diff --git a/conf.py b/conf.py index 665962ce..3c0a260f 100644 --- a/conf.py +++ b/conf.py @@ -33,9 +33,11 @@ extensions = [ "sphinx_design", "sphinxcontrib.youtube", - "sphinx_copybutton" + "sphinx_copybutton", + "sphinx.ext.todo", ] +todo_include_todos = False templates_path = ['_templates'] exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store', 'env', ".venv"] @@ -87,7 +89,7 @@ "name": "GeM India", } ], - "header_links_before_dropdown": 4, + "header_links_before_dropdown": 5, "show_prev_next": True, "icon_links": [ { diff --git a/guides/index.rst b/guides/index.rst new file mode 100644 index 00000000..5819eab5 --- /dev/null +++ b/guides/index.rst @@ -0,0 +1,11 @@ +.. _upsidedownlabs-guides: + +Guides +###################### + +.. toctree:: + :hidden: + :maxdepth: 1 + + usage-guides/skin-preparation/index + usage-guides/using-bioamp-bands/index \ No newline at end of file diff --git a/guides/usage-guides/skin-preparation/index.rst b/guides/usage-guides/skin-preparation/index.rst new file mode 100644 index 00000000..7df05e93 --- /dev/null +++ b/guides/usage-guides/skin-preparation/index.rst @@ -0,0 +1,87 @@ +.. _skin-preparation: + +Skin Preparation Guide +########################## + +Why skin preparation is important? +*********************************** + +Proper skin preparation is crucial before recording any biopotential signal be it Electrocardiography (ECG), Electromyography (EMG), Electroencephalography (EEG), or Electrooculography (EOG). + +- ``Clear recording surface`` Removes dead skin cells, oils, & other substances that increases skin impedance. +- ``Improve impedance`` Improves the conduction of electrical signals from the body to the recording equipment and minimizes impedance. +- ``Electrode-skin contact`` Ensures optimal contact between the electrodes and the skin surface. +- ``Signal quality`` Enhances the overall quality of recorded signals, providing clear & reliable data for analysis & improves the ability to capture subtle variations in biopotential signals. +- ``Consistency in recordings`` Reduces variability in signal quality, making it easier to make any Human-Computer Interface (HCI), Brain-Computer Interface (BCI) project or a real-world application. +- ``Long term adhesion`` Facilitates long-term adhesion & stable placement of electrodes to the skin during extended signal monitoring. + +Requirements +************** + ++-------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| **NuPrep Gel** | Mildly abrasive, highly conductive gel that should be applied before placing the electrodes on the skin to improve signal quality & enhances the performance of monitoring electrodes. | ++-------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| **Electrode Gel** | Highly conductive gel that acts as a coupling agent between electrodes and the skin to aid the transmission of biopotential signals like ECG, EMG, EOG, or EEG. | ++-------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| **Ten20 Paste** | Contains the right balance of adhesiveness and conductivity, enabling the dry electrodes to remain in place while allowing the transmittance of biopotential signals. | ++-------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| **Alcohol Swabs/Wet wipes** | Soft & non-woven pads that helps in cleaning the skin surface and does not leave any residue. | ++-------------------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ + +Steps to follow +***************** + +You can follow the steps given below to do the skin preparation properly: + +Step 1: Identify the targeted area +===================================== + +Identify the target area where the gel electrodes will be placed for recording ECG, EMG, EEG, or EOG. + +.. image:: media/skin-prep-eog.* + +.. image:: media/skin-prep-emg.* + +.. image:: media/skin-prep-ecg.* + +.. image:: media/skin-prep-eeg.* + +Step 2: Apply the gel +====================== + +Apply a drop of NuPrep gel to your targeted area where the electrodes will be placed. + +.. image:: media/step-2.* + +Step 3 +======= + +Use gentle, circular motions to rub the gel on the skin surface. This removes all the dead skin cells & improves conductivity. + +.. warning:: Do not rub the gel for too long as it has abrasive properties and may cause skin redness and irritation. + +Step 4 +======== + +Wipe away excess gel with the alcohol swabs or wet wipes. + +.. warning:: Close your eyes while using the alcohol swabs for EOG recording else it may cause eye redness & irritation. + +Step 5 +======== + +Now you can either use gel electrodes or the BioAmp bands for the signal recording. + +Using gel electrodes +---------------------- + + Connect the BioAmp cable to gel electrodes, peel the plastic backing from electrodes and place the IN+, IN-, REF cables according to your specific biopotential recording. + +Using BioAmp bands +---------------------- + + Connect the BioAmp cable to your BioAmp band. Now apply a small amount of electrode gel or Ten20 conductive paste on the dry electrodes between the skin and metallic part of BioAmp cable. This improves the signal conductivity, enhancing overall signal quality. + +Now you are all set! Make all the connections correctly and start recording your biopotential signals. + +.. note:: NuPrep gel, Ten20 paste and the alcohol swabs shouldn't be used if you have a history of skin allergies to lotions and cosmetics. \ No newline at end of file diff --git a/guides/usage-guides/skin-preparation/media/skin-prep-ecg.png b/guides/usage-guides/skin-preparation/media/skin-prep-ecg.png new file mode 100644 index 00000000..735ba1b5 Binary files /dev/null and b/guides/usage-guides/skin-preparation/media/skin-prep-ecg.png differ diff --git a/guides/usage-guides/skin-preparation/media/skin-prep-eeg.png