neurosity 1.0.1

Official Neurosity Python SDK

Neurosity Python SDK 🤯

Welcome to the official Neurosity Python SDK. This library is compatible with Python 3.

Documentation

• Getting Started
• Authentication
• Brainwaves
• Signal Quality
• Accelerometer
• Calm
• Focus
• Kinesis
• Device Info
• Device Status
• Device Settings

Getting Started

To get started with the Neurosity SDK, you'll need:

• Your device ID
• Your Neurosity account email
• Your Neurosity account password

To get your 32-character Neurosity device ID, use the Neurosity mobile app available for iOS and Android. Go to Settings -> Device Info.

💡 Never hardcode your email and password directly in your Python code. Instead, create a .env file in the root of your project and add:

NEUROSITY_EMAIL=your email here
NEUROSITY_PASSWORD=your password here
NEUROSITY_DEVICE_ID=your device id here

Authentication

We take data privacy very seriously at Neurosity. This is why we have designed the Neurosity OS to require authentication and authorization for streaming data.

When you sign up for an account on the Neurosity mobile app or console.neurosity.co and claim a device you have three new important items: deviceId, email, and password. If your device is not added to your Neurosity account, you will not be able to authenticate with it.

from neurosity import neurosity_sdk
from dotenv import load_dotenv
import os

load_dotenv()

neurosity = neurosity_sdk({
    "device_id": os.getenv("NEUROSITY_DEVICE_ID"),
})

neurosity.login({
    "email": os.getenv("NEUROSITY_EMAIL"),
    "password": os.getenv("NEUROSITY_PASSWORD")
})

Brainwaves

The brainwaves API is what we always wished for when it came to inventing the future: an easy way to get lossless brainwaves. Sometimes we wanted to manipulate the raw data and other times we wanted to analyze the power in each frequency bin. With brainwaves, our goal is to enable new APIs and powerful programs to be built. We expect that someone working with the brainwaves API has a bit of experience working with EEG data or a strong desire to learn.

Sampling Rate

The sampling rate will vary depending on the model of your device.

• Crown -> 256Hz
• Notion 2 -> 250Hz
• Notion 1 -> 250Hz

A sampling rate of 250Hz means the data contains 250 samples per second.

Metrics

There are four brainwaves metrics:

• raw
• rawUnfiltered
• psd
• powerByBand

Raw

The raw brainwaves parameter emits events of 16 samples for Crown and 25 for Notion 1 and 2. We call these groups of samples Epochs.

from neurosity import neurosity_sdk
from dotenv import load_dotenv
import os

load_dotenv()

neurosity = neurosity_sdk({
    "device_id": os.getenv("NEUROSITY_DEVICE_ID"),
})

neurosity.login({
    "email": os.getenv("NEUROSITY_EMAIL"),
    "password": os.getenv("NEUROSITY_PASSWORD")
})

def callback(data):
    print("data", data)

unsubscribe = neurosity.brainwaves_raw(callback)

The code above will output new epochs of 16 samples approximately every 62.5ms (see the data property). Here's an example of 1 event:

