Moodscope, subjective ratings and body blogging
Project Infobox 
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| Self researcher(s) | Ute Kreplin |
| Related tools | Moodscope |
| Related topics | Mood and emotion |
Builds on project(s) |
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| Has inspired | Projects (0) |
| Show and Tell Talk Infobox | |
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| Featured image | |
| Date | 2011/11/26 |
| Event name | 2011 QS Europe Conference |
| Slides | |
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Moodscope, subjective ratings and body blogging is a Show & Tell talk by Ute Kreplin that has been imported from the Quantified Self Show & Tell library.The talk was given on 2011/11/26 and is about Mood and emotion.
Description[edit | edit source]
A description of this project as introduced by Quantified Self follows:
Moodscope, subjective ratings and body blogging by Ute Kreplin. A keynote talk at the Quantified Self Conference Europe.
Video and transcript[edit | edit source]
A transcript of this talk is below:
Moodscope subjective ratings and body blogging by Ute Kreplin
My name is Ute and I’m a Ph.D. student at Liverpool John Moores University, and I share an office with Kyle and that’s how I got interested in this Quantified Self. What I did with this project is I combined a subjective mood tracking tool, an online tool with the body blogging system and the continuous recording of the heart rate to see whether I could learn something useful from combining the two. The tracking device I used was Moodscope, and it’s based on a slightly altered version of the positive and negative effective scale panels, which is a psychological tool that was developed in order to measure subjective experience mood. Moodscope allows you to visually track the ups and downs over the weeks and months. The body blogging system is the act of logging how your body changes over time using web technology, and as I said I got introduced to this by Kyle. I didn’t record my heart rate 24/7 though, I did it for eight hours during the working day, so usually about 9 to 5, and I live streamed this to Twitter and also the physiological computing dot website, which changes its colors depending on my levels of activity on my heart rate. There is some interesting things on my observations that I would like to share, and one of them is that we didn’t have time to develop a completely new system that I could use. So I used Kyle’s platform and Kyle’s twitter account in order to share my data with the Internet. What’s interesting is that my heart rate is 20 bpm lower than Kyles, so on twitter that meant that meant his heart rate dropped from an average of 70 to 80 beats per minutes to an average of 50 to 60 beats per minute, so it’s quite a difference. And on the physiological computing dot network site it indicated that Kyle was asleep for three weeks before we managed to change the system and adapt it to a little bit more to my changes of heart rate. What I found interesting is that no one enquires to Kyle about this and no one asked if he was okay or where these changes came from. And then another observation was my mum’s reaction. I sent her an email inviting her to follow my heart rate changes over twitter, but she replied that she would certainly not sign up to this. As you can imagine I was taken aback, so I asked her about it why this might be and I thought maybe she would be worried about my health and she just didn’t want to keep such a close eye on me. But she sent me an email back saying that she would find it annoying and disruptive, so thanks mom! But I thought about this for a while and I think it raises an interesting question, and that’s the question of how we can share this data in a more meaningful way and in a more meaningful way for other people as well. And obviously I was interested in for the body blogging data would tell me about my mood or the other way around. So what did I find? This is a graph of my Moodscope data and an average score of my heart rate recordings, and I think the on the Moodscope data you can see quite clearly. There are two negative and one positive spike in there, but the heart rate data doesn’t really follow this trend to the same degree. So I was wondering what was going on here, and I think one of the things that we are dealing with is an incompatibility of my recording. And what I mean by that is the Moodscope asks you for one day live recording of a subjective rate once-a-day, whereas the body blogging system it is a continuous rating throughout the day. And through that there is a lot of variation introduced into that data, because obviously your heart rate levels vary quite a lot during the day in depending whether you are sitting down, walking about, or having lunch and all of these sorts of things. By crashing that down into one daily average all of that variability is lost and I think to a certain degree may be skewed the data a little bit as well. So what I did next was to just look at the one hour where I had taken the Moodscope just to see maybe if I just look at the smaller sample that would be a better representation. And you can see from the graph on the right, that if I just look at the one hour the trend does seem to be following a little bit better, but it still doesn’t completely match up. A specially the positive spike is not followed by my heart rate data, and I think that one may be where there is a little bit more going on in the first spike on 4 August, where there is quite an negative spike and my Moodscope has quite a high positive rise on my heart rate data. But I will come back to that in a moment and talk a little bit more of what is going on that day. One of the other things that is going on is the question of context and how we act to the body blogging data, and I think there are two different sort of approaches that you can use. And one is more of a top-down approach, which are used with the Moodscope data. So predisposed the context and I wanted to match that onto the body blogging data and see how they match up, rather than letting it evolve naturally. I think sometimes that works a little bit better, and sometimes it doesn’t work quite so well as you could see on the previous graph. Perhaps a better way of looking at the body blogging data it is a bottom up approach, which is more what Kyle used in his year-long data. You have to have the recording first, and once you have the heart rate recording you see what is going on on the days where maybe there is an abnormality within the score. So whether the score is high or low, or where your sleep pattern is disrupted sort of at the context and gain a meaning after the recording has been done, rather than trying to have something beforehand that you then try to match up with it. I think the heat maps are a really good way of doing that, because it is just a nice visual representation of the body blogging data, which we can then go back and have a look at these abnormalities and sort of see what was going on. We had a heat map for my body blogging data for the month of August, and the same as with Kyles. The different colors reflect different levels of my heart rate and levels of activity. So the darker blue and green colors are low levels of activity, and the yellow and more orange colors are higher levels of activity. Because I only recorded during the day there is no actual sleep data within that. But I think what the heat map shows quite nicely it’s just that variety of the body blogging data, and that richness that we can get out of that, to which we can learn what that means. I think with that I would like to come back to 4 August which is this day here. It was only a short day of recording but it is quite an interesting day. And you can see from the colors that my heart rate was quite elevated that day, so you would expect to see something like if I do some mild form of some exercise or at least something quite vigorous if I’m highly stressed. But on that day I was asleep, so that is quite unusual with this coloring in it. And what you see represented here is just my body fighting with the common cold as I was ill that day, and that completely drove my heart rate through the roof. If I was asleep then you would expect my heart rate to be around 40 beats per minute, and my average was in the 70s which is quite a big difference. I think from that you can see about how you can gain more meaning from the data if you unlock the context later rather than predisposing it beforehand. So in conclusion I think there’s a compatibility mode of recording between the two, but it doesn’t quite work in the way that I tried to do it. Then I think building the context afterwards is more important, and that becomes more meaningful if you do it in that way. I love the heat maps because I think it is a really nice visual way of representing the data, and I think perhaps it is a good way of sharing the data as well, because it is easily accessible by other people as well. And it’s easier for other people to sort of following the patterns within that.
And I think that sort of brings me back to the sharing of the data and how we can make it more meaningful. And I think perhaps it is not the sharing of every day events that we are looking for, but more extraordinary events that are important to us that we can then share with other people. So with my mom it might be more important to follow my heartrate if she knows I went to a job interview or did some public speaking, rather than the sort of day to day. And I think through that body blogging systems can be a way of capturing new experiences as well, and going back to them later on almost like a personalized photograph. Because if you can just imagine if you wear a sensor on your wedding day and you can capture the butterflies that you experience from that day in beats per minute.
About the presenter[edit | edit source]
Ute Kreplin gave this talk.