muse-lsl

Python script to stream EEG data from the muse 2016 headset

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2Mentions

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787GitHub stars

REPOSITORY AT A GLANCE

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What it is

Python script to stream EEG data from the muse 2016 headset

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

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Mentions over time

HN mentions by week2 dated mentions

Observed mentions: 2021-09-07 21:08:00 UTC to 2022-01-10 09:09:58 UTC. Weeks start Monday, UTC.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges

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Period	Start (UTC)	End (exclusive, UTC)	Mentions	Comments
Sep 6	2021-09-06 00:00:00 UTC	2021-09-13 00:00:00 UTC	1	1
Sep 13	2021-09-13 00:00:00 UTC	2021-09-20 00:00:00 UTC	0	0
Sep 20	2021-09-20 00:00:00 UTC	2021-09-27 00:00:00 UTC	0	0
Sep 27	2021-09-27 00:00:00 UTC	2021-10-04 00:00:00 UTC	0	0
Oct 4	2021-10-04 00:00:00 UTC	2021-10-11 00:00:00 UTC	0	0
Oct 11	2021-10-11 00:00:00 UTC	2021-10-18 00:00:00 UTC	0	0
Oct 18	2021-10-18 00:00:00 UTC	2021-10-25 00:00:00 UTC	0	0
Oct 25	2021-10-25 00:00:00 UTC	2021-11-01 00:00:00 UTC	0	0
Nov 1	2021-11-01 00:00:00 UTC	2021-11-08 00:00:00 UTC	0	0
Nov 8	2021-11-08 00:00:00 UTC	2021-11-15 00:00:00 UTC	0	0
Nov 15	2021-11-15 00:00:00 UTC	2021-11-22 00:00:00 UTC	0	0
Nov 22	2021-11-22 00:00:00 UTC	2021-11-29 00:00:00 UTC	0	0
Nov 29	2021-11-29 00:00:00 UTC	2021-12-06 00:00:00 UTC	0	0
Dec 6	2021-12-06 00:00:00 UTC	2021-12-13 00:00:00 UTC	0	0
Dec 13	2021-12-13 00:00:00 UTC	2021-12-20 00:00:00 UTC	0	0
Dec 20	2021-12-20 00:00:00 UTC	2021-12-27 00:00:00 UTC	0	0
Dec 27	2021-12-27 00:00:00 UTC	2022-01-03 00:00:00 UTC	0	0
Jan 3	2022-01-03 00:00:00 UTC	2022-01-10 00:00:00 UTC	0	0
Jan 10	2022-01-10 00:00:00 UTC	2022-01-17 00:00:00 UTC	1	1

What Hacker News says

2 sources

Youden·Jan 10, 2022

If you want sleep tracking, you can use Muse S [0]. You can stream EEG readings in real-time using [1]. However it's really, really hard to get _useful_ data about one's sleep. The results computed by Muse are garbage. The only successful product I know is Dreem [2] but they've exited the consumer market. At the moment, I think the easiest way is to get an ECG (yep, for the heart, not the head) and process the readings using z3score-hrv [3]. [0]: https://choosemuse.com/muse-s/ [1]: https://github.com/alexandrebarachant/muse-lsl [2]: https://dreem.com/ [3]: https://medium.com/neurobit-technologies/clinical-grade-slee...

In Turn a Raspberry Pi into a Brain-Computer-Interface to Measure Biosignals

58x14·Sep 7, 2021

I have a Muse 2 [1] and a Flowtime [2]; both are consumer-oriented portable EEGs using Bluetooth to transmit data displayed on their respective mobile apps. The Muse hardware is seriously inhibited by the same user-exploitative trends we see everywhere, accompanied by meaningless promises. Many researchers used the Muse SDK and API until they discontinued it in 2019 [3] in favor of Muse Direct - another way to force users to feed Muse their data and lock them into a subscription. Unsurprisingly, this was also abandoned [4] and they claim "We're working on a solution that allows you to collect raw EEG data using the free to download" app, which would still allow Muse complete control over your authentication, use and data. Ugh. At least the community has reverse-engineered the LSL protocol and built a Python package [5]. Flowtime claimed t

Read the rest

hat it offers a closed API, as they don't have the resources to maintain an open API [6]. I remember somewhere they claimed it was on their roadmap, but I searched again today and couldn't find any support of their claim. BrainBit [7] and NextMind [8] seem to provide more robust developer tools, although I have no experience. Naturally, each of these runs more than double the ~$200 cost of the Muse and Flowtime devices. I have no formal neurological education but I strongly believe non-invasive EEGs, combined with novel, gamified training techniques coupled with machine learning will usher in a new era of digital interactions. Like the transition from tactile smartphone keypads to the eventually-ubiquitous full touchscreen, I expect many design iterations in both hardware and software will produce utterly fascinating products. I can't wait to get excited again for a product launch. [1] https://choosemuse.com/muse-2/ [2] https://www.indiegogo.com/projects/flowtime-biosensing-medit... [3] https://github.com/sccn/labstreaminglayer/issues/30 [4] https://choosemuse.force.com/s/article/Muse-Direct-Subscript... [5] https://github.com/alexandrebarachant/muse-lsl [6] https://www.kickstarter.com/projects/987756376/flowtime-bios... [7] https://sdk.brainbit.com/ [8] https://www.next-mind.com/developer/

In A soft, wearable brain–machine interface