With 2020 winding down, we’re working hard to finish our next batch of 250 Enophones. We’re on schedule with these units – manufacturing is near-complete, and they’ll be shipping in the next couple weeks.
Incase you missed it: check out our previous update for information about our shipping timeline, shipping order, and how to update your address.
In parallel, we’ve been reflecting on our progress this year, and looking eagerly towards our next steps. While our focus has been primarily on shipping our hardware, we’ve been making quiet progress on our data science and software in the background. In this update, we’ll be focusing on the most exciting part of Eno: the neurotech.
We mentioned in our last update that we’ve shipped 350 units to date, and are shipping the next 250 in the coming weeks. We’re still on schedule for this batch. Check out our previous update for our most recent timeline.
This update we’re discussing several neurotech experiments that we’ve run recently using Enophones – measuring blink rates, SSVEPs, alpha blockades, and more. Check out the full update for the details.
Last, we go through the next few features we’re designing into the Enowork app. We’ve been listening to the feedback of our beta testers, and we’re really excited about the next steps for our software.
And of course, wishing everyone a Happy New Year!
On the software side of Eno, the majority of our emphasis has been on data science: building a core competence in using the EEG data we gather from Enophone to extract meaningful metrics that we can build into our app.
With the finished version of Enophone now available, we’ve been running experiments to demonstrate what we can measure with the device. Below we’ll be showing 5 experiments that we’ve run recently, and speaking to the broader implications of what’s coming next for our product.
1. Blink rate
While Electroencephalography (EEG) refers to the electrical activity from the brain, our bodies produce several other sources of electrical activity that can be detected by Enophone’s sensors. Electrooculography (EOG) refers to the electrical activity generated by eye movements – namely, a sharp electrical spike whenever you blink.
In our data, we’ve seen that in the filtered EEG signal, blinks are often visually identifiable. Given that blink rates are strongly correlated with focused attention, this is good news: measuring blink may contribute an additional physiological axis to our focus metric.
2. Heart rate
Building on what we said above, electrocardiography (ECG) represents the electrical activity produced by the heart. Because Enophone’s ear cup sensors are closer to the heart than the top sensors, at very low frequencies we can often detect fluctuations in our data generated by the ECG signal.
This is very interesting to us. Because ECG has better time-sensitivity than pulse oximetry (the heart rate technology in smartwatches), we have the potential to generate some very accurate heart rate readings from Enophone. While we haven’t yet confirmed this, measuring heart rate variability and breathing rate through this signal is also potentially feasible. These metrics are strongly correlated with physiological responses to stress, focus, and many other neuro-physiological states.
We’re very excited by these preliminary results. We’ll be looking to investigate incorporating blink rate and heart rate into our enowork metrics in early 2021, while exploring what other information we can gather from these signals.
This one is slightly more esoteric: Steady State Visually Evoked Potentials (SSVEP) are a harmonic response generated in the brain when visually exposed to specific frequencies. In other words: when a light flashes at a particular frequency, that same frequency will be reflected in your brain activity.
During our experiment, the subject was exposed to a 6Hz flashing light on a computer monitor for a few seconds. In the frequency vs time graph of their data, we can clearly see a sharp spike at 6Hz from their brain reflecting the stimulus.
This response was also replicated in the auditory domain, known as an Auditory Steady State Response (ASSR) – when subjects listened to a 40Hz isochronic tone, we were able to detect a sharp spike in their data showing that their brain reflects that same frequency.
The reason this matters is that these signals are the basis of many actively controlled brain computer interface experiences. SSVEP-based systems have been used to enable communication, as users look at a grid of letters flashing at different frequencies in order to select the letters they want to communicate.
While this is not our area of focus, we’ll be looking to partner with organizations that can use these functions to enable new experiences using Enophone, building out the next generation of brain-computer interfaces.
4. Alpha Blockade
“Alpha waves” is the title given to brainwaves occurring in the [8, 13]Hz frequency band. Alpha waves are strongly correlated and anticorrelated with several neurological states, and as a result are frequently cited in EEG literature.
The alpha blockade (known as the berger effect) is a particular phenomena whereby opening your eyes from a closed state causes a dramatic decrease in alpha activity. The opposite is also true: closing your eyes will consistently cause a dramatic spike in alpha activity.
Using Enophones, we were able to repeatably isolate these alpha blockades in real-world use. The graph below shows alpha activity plotted during a session where the subject opened and closed their eyes at 10 second intervals. The clear spikes and dips are indicative of these alpha blockades.
