professional knowledge transfer to computational
models
Communication & visualization how to facilitate
interpretation of the results
1) E.g. excercise, race, nutrition, different aspects of
life..
2) E.g. sport professional knowledge transfer to computational
models
3) E.g. detailed recommendation in context
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Case: automatic stress detection based on digital behaviour
Detection of stressful events and determining optimal times for
training
Automatic detection of stress level from behavioral dataData
collected from mobile devicesPhysiological data incl. activity and
pulse from wearable devicesUnsupervised learning finds stressful
events from digital behavior as anomalies ~85% accuracy
Experimental stressdetection app by VTT
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Case: deep learning inspired physical activity recognition
Automatic detection and segmentation of daily activities in
real-world settings
Physical activity data-set from wrist-held wearable devices
(~40GB of data)Activity recognition accuracy in real-operating
environment using traditional signal processing ~80% Deep learning
inspired neural networks using raw data only => 97% accuracy
Always-on-Analytics helps to understand the overall situation of
an athlete and defining optimal training routines
Improved wearability help bringing measurements and analytics
into everyday-life settings Recent developments in machine learning
makes it possible to build automatic Always-on-Analytics
services
Key messages
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Thank YouContact: [email protected]