{
  label: 'raw',
  data: [
    [
        4.457080580994754,   4.851055413759571,
       2.7564288713972513, -0.5027899221971044,
       -2.738312652550817, -1.4222768509324195,
       3.7224881424127774,  10.026623768677425,
       13.387940036943913,   10.26958811063134,
      0.40214439930276313,  -10.90689891807639,
       -16.32031531728357,  -13.21110292437311,
       -4.346339152926361,   5.098462672115731
    ],
    [
       1.5414324608328491,   1.352550875105505,
       0.6428681224481866,  0.3647622839064659,
        1.106405158893898,    3.33535030106603,
        6.439447624257519,   8.453867322080404,
        7.755719477492251,  3.8854840128526726,
       -2.468418708869076,  -8.666576946507902,
      -11.279063910921169,   -9.32163910159064,
      -4.6549399985975555, 0.22830321396497988
    ],
    [
       6.2342484244030345,   5.845156697083605,
       3.8819440822537112,   1.452431055127227,
      -0.5878084105038387, -0.7746780077287738,
       1.8154316196085094,   6.074662974618359,
        9.322430831260775,   8.910160063433407,
       3.5874046672323043,  -4.554187036159066,
        -10.5813322711113, -11.267696723897789,
       -6.818338145262863,  0.6177864457464617
    ],
    [
      -0.03815349843983071, -0.3068494494059635,
       -2.2075671327003255,  -3.776991642244289,
        -3.708252867923816, -1.2505125622236009,
        3.2487010722502587,   7.931368090269462,
        10.511652358411597,   9.297157466389192,
         4.118487064147775,  -2.970255165231891,
        -8.603434324519576, -10.495401970387743,
        -8.913968355428027,  -5.576315727924461
    ],
    [
      0.4087987173450871, 1.9781686568610883,
      2.4009012312957907, 2.3444623435812657,
       2.017191526524595,  2.021880260660721,
       2.982232584662937,  4.815498699074363,
      6.7093290202119835,  7.201157697368587,
       5.116090777276677, 0.6675802498302112,
      -4.274751517565271, -7.425134286013973,
      -7.838523284654038, -5.779233789541195
    ],
    [
       5.2762700288652935,   6.831919893235682,
        6.468141714172544,   5.147606136919876,
        4.117592132996127,   4.788874365858218,
        7.116782027901927,    9.33554991116211,
        9.233167024756574,   5.130966403760715,
      -2.8162586562506586,  -11.22160733448037,
      -15.538132012307846, -13.939535958562475,
        -7.83032193319038, -0.5139467086717411
    ],
    [
      -1.0706877843314648,  1.6368537502872518,
        2.022946637839514,   0.940183871324582,
      -0.2837858448921892,  0.3170369574339986,
        3.778225479624427,   8.805770181583913,
       12.446309024446833,  11.648691354684154,
        5.113617281379798,  -4.345975093596486,
       -11.05811376487729, -11.719256256733335,
       -7.336025188705039,  -1.276174494743728
    ],
    [
        7.286685329938873,    8.201842402616839,
        5.517128178717949,   1.2864058791627557,
      -1.5101995538838966, -0.19819079250913285,
        5.195437241439434,   11.512563735679437,
       14.388370410845482,   10.711863367882668,
       0.8428177428317678,  -10.126402143316568,
       -15.75585412249734,  -13.887360795976967,
       -6.836657125920971,   1.1706118773123455
    ]
  ],
  info: {
    channelNames: [
      'CP3', 'C3',
      'F5',  'PO3',
      'PO4', 'F6',
      'C4',  'CP4'
    ],
    notchFrequency: '60Hz',
    samplingRate: 256,
    startTime: 1628194299499
  }
}

Epochs are pre-filtered on the device's Operating System to give you the cleanest data possible with maximum performance. These filters include:

• Notch of 50Hz or 60Hz and a bandwidth of 1.
• Band Pass with cutoff between 2Hz and 45Hz.

The order of these filters is set to 2, and the characteristic used is butterworth.

To apply your own filters, you can use the brainwaves_raw_unfiltered SDK method (see next section) and use a library like MNE or Brainflow for fine-grained filter customization.

Unsubscribe from brainwaves

To unsubscribe from brainwaves and stop the emission of data events, you can do the following:

unsubscribe = neurosity.brainwaves_raw(callback)

timer.sleep(5)

unsubscribe()

This last example will emit data for 5 seconds.

Raw Unfiltered

The unfiltered raw data follows the same shape as brainwaves_raw data shape, just without signal filters applied. This data comes directly from the analog to digital converter, and does not include any processing. We only recommend using the unfiltered data for advanced scenarios.

Note that unfiltered raw data will include environmental noise in the signal, as well as DC drift, which is expected when working with EEG.

from neurosity import neurosity_sdk
from dotenv import load_dotenv
import os

load_dotenv()

neurosity = neurosity_sdk({
    "device_id": os.getenv("NEUROSITY_DEVICE_ID"),
})

neurosity.login({
    "email": os.getenv("NEUROSITY_EMAIL"),
    "password": os.getenv("NEUROSITY_PASSWORD")
})

def callback(data):
    print("data", data)

unsubscribe = neurosity.brainwaves_raw_unfiltered(callback)

The code above will output new epochs of 16 samples approximately every 62.5ms (see the data property).. Here's an example of 1 event:

