Weight and exercise tracking with the Hacker Diet

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Project Infobox Question-icon.png
Self researcher(s) Jodi Schneider
Related tools scale, Phillips exercise tracker
Related topics Diet and weight loss, Food tracking, Stress, Activity tracking

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Has inspired Projects (0)
Show and Tell Talk Infobox
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Date 2011/11/26
Event name 2011 QS Europe Conference
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Weight and exercise tracking with the Hacker Diet is a Show & Tell talk by Jodi Schneider that has been imported from the Quantified Self Show & Tell library.The talk was given on 2011/11/26 and is about Diet and weight loss, Food tracking, Stress, and Activity tracking.

Description[edit | edit source]

A description of this project as introduced by Quantified Self follows:

Jodi Schneider talks about tracking weight and exercise using the Hacker Diet model. She discusses what she did, how she did it and what she learned from it. She also shares her experiences with the tools she used and what she learned from them.

Video and transcript[edit | edit source]

A transcript of this talk is below:

Weight and exercise tracking with the Hacker Diet by Jodi Schneider

Hi, I’m Jodi Schneider and I’m going to talk about tracking weight and exercise which is a much more personal talk for me. One thing that I noticed as I was coming into Amsterdam was these windmills offshore out to sea, and the thing that I thought about seeing those was they’re all in these straight lines and this pattern that we can pick out very easily by eye. But to pick that pattern out in data like weight and exercise data is a lot harder. So I’m hoping while I’m here to get some more about that. So just to tell you a little bit about what you know, so what am I doing to begin with? So you may have seen VMI categories of weight. I’m over here and slowly trying to move left down this continuum and so I’ll tell you what I did, how I did it, and what I’ve learned from that. So in terms of what I did, I just used two really simple tools, one is this exercise tracker which is actually from Phillips and thank you I actually found out today they’re one of the sponsors, and the other is just a normal scale. The other is a theory, so after I had been wearing the exercise monitor for maybe six months somebody I work with came and said, ‘Are you trying to lose weight?’ this is not a normal thing you say to a fat person, it’s really rude right. So I said yes, you know, this is a useful thing to begin with for that. And I got a story about here’s a story of how I lost a bunch of weight and it was this great thing and it’s the Hacker Diet. A really fantastic thing to look up and everybody has got the model how to lose weight. You just have to eat less and exercise more, and you know what you’re burning has to be less than your eating and so on. The reason this is actually complicated is the amount that we’re taking in, in terms of food, water, and oxygen and the amount that we’re putting out in terms of solids, water, and carbon dioxide stops about 6 kilos, 13.5 pounds. Now, if you’re somebody like me who has a lot of weight to lose ideally, then at the maximum you are probably going to be looking at 500-600g a day. So there’s an order of magnitude between the signal and the noise. That’s really a problem. So that’s one of the observations of the Hacker Diet and the way that they deal with that is by moving averages. So instead of looking at ‘Oh my weight went up three pounds and it went down three pounds’, when infact it’s really pretty much staying the same; this is the guy who made up the Hacker Diet and his sort of maintenance when he was here’s just 0.1 pound that’s actually going on. So you can find that signal amongst the noise where it looks like things are going all over the place. So if you are at all interested in keeping track of your weight, there are lots of ways to do averages, but you really need to be looking at moving averages, and this is generally when people tell you don’t weigh yourself every day, this is why. So I would say do weigh yourself every day, and that’s what I do, but use the data differently. So I’ve been weighing myself for the past a little more than a year and this is what my data looks like. So you can see that sometimes this is going in the direction I like, and sometimes not. And one of the things that the Hacker Diet has been really helpful for is just having this visual of what the data actual looks like, so that I can very quickly know ‘This month I seem to be on an upswing. I’d like to fix that before it becomes you know one of those upswings.’ Now, in terms of exercise monitoring this is something I’ve been doing for about a year and a half, and there’s what that data looks like. There is a lot of seasonal variation, you can see November, December cracked. This is what happens when you live in a country where there’s not so much light, and we make it worse by having daily savings time. But what I really wanted was having those two things together, and unfortunately that’s a little bit hard because these are systems that aren’t exactly designed to be programmed with or even to export their data in CSV files or something like that. So that’s one challenge that I’m working on and I have got a lot more skill at collecting the data than actually analyzing it. So that’s the first observation that I have about these tools. You really need to think about how you’re going to get the data out. The other issue that I’ve had with the exercise monitor, now this uses an accelerometer, so here it is on the chest and you can wear it around lots of different places in lots of different ways, but the bulk of my exercise is yoga, and biking. Now, yoga, you’re not moving around a lot. You’re doing these sort of static movements where you know, holding positions is what that’s about. And biking, obviously your legs are moving, but if you’re a really good biker you don’t need to use your hands, you just sort of go and your chest is completely still. But even so, through this system there’s a lot of hand labelling if you want to get the data correctly. So I accepted that the data is lossy and so I was doing really well annotating and just gave up, and I need a system that is going to learn and predict the patterns based on what they look like, because that’s what I’m doing when I’m annotating the data anyway. I don’t remember ‘Oh I came to work at 10 o’clock, so I must have been biking from 9:40 to 10.’ I look and say ‘there’s the spike’. And also as I said, having these visible tools is really helpful. In terms of exercise monitoring some of the things I learned, as I said sunlight really matters. And one thing that I don’t think – and not sort of obvious, but one thing that I don’t think I really would have learned without the exercise monitoring is different patterns can really make a difference. So, you know everybody thinks, ‘You should go to the gym and get a really good workout’, that can be really good, but it actually may not be. So one of the patterns that I have from time to time is I have an intense workout and then I’m like, ‘Oh I’m so tired I can barely move.’ And infact as it turns out there’s maybe times when I do maybe do, you know, sort of collapse and just spend the rest of the day just sort of sitting around not really even doing sort of normal level of moving. And that actually means that going to the gym can mean I’m getting less exercise overall which is detrimental obviously. So there’s this balance there, whereas a day when I maybe out shopping and doing lots of errands and walking around all day and I end up really tired, that is probably the day that I’m getting the most exercise. So some of the ironic things about what you think is exercise and what actually is it turns out that really having these patterns where you’re sedentary and sitting and you know probably many of us in this room are computer geeks, so then get an exercise ball and it you have other ideas around here I need some. In terms of weight tracking I went to CCC camp and just for survival and not going to get a lot of sleep, and I hadn’t eaten very well the day before I just stopped eating sugar while I was there and I was like, it’s really easy by the end of the week to not eat sugar. So I kept at it for a little more than a month and that was fantastic for weight loss. But really sugar is a very addictive substance. In terms of the weight averaging, like I said having the meaningful and the meaningless weight swings and knowing those, and getting the ability to correct those and having the real feedback loop there, and we need more on that. And travel is another thing and I’m still sort of working at. There are times when travel is just fine and then I went on a trip to Taiwan and I got really jet lagged for the first time ever and had no idea where things were and my eating patterns they were terrible. So that was a time when travel was really really bad for my weight. So things I would like to track and like to talk to people who are tracking these are you know food obviously, I need an easy way to do that, and there are plenty of ways to track but it needs to be easy and lazy. Blood sugar, if anybody is diabetic I’m really interested in hearing if there are good ways for people who aren’t diabetic to track blood sugar because I think that’s a real factor. And I would love to hear what other people are tracking that seem to be good, and also more about you know integrating the data that you’ve already got. The travel data I’ve got, the daily patterns I’ve got, but putting those altogether has sort of got to look at the monthly patterns but needs to do more.

So this is how to get a hold of me aside from in person and I would love to talk about more of those.

About the presenter[edit | edit source]

Jodi Schneider gave this talk.