b/guides/usage-guides/skin-preparation/media/skin-prep-eeg.png new file mode 100644 index 00000000..f7781ed8 Binary files /dev/null and b/guides/usage-guides/skin-preparation/media/skin-prep-eeg.png differ diff --git a/guides/usage-guides/skin-preparation/media/skin-prep-emg.png b/guides/usage-guides/skin-preparation/media/skin-prep-emg.png new file mode 100644 index 00000000..bfddd9b8 Binary files /dev/null and b/guides/usage-guides/skin-preparation/media/skin-prep-emg.png differ diff --git a/guides/usage-guides/skin-preparation/media/skin-prep-eog.png b/guides/usage-guides/skin-preparation/media/skin-prep-eog.png new file mode 100644 index 00000000..5436974f Binary files /dev/null and b/guides/usage-guides/skin-preparation/media/skin-prep-eog.png differ diff --git a/guides/usage-guides/skin-preparation/media/step-2.png b/guides/usage-guides/skin-preparation/media/step-2.png new file mode 100644 index 00000000..7bab5577 Binary files /dev/null and b/guides/usage-guides/skin-preparation/media/step-2.png differ diff --git a/guides/usage-guides/using-bioamp-bands/index.rst b/guides/usage-guides/using-bioamp-bands/index.rst new file mode 100644 index 00000000..f3b50fc7 --- /dev/null +++ b/guides/usage-guides/using-bioamp-bands/index.rst @@ -0,0 +1,4 @@ +.. _using-bioamp-bands: + +Using BioAmp Bands +################## \ No newline at end of file diff --git a/hardware/bioamp/bioamp-v1.5/index.rst b/hardware/bioamp/bioamp-v1.5/index.rst index f3cb1e89..c79fbe6b 100644 --- a/hardware/bioamp/bioamp-v1.5/index.rst +++ b/hardware/bioamp/bioamp-v1.5/index.rst @@ -3,7 +3,7 @@ BioAmp v1.5 ############ -Small-size portable biopotential amplifier with a no code setup for non-invasive EMG recording! +:bdg-danger:`2023 Edition` Overview ********* @@ -11,7 +11,7 @@ Overview It is a small size portable biopotential amplifier with a no code setup to record and listen to your muscle signals (EMG) non invasively. The best part is that it doesn’t require any microcontroller (like Arduino) to sample the signal. You just plug a 9V battery into the board, electrodes to the body, and an audio jack to a mobile/laptop, and you are ready to record signals from -muscles (EMG) using audacity or Backyard Brain’s spike recorder app. +muscles (EMG) using softwares like audacity or Backyard Brain’s spike recorder app. .. figure:: media/bioamp-v1.5.* :width: 800 @@ -39,8 +39,6 @@ Features & Specifications | Open Source | Hardware + Software | +-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ - - Hardware ********** Images below shows a quick overview of the hardware design. @@ -66,13 +64,36 @@ Images below shows a quick overview of the hardware design. .. figure:: media/back-pcb.* -.. figure:: media/front-assembled-with-wires-1.* +.. figure:: media/Assembly/16.* :align: center + :width: 70% + + Assembled BioAmp v1.5 + +Contents of the kit +******************** + +.. image:: media/kit-contents.* + +Software requirements +********************** -Assemblying the kit +Before you start using the kit, download Backyard Brains' `Spike Recorder `_ or `Audacity `_ according to the operating system you are using (Windows, OSX, Linux). + +.. figure:: ../../../kits/diy-neuroscience/basic/media/byb.* + + **Backyard Brains Spike Recorder** + +.. figure:: media/audacity.* + + **Audacity (An easy-to-use, multi-track audio editor and recorder)** + +Assembling the kit ******************** -You can get your own Bioamp v1.5 bag of parts from `our store `_ or `Tindie `_ or the step by step guide below. +You can get your own BioAmp v1.5 bag of parts from our `online stores `_ (shipping worldwide) and for assembling the board you can take a look at the step by step guide given below. + +**Note:** Follow the highlighted yellow shapes to assemble your BioAmp v1.5! .. grid:: 1 1 3 3 :margin: 2 2 0 0 @@ -169,25 +190,134 @@ You can get your own Bioamp v1.5 bag of parts from `our store `_ from playstore. +2. Open the app, click the setting icon on the top right corner and set the recording type to EMG. +3. Apply the 50Hz or 60Hz notch filter depending on the country you are living in. For example if you are in India then the AC current oscillates at a frequency of 50Hz but it oscillates at 60Hz frequency in USA. This AC current acts as a noise in the signals so we have to remove it by applying this notch filter. +4. Again click on the setting icon to close it and you are ready. +5. Flex your muscles to be able to visualize the muscle signals (EMG). +6. You can record the EMG data as a .wav file by pressing the record button on the top right corner of the app and then convert it in any other format as per your project requirements. + +.. image:: media/emg-in-mobile.* + +Step 7: Visualize the EMG signals on laptop +============================================ + +Connect the BioAmp AUX cable to your laptop that has 3.5mm jack support. + +Now there are various options to visualize the EMG signals: + +Using Backyard Brains' Spike Recorder +-------------------------------------------- -To measure the EMG signals, just connect BioAmp Cable v3 with the hardware as shown in the image below, and get started. +1. Install the spike recorder software that you downloaded earlier. +2. Open the software, click the setting icon on the top right corner and set the low band pass filter to 72Hz and high band pass filter to 720Hz. +3. Apply the 50Hz or 60Hz notch filter depending on the country you are living in. For example if you are in India then the AC current oscillates at a frequency of 50Hz but it oscillates at 60Hz frequency in USA. This AC current acts as a noise in the signals so we have to remove it by applying this notch filter. +4. Again click on the setting icon to close it and you are ready. +5. Flex your muscles to be able to visualize the muscle signals (EMG) +6. You can record the EMG data as a .wav file by pressing the record button on the top right corner of the app and then convert it in any other format as per your project requirements. -.. figure:: media/connections.