Author Archives: Robert

Motion capture system

For the EEGsynth project I have developed a full-body 8-channel motion capture system. It is based on the MPU9250 9-DOF inertial motion unit, which contains a three-axis accelerometer, gyroscope and magnetometer. I have combined this with the Madgwick AHRS algorithm, which takes the raw sensor data and computes the yaw, pitch and roll.

The design is based on one battery operated main unit that is worn for example in a Fanny pack around the waist, and up to 8 sensors that are attached to the arms, legs, etc.

The main unit contains a Wemos D1 mini, which is based on the ESP8266 module. It uses the TCA9548 I2C multiplexer to connect a maximum of 8 MPU9250 sensors.

The data from the IMU sensors is streamed using the Open Sound Control (OSC) format. The sampling rate that can be achieved with one sensor is around 200 Hz, the sampling rate for 8 sensors is around 60 Hz.

For initial configuration of the WiFi network it uses WiFiManager. After connecting to my local WiFi network, it has a web-server through which the configuration can be set, which includes the number of sensors and the destination host and port for the OSC UDP packets.

For the IMUs I am using MPU9250 modules that I purchased on Ebay for about 3 USD each.The MPU9250 units fit very nicely in a Hammond 1551MINI enclosure.

I designed the enclosure for the main unit in Fusion360 and printed it on my Prusa I3 MK3 3-D printer. I made two motion capture systems so far, one with black and one with white PLA filament.

The Arduino sketch and more technical documentation can be found here on GitHub.

First steps with a €20 single-channel EEG system

My friend Vladimir recently demonstrated a single-channel EEG system that he got at a hackathon in London. When he mentioned that it only costs €20 (or actually 20 GBP to be more precisely) I immediately decided to order one myself. The ICI-BCI system is a low cost open source brain computer interface.

The bag clearly and rightfully indicates that it is a totally experimental system, and that it should be used with caution.

The basic idea of the amplifier is that it takes an 1000 Hz analog audio signal from the computer or mobile phone, which is amplitude modulated by the ExG signal and subsequently fed back as microphone signal. So the system is fully analog and requires the DAC to be done by the audio input of the computer or phone.

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Configuring Multitech MDOT for TTN

I have a Multitech MDOT-BOX for testing. Configuring it for TTN requires the following connection to a computer, after which AT commands can be used to probe and set parameters. The following resets the MDOT to factory defaults and shows the configuration overview.

AT&F
AT&V

Firmware: 		2.0.0
Library : 		0.0.9-14-g4845711
Device ID:		00:80:00:00:00:00:b3:76
Frequency Band:		FB_868
Public Network:		off
Network Address:	00000000
Network ID:		6c:4e:ef:66:f4:79:86:a6
Network ID Passphrase:	MultiTech
Network Key:		1f.33.a1.70.a5.f1.fd.a0.ab.69.7a.ae.2b.95.91.6b
Network Key Passphrase:	MultiTech
Network Session Key:	00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00
Data Session Key:	00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00
Network Join Mode:	OTA
Tx Data Rate:		SF_7
Tx Power:		11
Log Level:		6
Maximum Size:		242
Minimum Size:		11
Maximum Power:		20
Minimum Power:		2
Data:			0

After adding a device to application page on the TTN console with OTA activation, the following identifiers/keys are listed on the TTN console page for the device

Device EUI
Application EUI
App Key
Device Address
Network Session Key
App Session Key

From the Multitech documentation: In OTA mode, the device only needs to be configured with a network name (+NI=1,name) and network passphrase (+NK=1,passphrase). The network session key, data session key, and network address are all automatically configured.

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EEG combined with VR

We recently had a meeting at the Astron radio telescope for the COGITO project with Daniela de Paulis, Stephen Whitmarsh, Guillaume Dumas and others. One of the goals of that meeting was to try out the combination of the EEG system with the Oculus Rift VR system.

For the COGITO project we are using the GTec Nautilus EEG system. Our specific system comprises of a 32-channel wireless amplifier that mounts on the back of the EEG cap, in combination with EEG caps in three different sizes. The caps have 64 holes at a subset of the  locations of the 5% electrode placement standard. We are not using the “Sahara” dry electrode option, but rather the regular wet electrodes.

