SenseView - Various sensors, different manufacturers - one platform to rule them all

Quantified Self Apps & Tools
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Firstly a great big hello to the QS community, I have been an avid lurker for the past 6 month or so, checking out the general views and needs of people who use sensors to track their health or anything else.

This is not a self-promotion post, even though it might seem like one, we are genuinely in need of any input other than our own. Please bear with me :slight_smile:


SenseView is a product of 3 years of very hard and dedicated work by a small group of people who now need, and would dare to ask for your help.

SenseView gives the users the ability to connect to various external or internal sensors to collect, view, share and analyze different sensoric readouts of the user and his/her environment. It is a wonderful (please excuse my obvious bias and enormous love for the project) platform which allows for very quick and simple integration of additional internal or external sensors and algorithms, made by developers around the globe. Currently supports Android 4.0 and higher versions due to an improved interface and processing power requirements - a dual core is preferred, quads work perfectly.

The application works with all internal and an expanding base of external sensors (currently fully supported are Zephyr HxM and BH3 and sensors from Shimmer, which work but are not integrated in this version). Using the Mobilis framework the app can be easily adapted to accept different types of projects, protocols, algorithms and sensors.

Some of the parameters the application can track (in real time) include: ECG, RtoR, breathing rate, posture, accelerations and gyroscopes, GPS, light sensors, proximity sensors, magnetic fields …

SenseView is fully capable of including any additionaly developed algorithms such as: Pedometer(working), fall detection, alarm thresholds for different parametres etc.

Our goal is to make SenseView an open platform, so that users can add their own additional sensors and algorithms in time.

We are now searching for the best candidates amongst commercially available sensors to integrate in the upcoming versions, and would like to ask you, the actual userbase, about what you think. Which sensors would you like to see integrated, what would you change, what bothers you with the application, what do you like? Any suggestions? What would you use it for? What would you like to see us integrate next?

For now our aim is to get as much feedback on different levels as we possibly can.

If you’re still with me, thank you. A bit about us:

I am part of a very small (tiny even) development group called Mobili specializing in bio-sensoric solutions and remote tracking of single persons or groups of people.

We are a part of the CHIRON EU project and have been actively developing our SenseView app for Android devices (4.0+ only), which is built using our Mobilis framework.

I’d like to express our graditute to all of you for help and would ask for
any comments, ideas and suggestions. Anything goes, we will use these
suggestions to make SenseView even better. Don’t be afraid to criticize, we will take everything in account.

Sincere thanks from the Mobili team!

1 Like
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Shameless bump for justice!

Now developing services for SensorDrone and TexasInstruments SensorTag, incorporating** Bluetooth 4.0 LE sensor connectivity on Android devices** (first!) and working towards FitBit and Shimmer sensors.

Another quick demonstration of out (pc) platform, real-time tracking of a ski jumper in the Planica world cup (2012) during a 180 metre long jump:

http://www.youtube.com/watch?v=hDEI7pboF4o - Cannot for the life of me embed this video.

For comparison, the range of Bluetooth connections usually:
Class 1: range up to 100 metres (in most cases 20-30 metres)
Class 2: range up to 30 metres (in most cases 5-10 metres)

Currently around 500 users (PlayStore) in three weeks, any comments are still more then welcome.

If you haven’t yet you can get it for free:

Thanks for viewing :)!

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Hi Ga per
Some interesting points:

  1. Intriguing - I mean the Planica video. How did you convince jumpers to use an equipment? What kind of sensors? I mean, what did they wear, a special suit? I don’t fell very comfortable even with a Polar HR belt wearing during run. No mention to jump more than 100m with it!
  2. What do you mean with real-time tracking? To get all data in real-time, during jump? Don’t wish to lower your claim, but it is more than 200m and there were a lot of people with their mobile phones around.
  3. Is that correct that before jump (as seen on the film), the guy on top had HR more than 180 and still doing nothing?

Tnx for you answers

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Hello, finally some input! :slight_smile:

  1. The jumpers were quite happy to be part of this little “experiment” of ours, there were no complications (I mean which athlete wouldn’t want to see their heart rate almost explode before a competitive run?) they also got their results in a print-out form and they thought it was pretty awesome - as did we.
    All the tracking was done with a Zephyr Bioharness 3, but it could also be done with another sensor.
    The jumpers wore their usual overalls (jumping suits?) and were equipped with the Bioharness3, we didn’t catch any problems nor did anyone complain of feeling uncomfortable.