* +.. image:: media/emg-in-laptop.* -Using the Sensor -******************* +Using Audacity +---------------- -.. .. youtube:: ujFsAE0E0nk -.. :align: center -.. :width: 100% +1. Install the audacity software that you downloaded earlier. +2. Open the software and set the recording device to microphone. +3. Flex your muscles to be able to visualize the muscle signals (EMG) +4. By default the EMG data would be recorded as a .wav file but you can convert it in any other format as per your project requirements. -Some project ideas -************************ +.. image:: media/emg-in-audacity.* -.. We have curated a playlist for you which consists some awesome project ideas for you to get started with your next HCI project. -.. .. youtube:: https://youtube.com/playlist?list=PLtkEloJ7UnkQIoz1HK4IXWujCB8hKdiKU&si=osloTX71TE7AJ3CF -.. :width: 100% -.. :align: center diff --git a/hardware/bioamp/bioamp-v1.5/media/9v-battery.png b/hardware/bioamp/bioamp-v1.5/media/9v-battery.png new file mode 100644 index 00000000..5870c92c Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/9v-battery.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/audacity.png b/hardware/bioamp/bioamp-v1.5/media/audacity.png new file mode 100644 index 00000000..c9b7d543 Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/audacity.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/bioamp-v1-5-connections.png b/hardware/bioamp/bioamp-v1.5/media/bioamp-v1-5-connections.png new file mode 100644 index 00000000..051f33e9 Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/bioamp-v1-5-connections.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/bioamp-v1-5-emg.png b/hardware/bioamp/bioamp-v1.5/media/bioamp-v1-5-emg.png new file mode 100644 index 00000000..f956261a Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/bioamp-v1-5-emg.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/board-with-cables.png b/hardware/bioamp/bioamp-v1.5/media/board-with-cables.png new file mode 100644 index 00000000..6cc4e5e9 Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/board-with-cables.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/connections.png b/hardware/bioamp/bioamp-v1.5/media/connections.png deleted file mode 100644 index e218b2f5..00000000 Binary files a/hardware/bioamp/bioamp-v1.5/media/connections.png and /dev/null differ diff --git a/hardware/bioamp/bioamp-v1.5/media/connections.webp b/hardware/bioamp/bioamp-v1.5/media/connections.webp deleted file mode 100644 index b10f2c56..00000000 Binary files a/hardware/bioamp/bioamp-v1.5/media/connections.webp and /dev/null differ diff --git a/hardware/bioamp/bioamp-v1.5/media/emg-in-audacity.png b/hardware/bioamp/bioamp-v1.5/media/emg-in-audacity.png new file mode 100644 index 00000000..5779e7a9 Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/emg-in-audacity.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/emg-in-laptop.png b/hardware/bioamp/bioamp-v1.5/media/emg-in-laptop.png new file mode 100644 index 00000000..9d568102 Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/emg-in-laptop.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/emg-in-mobile-2.png b/hardware/bioamp/bioamp-v1.5/media/emg-in-mobile-2.png new file mode 100644 index 00000000..d14d6a0f Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/emg-in-mobile-2.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/emg-in-mobile.png b/hardware/bioamp/bioamp-v1.5/media/emg-in-mobile.png new file mode 100644 index 00000000..f0be353f Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/emg-in-mobile.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/kit-contents.png b/hardware/bioamp/bioamp-v1.5/media/kit-contents.png new file mode 100644 index 00000000..a644555c Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/kit-contents.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/listening-emg-2.png b/hardware/bioamp/bioamp-v1.5/media/listening-emg-2.png new file mode 100644 index 00000000..af97b4e8 Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/listening-emg-2.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/listening-emg-3.png b/hardware/bioamp/bioamp-v1.5/media/listening-emg-3.png new file mode 100644 index 00000000..edc4deea Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/listening-emg-3.png differ diff --git a/hardware/bioamp/bioamp-v1.5/media/listening-emg.png b/hardware/bioamp/bioamp-v1.5/media/listening-emg.png new file mode 100644 index 00000000..ac733f68 Binary files /dev/null and b/hardware/bioamp/bioamp-v1.5/media/listening-emg.png differ diff --git a/hardware/bioamp/muscle-bioamp-biscute/index.rst b/hardware/bioamp/muscle-bioamp-biscute/index.rst index 3c994de8..81f17f71 100644 --- a/hardware/bioamp/muscle-bioamp-biscute/index.rst +++ b/hardware/bioamp/muscle-bioamp-biscute/index.rst @@ -3,15 +3,12 @@ Muscle BioAmp Biscute ###################### -Most affordable DIY Electromyography (EMG) sensor - Overview ********* -Muscle BioAmp BisCute is an ultra-affordable DIY ElectroMyography (EMG) sensor that allows you to create a -Human-Computer Interface (HCI) with ease and in the process of building your own BisCute, you learn what goes -into making a functional biopotential amplifier that can be used for amplifying sub mV signals created by muscles -inside your body to a level a microcontroller unit (MCU) can understand. To record the EMG signals you can use any -standalone ADC like ADS1115 or any microcontroller development board with an ADC of your choice like Arduino UNO/Nano. +Muscle BioAmp BisCute is the most affordable DIY ElectroMyography (EMG) sensor in the world that allows you to create a +Human-Computer Interface (HCI) projects with ease. In the process of building your own BisCute, you learn what goes +into making a functional biopotential amplifier that can be used for amplifying sub mV signals generated by muscles +inside your body to a level a microcontroller unit (MCU) can understand. .. figure:: media/Muscle_BioAmp_BisCute.