The clarity and repeatability of this signal make it very interesting. We are considering creating a classifier that recognizes when a users eyes are closed, and triggers an action in our app – say, starting a meditation session. We’ll be looking to run these experiments on a larger scale in 2021 to validate the accuracy, and determine whether this feature can add value to your day.
And of course, we’ve been experimenting with our focus metric.
We’ll be sharing a much more in-depth analysis of our focus metric, using performance proxies across different experiences – so stay tuned for that post. But in the meantime, we ran a quick fun experiment where we got users to alternate every 60 seconds between a mental arithmetic task, and a relaxing wakeful meditation. When we applied our focus metric, the results clearly portrayed changes in the two states of mind.
These experiments provide a simple way to explore the possibilities of what we can do with Enophone, as well as offering the chance to replicate some of traditional EEG experiments. We’ll be exploring these on a larger scale moving forward, in order to start leveraging the portability of Enophone to contribute to the current neurotechnology knowledge base.
Naturally, we want to share this with you as well – we’ll be building tools in the near future to allow you to test and experiment with your Enophone at home. If you’re interested in these experiments, and have ideas about your own experiments you’d like to run, let us know in the comments!
Enowork next steps
As a few hundred backers have started using our app, we’ve been working hard to test and refine the beta release. The last few months have focused exclusively on bug-fixing, as we get our first experience of shipping our software paired to the hardware at scale. Thank you again to everyone who’s helped us with bug-finding to date.
We’ve made some big progress in this area – with our next release we expect to be stable and fully functional on the vast majority of our backers’ devices. Because of this, we’ve started planning out the next few features we intend to implement, on the road to building an incredible experience that leverages the full potential of Enophone.
We wanted to share here the next few features we have in mind for the Enowork app.
1. Automatic session start
The Enowork app is designed around deep work sessions – fixed periods of time during which we track your focus level and app usage. For simplicity to start, these sessions are started and stopped by clicking a button in the dashboard of the app.
Our first priority is implementing this feature the way we’d intended: automatically starting each session when you put on your Enophone. This way, all of your focus data will be tracked by default, with no additional action required.
This will make tracking your focus fully seamless – put on the headphones, and the rest just happens. We’re quite excited about this change, and we’ll keep you posted on the timeline for sharing the major update.
2. Experimentation platform
This has been our most-asked-for feature for quite a while now. We intend to implement an experimentation platform within our app, where you’ll be able to record sessions, view your data and metrics in real time, and export your data for further analysis.
For all of you neurotech enthusiasts: if you have preferences for what features get added here, or how we can make the experimental setup more seamless, please do reach out!
3. Data visualization
In one of our earlier updates, we built a very quick-and-dirty data visualization graph as a demo into the app. Based on the feedback we’ve gotten, this is an area we intend to build out much more thoroughly.
The goal is to offer a page where you can visualize your raw brainwaves, but also your focus metrics, all in real time. We’re also looking at other tools like a frequency breakdown (theta, alpha, beta waves) and other indicators that could prove useful. The ultimate goal is to build this information into the deep work page, such that during any session you can view your data at a glance anytime Enophone is worn.
Let us know if there’s other information you’d like to see in this kind of page!
4. Daily view, and beyond
The current app helps you visualize focus levels in discrete sessions – each session is assigned a focus score, and offers insight into your brain activity during that period. From the feedback we’ve gotten, we intend to add a daily view as well, where you can see your day’s sessions amalgamated into a single view.
Beyond this, we will be looking to unlock our stats page, which offers weekly and monthly comparisons as well. This will be where we continue to add content over time, extracting additional insights from patterns across your sessions.
Our work is cut out for us, and we’re excited to be making progress with every release! We want to thank our beta testers once again for helping support our launch. In particular, shout out to the following users for their invaluable feedback: Kaben, Spechter, Brett, Mrbernz, M4tt_D4mon, JFNZ, Gustav, Sdimert, Cameron, Moibensa, Drex, Impish, Mobuli, Koguma, Tsetsefly, TheSingh, Adrian, Antoinette, Oldkidlg, and Raabuchanan!
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2020 has been a wild ride, but we’re so excited to have been able to finish it by shipping hundreds of Enophones. We can’t wait to ship the remaining units next year, so all of you can share in the experience.
Thank you so much to everyone for your support. Take care, be safe, and from the team here at Eno we wish you a happy new year across the world.
Lots of love,
– The Eno Team