4 Months Of Emotion Tracking
Project Infobox 
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| Self researcher(s) | Matteo Lai |
| Related tools | Empatica |
| Related topics | Mood and emotion, Stress |
Builds on project(s) |
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| Has inspired | Projects (0) |
| Show and Tell Talk Infobox | |
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| Featured image | 
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| Date | 2012/09/12 |
| Event name | 2012 QS Global Conference |
| Slides | |
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4 Months Of Emotion Tracking is a Show & Tell talk by Matteo Lai that has been imported from the Quantified Self Show & Tell library.The talk was given on 2012/09/12 and is about Mood and emotion, and Stress.
Description[edit | edit source]
A description of this project as introduced by Quantified Self follows:
Matteo Lai works for Empatica, real time emotion tracking through physiological signals. Matteo discusses the device they are currently working on. This small device comes in a mobile setting and helps users to accomplish their goals and see what’s going on in their emotional map. Mattoe shares his personal experience with the device. He did 4 months of emotion tracking with it.
Video and transcript[edit | edit source]
A transcript of this talk is below:
This is Empatica, the company I work for and we do real time emotion tracking through physiological signals. We do this with a small device in a mobile setting, because we think that's the best environment for doing it. Our idea is to help the user to accomplish their goals and having a sense of what’s going on in their emotional map.
At the moment, we concentrate especially on stress tracking. We run a lot of experiments and we take the data, analyze it and try to turn them into emotional models. This is an example of the report that we do. We run sessions in different ways and we track all sorts of physiological signals. And what you saw up there was the two models of stress and engagement. And of course we try to do this in real life because it’s more interesting, and we have all sorts of clinical settings. We mostly work with hospitals and research centers. So, that’s how we do it, and we have the device with some physiological sensors. Then the data gets sent to the iPhone and you can get contextual information on the activities that you’re doing. So, I tried to apply this stuff on myself rather than just having it on our experiments. I have a kind of very stressful life, and of course the startup life is very demanding. And I wanted to see at the beginning what sort of impact it had on my experience, in terms of the general trend and not so much of the daily specifics. So I did an experiment on myself for 10 weeks, and the sort of results that I focused on were the weekly trends. I wanted to look at the main mood that I was experiencing, and the activities and the location that mood was more frequent in. You can see here there is also the world's mood, and what we do with this is a fun thing with all the signals that we have available but that’s another story. So I ran this for 10 weeks and what turns out, and not surprisingly, is that I’m very stressed. So, a huge discovery! But it was very interesting because while I was doing it, I became much more aware of myself. The process of tracking was very introspective, and the situation it showed looked hopeless, as you can see. I thought, "Maybe I need to change something." During the process I started to be more interested in the daily tweaking of my everyday life. So I made some adjustments and tried to see in a different phase of just six weeks of what was going on. What I did. I started doing a breathing exercise first thing in the morning after getting right out of bed. I didn’t check my email until I had my morning meeting done, the top item on the list. And then I tried to do a meditation exercise in late evening of about 15 minutes. After six weeks I managed to come down a little bit, especially the morning exercise and the morning tweaking were very helpful. After this process I started looking more closely in what was going on in the daily pattern, and of course I have real-time stress tracking in my device. You can see an average working day here; this is after the six weeks. The exercises lowered the average stress levels for the first part of the day. Then stress would accumulate and be sort of amplified for the rest of the day. That was good, because before it was like huge piles at the beginning; email the first thing in the morning was very bad. So now I’m focusing on trying to do more relaxing techniques right after lunch. For example, I try meditating right after lunch to try to lower stress levels and not get the amplification effect that goes on at the end of the day. So this is quite interesting and I had some discoveries during the process. The first one was that I thought real-time was the coolest thing on earth; you get problems when you stress but it was very nice. In reality, at the beginning, it wasn’t so interesting. It starts off very faded away because I wasn’t very aware of myself, so I needed to have a bigger picture first. I think real-time works only if you have suggestions on what to do rather than looking at a graph and saying if you’re stressed or not. And trends are much more cooler, and you get a picture of what’s going on, and over time you sort of don’t need it anymore. So the data is very important but after a while it goes into the background, and you realize the data is not the end. It’s just a meaning to get the purpose done. So my purpose was to optimize and get my daily routine on track and not lose control of my day. So tracking in the background, focusing on the outcomes and leveraging this data to get something done. The things I’m concentrating on at the moment are on a personal level. I'm doing this sort of daily tweaking of small things that can change the daily pattern over time. That’s the first level on a much smaller scale. And on a much bigger scale I would like to see an impact on the big decisions, but also the daily life. But that is probably more difficult to see the impact it has on my days. That is going to be the next experiment.
The final disclaimer is that this is just about myself and not necessarily what the company does. It does more serious stuff, by the way. And if you are more curious about it just come and talk to me and I’ll be happy to answer. Thanks.
About the presenter[edit | edit source]
Matteo Lai gave this talk.