* :width: 800 @@ -21,29 +18,27 @@ standalone ADC like ADS1115 or any microcontroller development board with an ADC Features & Specifications *************************** -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Minimum Input Voltage | 3.3-30 V | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Input Impedance | 10^11 ohm | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Fixed Gain | x2420 | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Bandpass filter | 72 – 720 Hz | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Compatible Hardware | Any development board with an ADC (Arduino UNO & Nano, Espressif ESP32, Adafruit QtPy, STM32 Blue Pill, BeagleBone Black, Raspberry Pi Pico, to name just a few) | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| BioPotentials | EMG (Electromyography) | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| No. of channels | 1 | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Electrodes | 3 (Positive, Negative, and Reference) | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Dimensions | 3.0 x 4.5 cm | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Open Source | Hardware + Software | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ - - ++-----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Minimum Input Voltage | 3.3-30 V | ++-----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Input Impedance | 10^11 ohm | ++-----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Fixed Gain | x2420 | ++-----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Bandpass filter | 72 – 720 Hz | ++-----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Compatible Hardware | Any development board with an ADC (Arduino UNO & Nano, Adafruit QtPy, STM32 Blue Pill, BeagleBone Black, Raspberry Pi Pico, to name just a few) or any standalone ADC of your choice | ++-----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| BioPotentials | EMG (Electromyography) | ++-----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| No. of channels | 1 | ++-----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Electrodes | 3 (Positive, Negative, and Reference) | ++-----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Dimensions | 3.0 x 4.5 cm | ++-----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Open Source | Hardware + Software | ++-----------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ Hardware ********** @@ -72,16 +67,36 @@ Images below shows a quick overview of the hardware design. .. figure:: media/assembled.* :align: center + **Assembled PCB** + .. figure:: media/dimensions.* :align: center + **PCB Layout** + .. figure:: media/schematic.* :align: center -Assemblying the kit + **Schematic Diagram** + +Contents of the kit +******************** + +.. image:: media/kit-contents.* + +Software requirements +********************** + +- Before you start using the kit, please download `Arduino IDE v1.8.19 (legacy IDE) `_. Using this you'll be able to upload the arduino sketches on your development board and visualise the data on your laptop. + +.. image:: ../../../kits/diy-neuroscience/basic/media/arduino-ide.png + +Assembling the kit ******************** -You can get your own Muscle BioAmp BisCute bag of parts from `our store `_ or `Tindie `_ and for assembling your Biscute you can either take a look at `this interactive BOM `_ or the step by step guide below. +You can get Muscle BioAmp BisCute from our `online stores `_ (shipping worldwide) and for assembling the BisCute you can either take a look at `this interactive BOM `_ or the step by step guide given below. + +**Note:** Follow the highlighted yellow shapes to assemble your Muscle BioAmp BisCute! .. grid:: 1 1 3 3 :margin: 2 2 0 0 @@ -178,30 +193,93 @@ You can get your own Muscle BioAmp BisCute bag of parts from `our store `_ to assemble your BisCute. +Still can't figure out the assembly? You can watch the video below to assemble your Biscute. + +.. youtube:: 2dzW6pVT1L8 + :width: 100% + :align: center + +Using the kit +**************** -Connecting with Arduino -************************* +Step 1: Connect Arduino UNO R3 +================================= -After assembling the kit, you can pair it with any development board with an ADC (Arduino UNO & Nano, Espressif ESP32, -Adafruit QtPy, STM32 Blue Pill, BeagleBone Black, Raspberry Pi Pico, to name just a few) or any standalone ADC of your choice. +.. image:: media/arduino-biscute-connection.* -To measure the EMG signals, just connect BioAmp Cable v3 with the Muscle BioAmp BisCute as shown in the image below, and get started. +Connect VCC to either 5V or 3.3V, GND to GND, and OUT to Analog pin A0 of your Arduino UNO via jumper cables provided by us. If you are connecting OUT to any other analog pin, then you will have to change the INPUT PIN in the arduino sketch accordingly. -.. figure:: media/Electrode_Placement_Example.* +**Note:** For demonstration purposes we are showing connections of the sensor with Arduino UNO R3 but you can use any other development board or a standalone ADC of your choice. -Using the Sensor -******************* +.. warning:: Take precautions while connecting to power, if power pins (GND & VCC) are to be swapped, your sensor will be fried and it’ll become unusable (DIE). -.. youtube:: ujFsAE0E0nk +Step 3: Connecting electrode cable +======================================== + +.. image:: media/biscute-cable-connection.