{
  label: 'rawUnfiltered',
  data: [
    [
       1385.227003,   861.056247,
      -1835.167617, -1321.189256,
        999.860579,  1414.597195,
      -1246.623837, -1840.934367,
        406.757043,  1596.652153,
       -476.360375, -2080.790935,
       -222.556318,  1579.754234,
        355.660956, -2065.368232
    ],
    [
        774.21972,    286.25879,
      -951.714922,  -427.812387,
       650.368705,   611.744891,
      -746.391799,    -732.3102,
       398.039863,   770.732848,
       -412.99318,  -923.417614,
       122.174635,   823.840593,
         7.040799, -1004.286225
    ],
    [
       797.085555,   234.693316,
       -1099.4376,  -499.427375,
       669.613557,   598.870286,
      -859.916308,  -839.665628,
       420.369256,    765.63665,
      -515.185355,  -1057.66219,
       114.195062,   849.388636,
       -42.177742, -1155.495775
    ],
    [
       192.783795, -156.909245,
      -538.654687, -173.673053,
       210.084045,   13.008715,
      -496.208724, -314.354932,
       130.355373,  111.244632,
      -422.783244, -437.267174,
        43.116515,  179.573914,
      -267.952711, -512.234925
    ],
    [
       228.256013, -147.253292,
      -549.249414, -160.731394,
       234.961536,   16.093256,
      -506.803451, -304.162537,
       164.553542,   135.31746,
      -437.870671, -440.217605,
        71.212657,  207.267725,
       -272.04308, -523.634314
    ],
    [
        654.66024,   123.64985,
      -906.720861, -336.013773,
       578.217274,  426.337171,
      -751.487996, -629.246306,
       371.821267,  573.791629,
      -480.853076,  -827.26041,
       143.028812,  673.435705,
      -121.839358, -934.682893
    ],
    [
       764.362601,   258.095592,
      -996.172541,  -464.826875,
       639.975144,   603.094766,
      -765.368429,  -772.208063,
       384.829982,   745.453025,
       -437.46834,  -963.851919,
        93.139719,   807.747337,
       -22.865834, -1044.519364
    ],
    [
       1454.293893,   821.493659,
      -1599.334362,  -991.813951,
       1131.892333,  1364.506936,
      -1098.431772, -1494.459978,
        603.228876,  1578.815461,
        -421.71036, -1753.024956,
         21.860006,  1608.252708,
        343.859235, -1787.089015
    ]
  ],
  info: {
    channelNames: [
      'CP3', 'C3',
      'F5',  'PO3',
      'PO4', 'F6',
      'C4',  'CP4'
    ],
    samplingRate: 256,
    startTime: 1628194299499
  }
}

Power Spectral Density (PSD)

def callback(data):
    print("data", data)

unsubscribe = neurosity.brainwaves_psd(callback)

The code above will output new epochs 4 times a second. Every frequency label (e.g. alpha) contains the computed FFT (Fast Fourier transform) value per channel (see the psd property), as well as the frequency ranges (see the freqs property).

Here's an example of 1 event:

{
  label: 'psd',
  freqs: [
      0,   2,   4,   6,   8,  10,  12,  14,  16,  18,  20,  22,
     24,  26,  28,  30,  32,  34,  36,  38,  40,  42,  44,  46,
     48,  50,  52,  54,  56,  58,  60,  62,  64,  66,  68,  70,
     72,  74,  76,  78,  80,  82,  84,  86,  88,  90,  92,  94,
     96,  98, 100, 102, 104, 106, 108, 110, 112, 114, 116, 118,
    120, 122, 124, 126
  ],
  info: {
    notchFrequency: '60Hz',
    samplingRate: 256,
    startTime: 1628197298732
  },
  psd: [
    [
       98.63572869924877,  278.0499119981597,  396.9075453246308,
      330.93307599602673,  154.4437300666471,   127.381718447909,
      156.28589064508202,  90.27952532968459,  74.02596881179568,
      102.68745491461037,  77.40464372151173,  65.97947493071318,
       93.61333998578448,  70.03755439407374, 47.965913961348285,
       72.11457749610696,  60.14793608854482,  36.43407809513316,
        52.5321191045999, 45.400500672083176, 24.168757651016627,
        37.1839936941784, 35.105296424441036, 14.991272333196237,
      17.013079679743214, 22.931615422127962,   9.64319909169338,
        6.95610789706202,  10.48806813349181,   8.77101666889275,
        8.08687117576467,   7.88454615426007,   7.00857990702008,
       9.129752553805993,  7.500414008219254, 6.4966183674128635,
       7.833399187762861,  7.283708613586358,  5.616493707372124,
       7.336663052350952,  6.859592851990316,  6.153804860755752,
       6.618696201331677,  6.837180878389385, 5.7838083130648945,
       6.562155335152424,  6.093398492507891,  6.073406841367065,
      5.9593899491763205,   6.14611107916922,  5.674535238756583,
      6.0774035077156645,  5.656938723201682,  5.892346415487732,
        5.61605742554047,  5.842031463718972,  5.514410378848478,
       5.803658958523979,   5.47172273287992,  5.745739449800702,
       5.452574435173335,  5.724439426371041, 5.4273919360609035,
       5.707772456903569
    ],
    [
       705.0449351206108, 1355.4773207863375, 1795.4768676020658,
      1480.8269991044856,  879.7073135412625,  734.4677613113015,
       691.6145778964477,  482.9726329188916,  463.9458627254311,
       448.9185196251005,  325.3989179173811,  356.7357077059943,
      366.94089924861487, 288.75232488327777,  304.2605284381872,
       301.8930577524112,  237.4042509842181,   248.189270828571,
      244.01379638689255,  177.6237336667693, 172.43627544841166,
      176.69895192953885, 125.52722189861495, 105.15448954029884,
      106.56146701054848, 63.477588704077554, 33.251603187541896,
       42.84498288204394, 23.928294234593277,  9.767390485089537,
       15.03794181419898, 13.965161093202841, 20.844294981525614,
      12.007423569211078, 11.126393885153014, 20.104729878667776,
      12.319226156469027, 10.486815016962693, 17.143209506256614,
      11.132954923524995,  10.62728760663002, 14.463591856614492,
      10.925935011739528, 10.576245202399233, 12.869498809209984,
      10.551373735436435,  10.90154409382562, 11.496161902596342,
       10.59771747532043, 10.626533456022605, 10.982565808529692,
      10.292226858572462, 10.587506870484761, 10.420838952336604,
       10.33846013622055, 10.228524593265222, 10.333151489515492,
      10.081149399888313,  10.23400481786508, 10.046416371678554,
       10.14064797386651,  9.979626942208188, 10.115418833026341,
       9.962197147976129
    ],
    [
       929.0377610383296, 1793.6811181430987, 2377.6119679334947,
      1958.9102655269323, 1162.3055283149445,  979.7382233236812,
        921.065883147485,  640.2289218688652,  619.3532710184182,
       597.9752360209405, 433.84218492741303, 480.63827859906377,
       494.8759497888118,  388.5592867189369, 408.72806358233913,
       403.8696475504568,  318.0820897599802,  335.6971387951459,
       330.1749076377176,  240.2816149573954,  234.1828700249589,
       238.8172342465352, 168.40453177012395, 141.41297208524767,
       143.3763643586936,  84.85781325822384, 44.693260335642535,
       57.99822015732011,  32.12541610045182, 13.475265334606835,
      20.599681672533375,  19.01837044906831, 28.246044041267428,
      16.189180127175323,  15.41587209212851,  27.05517471975363,
      16.903913745426895,  14.33546383874818, 23.026090510272617,
       14.87036823280212,   14.6068129622348, 19.471383549994453,
       14.96633838574153, 14.387933483886725, 17.466586501671532,
      14.355984995364704, 14.919336874633427, 15.536030663642576,
      14.543171342633388, 14.399423945911408,  15.00275665739408,
      13.982397994287624, 14.474361692225106, 14.126311107434065,
      14.160828645624179,  13.86227555141294, 14.139642435285486,
      13.674442534649062, 14.000882290360456, 13.623523705584073,
      13.881719450096554, 13.533315732597867,  13.84382520692153,
      13.508775392377734
    ],
    [
       461.1411944745596,   865.879891899699, 1150.3297939965412,
       967.6717977233337,  599.5067484775997,  487.7449557189379,
       449.7148527252277, 324.75340665195546,  307.3960653823736,
      289.99356448521917,  218.9307327550319,   241.757776766985,
      249.28709256762335, 206.95217758165205,  213.8552238566172,
      208.04287443336904, 172.16085191285578,  177.8042520513104,
      170.76433578042244,  131.2290615556113, 127.75140879293434,
       125.8563352501824,  94.44550500099892,  81.32600662751962,
       76.33377477822643,  47.53219019300205, 29.403234515228505,
      29.734512582314988,  14.48430634759893,  4.338569856695335,
       7.956256668786119,  7.925904164095972, 12.763456529014546,
       5.823156703304557,  7.213304914646235,  12.53665043042392,
       6.064277734596193, 6.0142267398677225, 10.591216540020291,
       5.491335175417487,  5.995538415704912,   8.41366666249266,
       5.354337464315892,  5.684078918046329,  7.289586947844527,
       5.258040775750918,  5.927892633808341,  6.209024439918837,
      5.5308778688068525,  5.658218846438647,  5.937393602233365,
       5.337787715362042,  5.723456582324143,  5.491309810378187,
