I’ve encountered a problem with hysteresis and the Interlink FSR and Tekscan flexiforce sensors integrated into the flight controls. Over an extended period of time they are exhibiting up to 10% drift on measurements, the FSR slightly less than the flexiforce. It may be necessary to come up with a scaling model to address this drift.
K4W V2 Dev Preview
Hardware acquisition and evaluation is moving quickly now. I was accepted to the Kinect for Windows V2 Developer Preview program, in part due to previous work with the Kinect for Windows V1. I’ll be adding this to the hardware & API feasibility mini studies I am conducting for the next 1-2 months, to see what biosignal data for subject affect I can reliably acquire with the Kinect For Windows V2 Preview hardware and APIs.
E-Health Sensor Shield
I have identified an interesting hardware option for building a portable system for the bulk of the sensor/data gathering needed to determine pilot affect: the open source eHealth Sensor Platform. It is Arduino or Raspberry Pi based, and offers a rudimentary API for data gathering from sensor like:
It also offers a variety of connectivity options in terms of data transport (USB, serial, 3G, GPRS, Bluetooth, 802.15.4, and ZigBee). I’ve ordered the platform and several sensors to evaluate their performance for use in my research. It’s potentially a good fit, as the flexiforce sensors I have decided to utilize are also Arduino/Raspberry Pi based.
I’ve identified two potential headsets for EEG data acquisition. Over the course of the next several months I will be evaluating each.
Neurosky Mindwave EEG
The Neurosky MindWave is a relatively inexpensive ($99) option, but is limited in that it does not have APIs for raw access to EEG data, only to am affect model developed by the manufacture. It also utilized only two EEG sensors, so it is somewhat limited in its reporting options.
Emotiv EEG
The Emotiv EEG headset is a more expensive option (at $250 or $750 depending on licensing), but it utilizes a 16 sensor setup and has APIs for raw EEG data as well as affective models developed by the manufactures., including an api for interpreting facial expressions, emotional states, and subject intent.
A short 3 minute video of takeoff (tow) to pattern altitude and a quick landing to demonstrate multi monitor support and instrument panel integration.
Recorded with Google Glass
Work continues on my simulator. I now have a fully functioning control panel working with software wrappers that allow it to integrate with multiple flight simulations. Other additions include 3 front speaker mounts fabricated from Vex structural hardware to hang the speakers below the displays.
Now I can start integration with Glass for the affective computing/augmented reality portion of my research!
I have begun assembly of Version 1 of the soaring flight simulator chassis and platform to be used for my dissertation research.It is not yet fully assembled (some parts are still on the way), and some parts are still being fabricated. This is a static (non-motion) platform. Version 2 will include partial motion. Components include… Continue Reading →