* + +Connect the BioAmp cable to Muscle BioAmp Biscute by inserting the cable end in the JST PH connector as shown above. + +Step 4: Skin Preparation +=============================================== + +Apply Nuprep Skin Preparation Gel on the skin surface where electrodes would be placed to remove dead skin cells and clean the skin from dirt. After rubbing the skin surface thoroughly, clean it with a wet wipe. + +For more information, please check out detailed step by step :ref:`skin-preparation` + +Step 5: Measuring EMG (ElectroMyoGraphy) +=============================================== + +We have 2 options to measure the EMG signals, either using the gel electrodes or using dry electrode based Muscle BioAmp Band. You can try both of them one by one. + +- **Using gel electrodes:** + +1. Connect the BioAmp cable to gel electrodes, +2. Peel the plastic backing from electrodes +3. Place the IN+ and IN- cables on the arm near the ulnar nerve & REF (reference) at the back of your hand as shown in the connection diagram. + +.. image:: media/biscute-emg.* + +- **Using Muscle BioAmp Band:** + +1. Connect the BioAmp cable to Muscle BioAmp Band in a way such that IN+ and IN- are placed on the arm near the ulnar nerve & REF (reference) on the far side of the band. +2. Now put a small drop of electrode gel between the skin and metallic part of BioAmp cable to get the best results. + + **Tutorial on how to use the band:** + +.. youtube:: xYZdw0aesa0 :align: center :width: 100% -Some project ideas -************************ +.. note:: In this demonstration we are recording EMG signals from the ulnar nerve, but you can record EMG from other areas as well (biceps, triceps, legs, jaw etc) as per your project requirements. Just make sure to place the IN+, IN- electrodes on the targeted muscle and REF on a bony part. + +**Uploading the code:** + +Connect your Arduino UNO to your laptop using the USB cable (Type A to Type B). Copy paste any one of the arduino sketches given below in Arduino IDE v1.8.19 that you downloaded earlier: + +EMG Filter: https://github.com/upsidedownlabs/Muscle-BioAmp-Arduino-Firmware/blob/main/2_EMGFilter/2_EMGFilter.ino -We have curated a playlist for you which consists some awesome project ideas for you to get started with your next HCI project. +EMG Envelope: https://github.com/upsidedownlabs/Muscle-BioAmp-Arduino-Firmware/blob/main/3_EMGEnvelope/3_EMGEnvelope.ino -.. .. youtube:: https://youtube.com/playlist?list=PLtkEloJ7UnkQIoz1HK4IXWujCB8hKdiKU&si=osloTX71TE7AJ3CF -.. :width: 100% -.. :align: center +Go to **"tools"** from the menu bar, select **"board"** option then select Arduino UNO. In the same menu, +select the COM port on which your Arduino Uno is connected. To find out the right COM port, +disconnect your board and reopen the menu. The entry that disappears should be the +right COM port. Now upload the code, & open the serial plotter from the tools menu to visualize +the EMG signals. + +After opening the serial plotter make sure to select the baud rate to 115200. + +.. warning:: Make sure your laptop is not connected to a charger and sit 5m away from any AC appliances for best signal acquisition. + +**Visualizing the EMG signals** + +Now flex your arm to visualize the muscle signals in real time on your laptop. + +.. image:: media/using-biscute.* + + +**Video tutorial:** + +.. youtube:: ujFsAE0E0nk + :align: center + :width: 100% diff --git a/hardware/bioamp/muscle-bioamp-biscute/media/arduino-biscute-connection.png b/hardware/bioamp/muscle-bioamp-biscute/media/arduino-biscute-connection.png new file mode 100644 index 00000000..32f60190 Binary files /dev/null and b/hardware/bioamp/muscle-bioamp-biscute/media/arduino-biscute-connection.png differ diff --git a/hardware/bioamp/muscle-bioamp-biscute/media/biscute-cable-connection.png b/hardware/bioamp/muscle-bioamp-biscute/media/biscute-cable-connection.png new file mode 100644 index 00000000..e5148cff Binary files /dev/null and b/hardware/bioamp/muscle-bioamp-biscute/media/biscute-cable-connection.png differ diff --git a/hardware/bioamp/muscle-bioamp-biscute/media/biscute-emg.png b/hardware/bioamp/muscle-bioamp-biscute/media/biscute-emg.png new file mode 100644 index 00000000..e4b69384 Binary files /dev/null and b/hardware/bioamp/muscle-bioamp-biscute/media/biscute-emg.png differ diff --git a/hardware/bioamp/muscle-bioamp-biscute/media/kit-contents.png b/hardware/bioamp/muscle-bioamp-biscute/media/kit-contents.png new file mode 100644 index 00000000..89e8428a Binary files /dev/null and b/hardware/bioamp/muscle-bioamp-biscute/media/kit-contents.png differ diff --git a/hardware/bioamp/muscle-bioamp-biscute/media/using-biscute.png b/hardware/bioamp/muscle-bioamp-biscute/media/using-biscute.png new file mode 100644 index 00000000..6eb9eb47 Binary files /dev/null and b/hardware/bioamp/muscle-bioamp-biscute/media/using-biscute.png differ diff --git a/hardware/bioamp/muscle-bioamp-candy/index.rst b/hardware/bioamp/muscle-bioamp-candy/index.rst index 533358af..341e1a6c 100644 --- a/hardware/bioamp/muscle-bioamp-candy/index.rst +++ b/hardware/bioamp/muscle-bioamp-candy/index.rst @@ -3,16 +3,12 @@ Muscle BioAmp Candy ##################### -Candy-size affordable muscle sensor for precise EMG sensing. - Overview ********* -A candy-size single-channel ElectroMyography (EMG) sensor for precise recording of muscle signals -at an affordable cost. It is an SMD version of Muscle BioAmp BisCute that can be used to make -amazing Human-Computer Interface (HCI) projects. To record the EMG signals you can use any standalone -ADC like ADS1115 or any microcontroller development board with an ADC of your choice like Arduino -UNO/Nano. +A candy-size single-channel ElectroMyography (EMG) sensor for recording of muscle signals +at an affordable cost. It is an SMD version of :ref:`muscle_bioamp-biscute` that can be used to make +amazing Human-Computer Interface (HCI) projects. .. figure:: media/Muscle-BioAmp-Candy-front.