       5.517788579034077, 5.3995359451843115,  5.544753793342432,
       5.291402564159946,  5.499716204904763,  5.281561955171903,
      5.4342620388212115,  5.243854533655554,  5.426831995465968,
        5.23668469315059
    ],
    [
      485.28953220351815,  913.8215446531855, 1212.6893063853145,
      1017.6653954348992,  629.0590135927589,  513.8401411331691,
      473.94607162953474,  340.7794194629709,  323.4068209463424,
       304.6140613386581,  227.9530765749002, 253.44275369319936,
      261.96382482250846, 215.95821471824453,  223.2060790303756,
       217.5887331092368, 180.05264499052626,  186.6722683242584,
      178.86415942933493, 135.75616983861607,  132.7145908145038,
       131.7205674261096,  98.13621951582651,  84.22587059556682,
       79.69348482329639,  49.27415323250583, 29.885948066276374,
      31.018207012950032, 15.464201551787149,  4.696597650070098,
       8.680077668220271,  8.409519490488169, 13.587393841532371,
       6.264695355862866,  7.572139679407593,  13.17605643990251,
       6.652754348269858, 6.3465028991975325, 11.306345734652368,
       5.926439990819285,  6.470051702062516,  8.904949649675096,
        5.90150761172456,  6.060485555618185,  7.854198979433359,
       5.663406547398727, 6.4306283909466435,  6.623721018560318,
       6.041438452881903, 6.0442294631002795,  6.444444318919457,
       5.721040377425073,  6.213246144964029, 5.8753004744243755,
       6.002696003640614,  5.774903831465746,  6.026353504659674,
       5.663944879598529,  5.975725903093066,  5.652394044025673,
       5.907643067149823,  5.612177778683849,  5.898257253854689,
       5.604260960707902
    ],
    [
       703.9620591951088, 1348.1617601998341,  1787.817378338989,
      1480.9682977349662,  887.8732586924484,  741.7489045127593,
       696.4862482257432, 486.69267953812624, 464.30488178918847,
      448.10745320129496,  329.6131727268781,  364.1234842222161,
      375.17667115955084, 296.30580382389024,  307.6916385785675,
       303.4585158601969,  241.4840430193035,  253.3373457325428,
      248.14875370587004,  181.8456760420915, 176.16078095306457,
      178.58969714768043,  126.8938114163353,  106.7131960446341,
      106.86715498126117, 63.565099293832944,  33.94124074989405,
       42.78261882478681, 23.418093057211088,  9.598376452708248,
        14.8564635663729,  13.73158527388318, 20.632309203759725,
      11.571312623082235,  11.16199944105178,  19.71697966916169,
      12.151289348370563,  10.27332116826051,  16.93453042721219,
      10.734196078665759, 10.578983816474802,  14.17031151713728,
      10.741999390916682, 10.370828224990875, 12.669038407738478,
      10.290437631963869, 10.794986602960588, 11.204752776686476,
      10.481500894235385, 10.373479646590457, 10.845762801813153,
       10.04623630410688, 10.466118545780976,  10.16324823810254,
      10.225788013632457,  9.975974411529377,  10.21577779934349,
       9.834755780463283, 10.117741157508208,  9.799067226573825,
      10.029038431063377,  9.733625015451048, 10.002552468346979,
        9.71630020598175
    ],
    [
       753.3573854351718, 1451.3463711535637, 1925.4394750722938,
      1592.2479396735228,  950.1320711729846,  793.4163539564408,
        744.990261771651,  519.4611344925438,  498.6282329256233,
       480.4651411728872,  349.9224396629356, 388.08464608248545,
      400.41433150212987, 314.28699618071386,  328.3871848882801,
      325.21671199729667, 257.08898576447365,  270.0756790958063,
      265.56055695000117, 193.58422699465976,  187.3975181698473,
       190.5723885919431,  134.7850068920377, 113.55417235960783,
      114.65352872167782,  67.97249319078067,  36.07066166066659,
      46.193455592634194, 25.446519462818365, 10.645647869461468,
       16.33292205396577, 15.082694752225358, 22.479081487850554,
      12.660457753439347, 12.331655605615103, 21.469122245638992,
      13.259611882976637, 11.366093905761021,   18.4614508154199,
      11.778790555694387, 11.710458297806564, 15.485077358432786,
      11.805213571500564, 11.446226210170733, 13.887884653568616,
      11.334007371207884, 11.881804314077982,  12.30654501069072,
      11.528873716721828, 11.419099102496702, 11.910897138255397,
      11.059631088502826, 11.505557872713792, 11.178885987141047,
      11.242816922347224,  10.97697117415906, 11.227884136208706,
      10.822693801769324, 11.121177549665633, 10.782078947654583,
      11.024368739435461, 10.711151846144949, 10.995151378799578,
      10.691866595209362
    ],
    [
       367.4136193009799,  826.7329948628463, 1118.3539023221265,
        890.162220791093,  436.1682590608995,  391.4382314784865,
      417.04217210936963, 251.56740893464422,  238.5284921292077,
       267.6000138141995,   168.617128049186, 165.98870799455165,
      200.56943140232212, 129.37112302840023, 126.00839013852573,
      162.39587433692205, 109.20332945126022,  87.00867663058928,
      117.95711115144483,  83.29961985396704,  58.57022651921219,
       86.68284556964056,  63.23057486573713, 22.615043247176825,
       45.79353231282386,  39.94573246684187,  6.411920387449734,
      21.964845928081306, 21.959370088243116, 16.277025835788837,
      16.547064843486048, 15.715335138181468, 16.607457789253704,
      17.537478155658583, 13.336615276197591, 15.835823046176726,
      15.461292461652397, 13.730332854951738,  13.27865408978899,
      14.709605078820157,   12.9045807988706, 13.692853045756497,
      13.258453124525246, 13.287331440282053, 12.481768554519784,
      13.223425784019863, 12.187280042833416, 12.738723198131671,
      12.048047848217715,  12.49122466572343, 11.744286244430379,
      12.342663893673903, 11.552471648965968, 12.117055516659004,
      11.432033986591367, 11.965037193629023, 11.288502743059457,
      11.863912386218576, 11.190384199321217, 11.771734261131785,
      11.131137815008097,  11.71660417394918,  11.08761147894627,
      11.686948260719255
    ]
  ]
}

