Imagine you’re sitting down to eat, but before you take a bite, you whip out your smartphone, fire up a special app, and take a picture of your food.
The app identifies the food types by appearance, then calculates the size of your portions, and estimates your intake of calories, carbs, protein, vitamin, mineral, sugar, salt, and so on. Later you can review your data in a variety of ways.
You can see your calorie intake for the day, or compare yourself to other people who are your same age, size, activity level, and so on.
At the end of a meal, if you have some food left, you can snap another picture so the app can calculate the net of what you actually ate.
If it seems impossible that an app could recognize food types, consider that software can already recognize faces, voices, specific songs, and fingerprints. Recognizing broccoli can’t be that much harder.
And anything that has a label or a wrapper, such as Diet Coke or a Snickers candy bar, would be relatively easy for the app to identify.
Soups and casseroles would be harder to identify and analyze. The app might ask you to supply some information on the main components of the dish. If you said it was a casserole with potato, chicken, and garlic, the app would know that garlic is a minor ingredient and potato is the main ingredient.
It might even look at similar recipes in its database and take an average.
The app would not be perfect at estimating, even with your frequent tweaks. But it would be far better than your own guessing. And it would be great at telling you where your diet is lacking. You might think you have a good diet, only to discover that you aren’t getting enough variety of fruits and veggies.
Now imagine that an accessory for this app is a small waterproof motion detector that you can clip to your footwear. It comes with a watch that also has motion detection. When your smartphone is nearby, the two motion detectors wirelessly download how much movement your arms and legs have experienced that day.
That would be a rough proxy for exercise. You would have to add any data for weight training because that doesn’t require much movement.
Now your app has your total nutrition and exercise profile. You could round out its knowledge by telling it your age, weight, gender, whether you smoke, and other relevant health questions.
From that point on your app could predict your life expectancy and even your odds of dying from specific types of preventable diseases. Perhaps your watch could display both the current time and how many days you have left if you keep living the way you are.
Two factors that most influence human behavior are the ability to measure progress and the framework used to rank performance. This app solves both problems. Allow me to expand on this.
I’ve noticed that losers compare themselves to the average of other people, whereas winners compare themselves to their own natural potential.
The loser can find comfort in knowing there are plenty of other slackers, and he is average (good enough) among them. The winner compares his progress to his personal potential and doesn’t stop until he achieves it.
Researchers have found that simply being near overweight people has a large influence on your own weight. This is probably a result of looking around and deciding that eating a little extra is normal, and good enough. The app I described would change your point of reference by continually reinforcing your own potential.
In time, your frame of reference would be less about your chubby friends and more about how you are doing compared to your own best, as measured by your app.
The app identifies the food types by appearance, then calculates the size of your portions, and estimates your intake of calories, carbs, protein, vitamin, mineral, sugar, salt, and so on. Later you can review your data in a variety of ways.
You can see your calorie intake for the day, or compare yourself to other people who are your same age, size, activity level, and so on.
At the end of a meal, if you have some food left, you can snap another picture so the app can calculate the net of what you actually ate.
If it seems impossible that an app could recognize food types, consider that software can already recognize faces, voices, specific songs, and fingerprints. Recognizing broccoli can’t be that much harder.
And anything that has a label or a wrapper, such as Diet Coke or a Snickers candy bar, would be relatively easy for the app to identify.
Soups and casseroles would be harder to identify and analyze. The app might ask you to supply some information on the main components of the dish. If you said it was a casserole with potato, chicken, and garlic, the app would know that garlic is a minor ingredient and potato is the main ingredient.
It might even look at similar recipes in its database and take an average.
The app would not be perfect at estimating, even with your frequent tweaks. But it would be far better than your own guessing. And it would be great at telling you where your diet is lacking. You might think you have a good diet, only to discover that you aren’t getting enough variety of fruits and veggies.
Now imagine that an accessory for this app is a small waterproof motion detector that you can clip to your footwear. It comes with a watch that also has motion detection. When your smartphone is nearby, the two motion detectors wirelessly download how much movement your arms and legs have experienced that day.
That would be a rough proxy for exercise. You would have to add any data for weight training because that doesn’t require much movement.
Now your app has your total nutrition and exercise profile. You could round out its knowledge by telling it your age, weight, gender, whether you smoke, and other relevant health questions.
From that point on your app could predict your life expectancy and even your odds of dying from specific types of preventable diseases. Perhaps your watch could display both the current time and how many days you have left if you keep living the way you are.
Two factors that most influence human behavior are the ability to measure progress and the framework used to rank performance. This app solves both problems. Allow me to expand on this.
I’ve noticed that losers compare themselves to the average of other people, whereas winners compare themselves to their own natural potential.
The loser can find comfort in knowing there are plenty of other slackers, and he is average (good enough) among them. The winner compares his progress to his personal potential and doesn’t stop until he achieves it.
Researchers have found that simply being near overweight people has a large influence on your own weight. This is probably a result of looking around and deciding that eating a little extra is normal, and good enough. The app I described would change your point of reference by continually reinforcing your own potential.
In time, your frame of reference would be less about your chubby friends and more about how you are doing compared to your own best, as measured by your app.
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