* :width: 800 @@ -31,7 +27,7 @@ Features & Specifications +-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Bandpass filter | 72 – 720 Hz | +-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Compatible Hardware | Any development board with an ADC (Arduino UNO & Nano, Espressif ESP32, Adafruit QtPy, STM32 Blue Pill, BeagleBone Black, Raspberry Pi Pico, to name just a few) | +| Compatible Hardware | Any development board with an ADC (Arduino UNO & Nano, Adafruit QtPy, STM32 Blue Pill, BeagleBone Black, Raspberry Pi Pico, to name just a few) | +-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | BioPotentials | EMG (Electromyography) | +-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ @@ -75,33 +71,108 @@ Images below shows a quick overview of the hardware design. :align: center .. figure:: media/dimensions.* :align: center + + **PCB Layout** + .. figure:: media/schematic.* :align: center -Connecting with Arduino -**************************** + **Schematic Diagram** -To get started, you can pair Muscle BioAmp Candy with any development board with an ADC (Arduino UNO & Nano, Espressif ESP32, -Adafruit QtPy, STM32 Blue Pill, BeagleBone Black, Raspberry Pi Pico, to name just a few) or any standalone ADC of your choice. +Contents of the kit +******************** -To measure the EMG signals, connect BioAmp Cable v3 with your muscle sensor as shown in the image below: +.. image:: media/kit-contents.* -.. figure:: media/Muscle-BioAmp-Candy-Arduino-EMG-Recording.* +Software requirements +********************** -**CAUTION:** Make sure to follow the above diagram while making the connections between your Muscle BioAmp Candy & Arduino (or any other ADC of your choice), especially the GND and VCC else it may damage the muscle sensor. +- Before you start using the kit, please download `Arduino IDE v1.8.19 (legacy IDE) `_. Using this you'll be able to upload the arduino sketches on your development board and visualise the data on your laptop. + +.. image:: ../../../kits/diy-neuroscience/basic/media/arduino-ide.png -Using the sensor -****************** +Using the kit +**************** -.. youtube:: lPX2TGBcHOA - :width: 100% +Step 1: Connect Arduino UNO R3 +================================= + +.. image:: media/arduino-candy-connection.* + +Connect `VCC` to either `5V` or `3.3V`, `GND` to `GND`, and `OUT` to `Analog pin A0` of your Arduino UNO via jumper cables provided by us. If you are connecting OUT to any other analog pin, then you will have to change the `INPUT PIN` macro in the example arduino sketch accordingly. + +.. note:: For demonstration purposes we are showing connections of the sensor with Arduino UNO R3 but you can use any other development board or a standalone ADC of your choice. + +.. warning:: Take precautions while connecting to power, if power pins (GND & VCC) are to be swapped, your sensor will be fried and it’ll become unusable (DIE). + +Step 3: Connecting electrode cable +======================================== + +.. image:: media/candy-cable-connection.* + +Connect the BioAmp cable to Muscle BioAmp Candy by inserting the cable end in the JST PH connector as shown above. + +Step 4: Skin Preparation +=============================================== + +Apply Nuprep Skin Preparation Gel on the skin surface where electrodes would be placed to remove dead skin cells and clean the skin from dirt. After rubbing the skin surface thoroughly, clean it with an alcohol wipe or a wet wipe. + +For more information, please check out detailed step by step :ref:`skin-preparation` + +Step 5: Measuring EMG (ElectroMyoGraphy) +=============================================== + +We have 2 options to measure the EMG signals, either using the gel electrodes or using dry electrode based Muscle BioAmp Band. You can try both of them one by one. + +- **Using gel electrodes:** + +1. Connect the BioAmp cable to gel electrodes, +2. Peel the plastic backing from electrodes +3. Place the IN+ and IN- cables on the arm near the ulnar nerve & REF (reference) at the back of your hand as shown in the connection diagram. + +.. image:: media/candy-emg.* + +- **Using Muscle BioAmp Band:** + +1. Connect the BioAmp cable to Muscle BioAmp Band in a way such that IN+ and IN- are placed on the arm near the ulnar nerve & REF (reference) on the far side of the band. +2. Now put a small drop of electrode gel between the skin and metallic part of BioAmp cable to get the best results. + + **Tutorial on how to use the band:** + +.. youtube:: xYZdw0aesa0 :align: center + :width: 100% -Some project ideas -******************** +.. note:: In this demonstration we are recording EMG signals from the ulnar nerve, but you can record EMG from other areas as well (biceps, triceps, legs, jaw etc) as per your project requirements. Just make sure to place the IN+, IN- electrodes on the targeted muscle and REF on a bony part. + +**Uploading the code:** + +Connect your Arduino UNO R3 to your laptop using the USB cable (Type A to Type B). Copy paste any one of the arduino sketches given below in Arduino IDE v1.8.19 that you downloaded earlier: + +EMG Filter: https://github.com/upsidedownlabs/Muscle-BioAmp-Arduino-Firmware/blob/main/2_EMGFilter/2_EMGFilter.ino + +EMG Envelope: https://github.com/upsidedownlabs/Muscle-BioAmp-Arduino-Firmware/blob/main/3_EMGEnvelope/3_EMGEnvelope.ino + +Go to ``tools`` from the menu bar, select ``board`` option then select Arduino UNO. In the same menu, +select the COM port on which your Arduino Uno is connected. To find out the right COM port, +disconnect your board and reopen the menu. The entry that disappears should be the +right COM port. Now upload the code, & open the serial plotter from the tools menu to visualize +the EMG signals. + +After opening the serial plotter make sure to select the baud rate to 115200. + +.. warning:: Make sure your laptop is not connected to a charger and sit 5m away from any AC appliances for best signal acquisition. + +**Visualizing the EMG signals** + +Now flex your arm to visualize the muscle signals in real time on your laptop. + +.. image:: media/using-candy.