Please note this data is pre-filtered using the same filters describe under the raw data parameter: notch and band pass.

Power By Band

def callback(data):
    print("data", data)

unsubscribe = neurosity.brainwaves_power_by_band(callback)

The code above will output new epochs 4 times a second. Every frequency label (e.g. beta) contains an average power value per channel.

Here's an example of 1 event:

{
  label: 'powerByBand',
  data: {
    alpha: [
      0.4326838933650053,
      0.7011913998347046,
      1.3717684682104212,
      0.4043711439234614,
      0.4276277910286375,
      0.7343967679911133,
      0.4643529443786634,
      0.5012185195340365
    ],
    beta: [
      1.0473270376446968,
      0.6565360935142369,
      0.9905849734272257,
      0.4167252084581245,
      0.5812834985846604,
      0.9092642713573444,
      0.9963075404421067,
      1.0495665446734443
    ],
    delta: [
      0.46131690566460004,
      1.0030278320362798,
      0.8563781797682917,
      0.2911634678359473,
      0.5829804845703581,
      0.6714666592936025,
      0.37730719195446316,
      1.0851178080710937
    ],
    gamma: [
      0.22648773160183822,
      0.2171827127990081,
      0.2626969784220435,
      0.16349594919353772,
      0.17327387900192714,
      0.18990085940799623,
      0.22908540295491436,
      0.2537584109981627
    ],
    theta: [
      0.6434504807739541,
      0.936240328507981,
      0.8679595766147628,
      0.23662065697316603,
      0.6048174207817718,
      0.816112075629094,
      0.3367745804938397,
      1.1043745310136739
    ]
  }
}

Please note this data is pre-filtered using the same filters describe under the brainwaves_raw method: notch and band pass.