  2. Real-time tracking means exactly that - everything you see was recorded in real time, we pressed record and saved - it was easier using our Mobilis PC platform, as you can see the whole functionality is accessible from a browser, providing the user has a server (or is using ours) to support data streaming and analysis. The only thing that was edited in later on, are the bubbles explaining the graphs.
    As for the interference, we were ready for that and were using an Bluetooth antenna. Were there no interference (no mobile devices mostly) the same thing could be done without a specialized external antenna.

  3. Wow okay, to answer that we need to define ‘‘doing nothing’’. Sitting on a bench seconds before a huge descent, then soaring through the air and having to think about landing it can hardly be defined as doing nothing, I think he handled it like a champion.

Thanks for your questions!

EDIT: Typos and other worms.

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Now that this discussion is getting going, I’m piling on. I want to see the jump too, but I can’t get the video to play…

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Damn I’m terribly sorry for that :c

Here is the video again:

Here is the link to the site (framework):

Link to the jump site:
http://www.mobili.si/news/mobili/56-ski-jumpers-meassured-with-wireless-biosensors

Any thoughts, suggestions, ideas, improvements, questions welcome!

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Nice! So you just gave sensors to jumpers, mount a huge antenna(s) on strategic places and collected all needed bio-data in real time?

I still have some thoughts about interference - I have a problem with clear connection even with my BT headphones from my kitchen to the living room.

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Hello, sorry for the long wait:

The antenna was a normal Bluetooth antenna (directional). Strategic places not so much, we had two journalist passes and were given random spots by the ramp. There was only one antenna with which I held in my hand.

The interference problem wasn’t really an issue, even though there were about 10,000 out of which we’d say at least 500 had Bluetooth turned on on their mobile devices :).

Also uploading new services for Senseview, new sensors:

TexasInstruments Sensor Tag (BT LE)
SensorDrone - (BT + BT LE)
BT LE service for HeartRate sensors - (supports around 40 sensors)
OBDs - (car sensors)

More at: http://www.senseview.mobi/supported-sensors

Top of a day to you all!

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Wow thank you very much indeed! I hope that wasn’t sarcasm :).

SenseView carries on, looking for anyone with an Android 4.3 device with BT LE
(new Nexus7, Nexus 4, Optimus G, 4X, G2, Galaxy S3, Galaxy S4, Galaxy S4 Mini, and Note 2, Note 3)

In conjunction with any of the above mentioned sensors, preferably the BT LE (smart) ones.
Anyone willing to test or contribute with suggestions/improvements can contact me here or via email.

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Interesting app. I have a Sensordrone on order right now, I will checkout your app when I get the unit in a few weeks.

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Very glad to see people getting interested!

The SensorDrone works like a charm, one of the better tech toys I’ve had the pleasure of playing with.

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I’d just like to notify all of you that SenseView made with our Mobilis Framework, won “App of the Month” and is featured on Bluetooth.org:
“Mobilis SenseView framework helps clients connect mobile sensors for a variety of uses, and in a fraction of the time.”

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Congratulations Jure - !

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After a long wait, some news:

**SenseView is one of the phase1 finalists on the Under Armor 39 challenge, moving towards supporting their sensor! **

SenseView carries on:

New sensor additions:

  • Fitbit (Bar diagrams, web service added)
  • Samsung S4 specific sensors (Ambient air temperature, luminance, ambient air pressure, ambient relative humidity)
  • Nexus 5 sensors (Step counter, step detector)

Other new additions:

  • Session manager
  • Time picker up to 1 year (depends on type (intensity) of data)
  • Imperial units
  • Light theme
  • Continuous accelerometer recording
  • Whole screen buttons if no diagrams are shown
  • Bigger fonts in dashboard
  • Fixed labels in graphs
  • Minor bugs fixed
  • Notification icons for SensorDrone, SensorTag, FitBit …

Still taking suggestions and requests for additional sensor services and looking for beta testers!

Keep on quantifying!

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Hi Gasper

Thanks for sharing the info.

Can your device be used for real-time biofeedback, e.g. using HRV? Any applications available?

I understand it works both with Zephyr Bioharness and HxM, correct?

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Yes, HRV is one of parameters (of course if you have a sensor for it, for example Zephyr Bioharness). SenseView works with Zephyr Bioharness, HxM, HxM Smart and other sensors.

Best regards

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Thanks, but can it do REAL-TIME biofeedback?

E.g. show change of HRV during jogging so a jogger could correct his emotional state?

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YES, all data from sensors are displayed in real time, including R-R (if you use a sensor supporting it).