* + +**Video tutorial:** + +.. youtube:: lPX2TGBcHOA + :align: center + :width: 100% -We have curated a playlist for you which consists some awesome project ideas for you to get started with your next HCI project. -.. .. youtube:: https://youtube.com/playlist?list=PLtkEloJ7UnkQIoz1HK4IXWujCB8hKdiKU&si=osloTX71TE7AJ3CF -.. :width: 100% -.. :align: center diff --git a/hardware/bioamp/muscle-bioamp-candy/media/arduino-candy-connection.png b/hardware/bioamp/muscle-bioamp-candy/media/arduino-candy-connection.png new file mode 100644 index 00000000..d7feb411 Binary files /dev/null and b/hardware/bioamp/muscle-bioamp-candy/media/arduino-candy-connection.png differ diff --git a/hardware/bioamp/muscle-bioamp-candy/media/candy-cable-connection.png b/hardware/bioamp/muscle-bioamp-candy/media/candy-cable-connection.png new file mode 100644 index 00000000..2225b220 Binary files /dev/null and b/hardware/bioamp/muscle-bioamp-candy/media/candy-cable-connection.png differ diff --git a/hardware/bioamp/muscle-bioamp-candy/media/candy-emg.png b/hardware/bioamp/muscle-bioamp-candy/media/candy-emg.png new file mode 100644 index 00000000..7884b6b9 Binary files /dev/null and b/hardware/bioamp/muscle-bioamp-candy/media/candy-emg.png differ diff --git a/hardware/bioamp/muscle-bioamp-candy/media/kit-contents.png b/hardware/bioamp/muscle-bioamp-candy/media/kit-contents.png new file mode 100644 index 00000000..5dbb5ad0 Binary files /dev/null and b/hardware/bioamp/muscle-bioamp-candy/media/kit-contents.png differ diff --git a/hardware/bioamp/muscle-bioamp-candy/media/using-candy.png b/hardware/bioamp/muscle-bioamp-candy/media/using-candy.png new file mode 100644 index 00000000..7a5107c7 Binary files /dev/null and b/hardware/bioamp/muscle-bioamp-candy/media/using-candy.png differ diff --git a/hardware/bioamp/muscle-bioamp-patchy/index.rst b/hardware/bioamp/muscle-bioamp-patchy/index.rst index f6e1d8df..01832b46 100644 --- a/hardware/bioamp/muscle-bioamp-patchy/index.rst +++ b/hardware/bioamp/muscle-bioamp-patchy/index.rst @@ -3,8 +3,6 @@ Muscle BioAmp Patchy ##################### -Wearable ElectroMyoGraphy (EMG) sensor - Overview ********** @@ -18,29 +16,29 @@ based Human-Computer Interface (HCI). Features & Specifications ************************** -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Minimum Input Voltage | 4.5 V | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Input Impedance | 10^12 ohm | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Fixed Gain | x2420 | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Bandpass filter | 72 – 720 Hz | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Wearable | Yes | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Compatible Hardware | Any development board with an ADC (Arduino UNO & Nano, Espressif ESP32, Adafruit QtPy, STM32 Blue Pill, BeagleBone Black, Raspberry Pi Pico, to name just a few) | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| BioPotentials | EMG (Electromyography) | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| No. of channels | 1 | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Electrodes | 3 (Positive, Negative, and Reference) | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Dimensions | 47 x 14 mm | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ -| Open Source | Hardware + Software | -+-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------+ ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Operating Voltage | 5 V | ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Input Impedance | 10^12 ohm | ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Fixed Gain | x2420 | ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Bandpass filter | 72 – 720 Hz | ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Wearable | Yes | ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Compatible Hardware | Any development board with an ADC (Arduino UNO & Nano, Adafruit QtPy, STM32 Blue Pill, BeagleBone Black, Raspberry Pi Pico, to name just a few) or a standalone ADC of your choice | ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| BioPotentials | EMG (Electromyography) | ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| No. of channels | 1 | ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Electrodes | 3 (Positive, Negative, and Reference) | ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Dimensions | 4.7 x 1.4 cm | ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ +| Open Source | Hardware + Software | ++-----------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ .. youtube:: qRKU_HvapDE :align: center @@ -72,46 +70,96 @@ Images below shows a quick overview of the hardware design. .. figure:: media/Muscle-BioAmp-Patchy-Assembled-Front.* :align: center + .. figure:: media/Muscle-BioAmp-Patchy-Assembled-Back.