We started by removing all electrodes and cups from the cap, to get a clear view on which electrode sites are accessible. The central electrode locations (i.e. the z-line), temporal electrode locations and occipital electrode locations are occluded by the VR head mount. But there are still plenty of electrode locations accessible.

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Art-Net to DMX512 with ESP8266

Update 26 May 2017 – added photo’s of second exemplar and screen shots of web interface for OTA.

Professional stage and theatre lighting fixtures are mainly controlled over DMX512. To allow a convenient interface between the EEGsynth and this type of professional lighting systems, I built an Artnet-to-DMX512 converter. It quite closely follows the design of my Artnet-to-Neopixel LED strip module.

Let me first show the finished product. It has a 5 pin XLR connector, a 2.1 mm power connector, and a multi-color status LED:

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GPS-enabled LoRaWAN temperature sensor

Together with the TTN Nijmegen community we are discussing possible applications of remote sensing nodes in Nijmegen. To get a better view on the TTN coverage in Nijmegen and to get a feel for what works (and what not), we are working on the implementation of some nodes.

The PoC2 TTN gateway will soon be installed by Michiel Nijssen at Maptools in Molenhoek. To help Michiel get started, we agreed that I would give him a fully functional node to play with. Michiel came up with a very concrete idea: it consists of a GPS-enabled temperature sensor that sends the data over LoRaWAN/TTN. Below you can find some details of a very fist implementation.

The node consists of

  • Teensy 3.2 MCU board
  • Dorji LoRa module
  • DS18b20 temperature sensor
  • Ublox NEO-M8N GPS module
  • 4k7 ohm resistor
  • small LED and 200 ohm resistor (not on photo)

I estimate that the material costs amount to 50 euro. It still needs to be soldered in a more sturdy form-factor and a battery and enclosure need to be added.

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Getting started with Pine64

UPDATE: see at the end for some problems that I encountered after the initial install.

The Pine64 is a single board computer that resembles the Raspberry Pi, but with a 64-bit CPU, up to 2GB of RAM and available for $15-$29. It was introduced with a Kickstarter campaign which I supported. My 2GB Pine64 has been lying on a shelf for quite some time, as I was waiting for the kernel, distribution and documentation to mature.

My first installation yesterday went fine (some slight troubles to get WiFi connected), but while updating the kernel, the root disk partition completely filled up and borked the installation. Hence I have to start again. Let me now document it, as I might need to repeat the installation more than a second time.

I primarily followed the instructions from https://www.pine64.pro/getting-started-linux/ with some additional information from http://forum.pine64.org/showthread.php?tid=982. I am working off an Apple MacBook Pro computer.

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ESP-8266 Art-Net NeoPixel module

As explained in a previous post, for the EEGsynth we want to use a neopixel array that can be controlled wirelessly using the DMX512 protocol. I purchased a number of Adafruit neopixel rings with 12, 16 and 24 elements respectively. Each RGBW pixel contains a red, green, blue and white LED. For the 24-pixel ring that means that there are in total 4*24=96 LEDs of which the intensity can be set.

The ESP-8266 module is a versatile WiFi module that comes in many versions. During development I especially like the NodeMCU version, which mounts the ESP-12 module on a development board with USB connection, and the even smaller Wemos D1 mini board. The Wemos D1 mini is hardly more expensive on Ebay than the simpler bare-bone ESP-8266 modules.

The hardware connection is simple: I connected Vcc and GND directly to the Wemos D1 mini board, and connected pin D2 to the data-in of the first pixel. Although the Neopixels are specified for 5V, in my experience the Adafruit rings also work fine at 3.3V, both for power and for the serial control signal. Each LED can take up to 20 mA when fully bright, which means that all LEDs of the 24-pixel RGBW ring can take up to 24*4*20 = 1920 mA, or close to 2 A. However, not all LEDs will be at full intensity at the same time, and driving them with 3.3V rather than 5V further reduces the current. I encountered no issues powering them over the USB port of my MacBook.

For the EEGsynth we want to map a small number of control signals to aesthetically pleasing light effects. E.g. it can control the hue, the frequency with which the array flashes, or the speed with which a bright bar rotates along the ring.