Adding Markers

def callback(data):
    print("data", data)

unsubscribe = neurosity.brainwaves_raw(callback)
time.sleep(2)
neurosity.add_marker("eyes-closed")
time.sleep(2)
unsubscribe()

Signal Quality

Standard deviation based signal quality metrics. Great signal happens when the standard deviation is between 1.5 and 10.

def callback(data):
    print("data", data)

unsubscribe = neurosity.signal_quality(callback)

Accelerometer

def callback(data):
    print("data", data)

unsubscribe = neurosity.accelerometer(callback)

Calm

Constantly fires and predicts user's calm level from passive cognitive state. Calm is a probability from 0.0 to 1.0. To get calm over 0.3 is significant. Calm will take up to 16 seconds to initialize. We normally take a longer rolling average of calm to produce brain processes over time, see how we do it in our flow walk through.

Things that can help increase the calm score are:

• Closing your eyes for 30 seconds or more
• Seating or standing still
• Breathing exercises
• Meditating

def callback(data):
    print("data", data)

    # { probability: 0.34, metric: "awareness", label: "calm", timestamp:  1569961321101 }
    # { probability: 0.41, metric: "awareness", label: "calm", timestamp:  1569961321105 }
    # { probability: 0.45, metric: "awareness", label: "calm", timestamp:  1569961321110 }

unsubscribe = neurosity.calm(callback)

Focus

Constantly fires and predicts user's focus level from passive cognitive state based on the gamma brainwave between 30 and 44 Hz. Focus is a probability from 0.0 to 1.0. To get focus over 0.3 is significant. Focus will take up to 16 seconds to fully initialize.

def callback(data):
    print("data", data)

    # { probability: 0.51, metric: "awareness", label: "focus", timestamp:  1569961321102 }
    # { probability: 0.56, metric: "awareness", label: "focus", timestamp:  1569961321106 }
    # { probability: 0.62, metric: "awareness", label: "focus", timestamp:  1569961321111 }

unsubscribe = neurosity.focus(callback)

Kinesis

The Kinesis API is based on the Motor Imagery BCI method. Fires when a user attempts to trigger a side effect from defined thoughts. E.g. motor imagery, etc.

Kinesis implements a spike detection algorithm over the predictions stream.

To train a Kinesis command, use console.neurosity.co and use the corresponding label for the Active classifier. Learn how to train a new command here.

def callback(data):
    print("data", data)
    # Switch light off/on
    light.togglePower()

    # { probability: 0.93, label: "rightArm", timestamp: 1569961321174, metric: "kinesis" }


unsubscribe = neurosity.kinesis("rightArm", callback)

Or:

def callback(data):
    print("data", data)
    # Launch drone
    drone.launch()

    # { probability: 0.92, label: "leftArm", timestamp: 1569961321191, type: "kinesis"  }

unsubscribe = neurosity.kinesis("leftArm", callback)

Device Info

info = neurosity.get_info()
print(info)

# { apiVersion: string,  channelNames: string[], channels: number,
#  deviceId: string, deviceNickname: string, manufacturer: string, model: string,
#  modelName: string, modelVersion: string, osVersion: string, samplingRate: number }

Device Status

Metrics:

• state: "online" | "offline" | "shuttingOff" | "updating" | "booting"
• sleepMode: boolean
• sleepModeReason: "updating" | "charging" | null
• charging: boolean
• battery: number
• lastHeartbeat: number
• ssid: string
• claimedBy: string

Get Status Once

status = neurosity.status_once()
print(status)

# { state: "online", charging: true, battery: 93, ... }

Stream Status

def callback(data):
    print("data", data)
    # { state: "online", charging: true, battery: 93, ... }


unsubscribe = neurosity.status(callback)

Device Settings

def callback(data):
    print("data", data)
    # { lsl: false, osc: false }

unsubscribe = neurosity.settings(callback)

Code of Conduct

This project has adopted a Code of Conduct. Contact [e-mail] with any additional questions or comments.

License

Copyright (c) Neurosity, Inc. All rights reserved.

Licensed under the MIT license.