* :align: center -Connecting with Arduino -************************ +Contents of the kit +******************** -To get started, you can pair Muscle BioAmp Patchy with any development board with an ADC (Arduino UNO & Nano, Espressif ESP32, -Adafruit QtPy, STM32 Blue Pill, BeagleBone Black, Raspberry Pi Pico, to name just a few) or any standalone ADC of your choice. +.. todo:: Add image here -For the connections and electrode placements, you can follow the diagram given below: +Software requirements +********************** -.. figure:: media/Patchy-Arduino-Connections.* - :width: 100% - :align: center +Before you start using the kit, please download `Arduino IDE v1.8.19 (legacy IDE) `_. Using this you'll be able to upload the arduino sketches on your development board and visualise the data on your laptop. + +.. image:: ../../../kits/diy-neuroscience/basic/media/arduino-ide.png -Demonstration +Using the kit **************** -After snapping the Patchy onto gel electrodes(placed on our targeted muscle), you can connect your patchy to the arduino via -jumper cables, arduino to your battery operated laptop, and start recording your EMG easily. Follow the steps shown in the video -below for the demonstration. +likhdenge -.. youtube:: 4dnCX3U7LS8 - :width: 100% - :align: center +Step 1: Connect reference cable +================================= -Some project ideas -********************* +.. todo:: Add image here -.. grid:: 1 1 1 1 - :margin: 2 2 0 0 - :gutter: 2 +Connect the reference cable to the Muscle BioAmp Patchy as shown in the diagram. - .. grid-item:: +Step 2: Connecting Muscle BioAmp Patchy to Gel Electrodes +============================================================ - .. card:: - - Recording and Visualizing Muscle Signals (EMG) Using Muscle BioAmp Patchy (wearable Muscle Sensor) - ^^^^ +.. todo:: Add image here + +Connect the Muscle BioAmp Patchy to gel electrodes (Don't peel the plastic backing from the electrodes at this moment). + +Step 3: Skin Preparation +============================= + +Apply Nuprep Skin Preparation Gel on the skin surface where electrodes would be placed to remove dead skin cells and clean the skin from dirt. After rubbing the skin surface thoroughly, clean it with a wet wipe. + +For more information, please check out detailed step by step :ref:`skin-preparation`. + +Step 4: Electrode Placements +============================== + +.. todo:: Add image here + +Now peel off the plastic backing from the gel electrodes and place the Muscle BioAmp Patchy on the targeted muscle and the reference on the bony part of your elbow as shown in the diagram. + +.. note:: In this demonstration we are recording EMG signals from the ulnar nerve, but you can record EMG from other areas as well (biceps, triceps, legs, jaw etc) as per your project requirements. Just make sure to place the IN+, IN- electrodes on the targeted muscle and REF on a bony part. - .. youtube:: 4dnCX3U7LS8 - :align: center - :width: 100% \ No newline at end of file +Step 5: Connect Arduino UNO R3 +================================= + +.. todo:: Add image here + +Connect VCC to 5V, GND to GND, and OUT to Analog pin A0 of your Arduino UNO via jumper cables provided by us. If you are connecting OUT to any other analog pin, then you will have to change the INPUT PIN in the arduino sketch accordingly. + +**Note:** For demonstration purposes we are showing connections of the sensor with Arduino UNO R3 but you can use any other development board or a standalone ADC of your choice. + +Step 6: Upload the code +=============================================== + +.. todo:: Add image here + +Connect your Arduino UNO to your laptop using the USB cable (Type A to Type B). Copy paste any one of the arduino sketches given below in Arduino IDE v1.8.19 that you downloaded earlier: + +EMG Filter: https://github.com/upsidedownlabs/Muscle-BioAmp-Arduino-Firmware/blob/main/2_EMGFilter/2_EMGFilter.ino + +EMG Envelope: https://github.com/upsidedownlabs/Muscle-BioAmp-Arduino-Firmware/blob/main/3_EMGEnvelope/3_EMGEnvelope.ino + +Go to **"tools"** from the menu bar, select **"board"** option then select Arduino UNO. In the same menu, +select the COM port on which your Arduino Uno is connected. To find out the right COM port, +disconnect your board and reopen the menu. The entry that disappears should be the +right COM port. Now upload the code, & open the serial plotter from the tools menu to visualize +the EMG signals. + +After opening the serial plotter make sure to select the baud rate to 115200. + +.. warning:: Make sure your laptop is not connected to a charger and sit 5m away from any AC appliances for best signal acquisition. + +Step 7: Visualizing the EMG signals +====================================== + +Now flex your arm to visualize the muscle signals in real time on your laptop. + +.. todo:: Add image here + +**Video tutorial:** + +.. youtube:: 4dnCX3U7LS8 + :align: center + :width: 100% \ No newline at end of file diff --git a/index.rst b/index.rst index fb86ae50..baa3f44c 100644 --- a/index.rst +++ b/index.rst @@ -26,7 +26,11 @@ or Brain-Computer Interface (BCI) projects with ease. Overview of BioAmp Hardware ****************************** -Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. +Discover our open-source bioamp hardware, designed to help you easily record biopotential signals +from the body making it accessible to explore the field of neuroscience & electrophysiology. +We offer easy to follow guides that walk you through the setup process step by step, making it +simple for beginners to get started. You can also find software examples on our github profile +that you can use with our hardware. .. grid:: 1 1 4 4 :margin: 4 4 0 0 @@ -132,4 +136,11 @@ Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor i :maxdepth: 1 :caption: Kits - kits/index \ No newline at end of file + kits/index + +.. toctree:: + :hidden: + :maxdepth: 1 + :caption: Guides + + guides/index \ No newline at end of file