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Scalable lighting systems

The X-mass holiday is always a nice time of the year to spend studying and tinkering on electronics projects. In the EEGsynth project we have identified that it would be cool to control light with brain and body signals, besides controlling modular synthesizers which we have focussed on so far. As it is not yet clear what kind of light and what kind of control will conceptually and aesthetically work well on the EEGsynth control signals, I have been studying both small and large lighting systems. We might for example want to use small and wearable lights on a performer, or control the stage light, or use a LED strip as indicator of the EEG-extracted control signals.

In theatrical and stage performance lighting there is a clearly dominant standard: DMX512. For lighting setups there are many fixtures (i.e. lamps rigged on ceiling mounted truss) that can be remotely controlled over DMX512, not only on-off, but they can be dimmed, the color can be changed, spotlights can be moved, etc. If you look on for example on Thomann, you’ll see that many light fixtures support DMX.

The Disco Biscuits – City Bisco – 10/5/12 – The Mann Center for the Performing Arts – Philadelphia, PA – Photo © Dave Vann 2012

Going to the smallest systems, I considered individual LEDs. Neopixels are a very interesting type of RGB LEDs, which combine a red, green and blue (and sometimes white) LED in a single few-mm small housing together with a controller chip. The controller chip allows the individual LED intensities of the neopixels to be addressed over a serial controller by a microcontroller such as an Arduino. Furthermore, multiple Neopixels can be daisy-chained, where each pixel in the array can be addressed. LED strips consisting of 30, 60 or even 144 pixels per meter can be purchased per meter, for example on Ebay.

Adafruit NeoPixel Ring with 16 x 5050 RGB LEDs with integrated drivers

For the the EEGsynth it is desirable to have a single control module that provides a uniform interface between ExG control signals and light control. An individual neopixel can be considered as an RGB lamp, just like a theatrical stage light. The intensity of the red, green and blue can be controlled, just like the DMX channels of a stage light. Controlling a small LED jewel worn by the performer should not be different than controlling the light of the stage on which the performer acts.

An important difference in the requirements for fixed stage lighting and a small wearable LED jewel is that the first must hook up to existing DMX512 cabling systems, whereas the second should be wireless. This is where Art-Net and the ESP-8266 come in. Art-Net is a protocol for sending the DMX control protocol over a network. The ESP-8266 is a small and low-cost microcontroller combined with a WiFi chip that is compatible with Arduino.

Further details on the hardware and firmware design for the actual light controller modules will come in a series of follow-up posts.

ESP-12 bootloader modes and GPIO state at startup

Since I encountered some initial difficulties in programming the ESP-12 version of the ESP8266 module using the Arduino IDE, let me here summarise some findings based on information from [1,2,3].

esp12-pinout

The ESP-12 module exposes 11 GPIOs. Three of them are especially relevant, as they determine the bootloader mode at startup or following reset.

                                  | GPIO 0 | GPIO 2 | GPIO 15
----------------------------------|--------|--------|---------
Flash Startup (Normal)            |   1    |   1    |   0
UART Download Mode (Programming)  |   0    |   1    |   0
SD-Card Boot                      |   0    |   0    |   1

Furthermore, CHPD should be pulled up and RESET should be pulled up or should be floating. If you connect RESET to ground, the module resets.

I have not yet figured out what the SD-Card boot means, so in my applications GPIO 2 should always be pulled up and GPIO 15 should always be pulled down. I am using 10k resistors, but smaller values (e.g. 3.3k) should also work.

To facilitate development, I connected two push button switches to the GPIO 0 and RESET pins, shorting them to ground when pressed. When the buttons are not pressed, they are both pulled up to 3.3V using a 10k resistor.

This allows me to do the following two-finger-action to restart in programming mode and allow the Arduino IDE to upload a new firmware:
– press reset button
– press programming button
– release reset button
– release programming button

References

[1] https://zoetrope.io/tech-blog/esp8266-bootloader-modes-and-gpio-state-startup
[2] http://www.instructables.com/id/Getting-Started-with-the-ESP8266-ESP-12/
[3] http://www.instructables.com/id/ESP8266-Using-GPIO0-GPIO2-as-inputs/