Can wearables detect our "overeating moments"?

Today, wearables are evolving beyond simple fitness devices into personal health partners that read the invisible signals our bodies and minds send. They capture not only visible data like heart rate, body temperature, and steps, but also our lifestyle habits and emotional states. This raises an important question: "Can wearables actually detect the moments when we overeat?"

The answer many expect is, "Yes, they can!" However, the reality is a bit more complex. Given the current state of technology, wearables cannot 100% definitively tell you that you're overeating. Food isn't simply an act of energy intake; it's a complex experience intertwined with emotions, habits, stress, and environmental factors. At the same time, it's clear that "predicting" the possibility of overeating or "detecting warning signs" is becoming increasingly possible.

Signals from the Body

The first thing we can check is physiological signals. Heart rate and heart rate variability (HRV) are indicators that change significantly when we're tense or stressed. Because stress often triggers the desire to compensate with food, wearables can detect these changes as cues for emotional overeating. Galvanic skin response (GSR) is also noteworthy. Skin resistance changes with anxiety or arousal, indirectly suggesting that physical arousal can be linked to binge eating.

Body temperature and sleep patterns are also important data points. Sleep deprivation, in particular, disrupts the hormonal balance that regulates hunger and satiety, making us feel hungrier than we actually are. Low body temperature is also linked to changes in metabolic rate, ultimately stimulating appetite. Wearables that record our body temperature and sleep quality daily aren't just statistics; they provide practical clues that can help us identify the risk of overeating.

Moreover, activity levels cannot be overlooked. Inactivity throughout the day can trigger the body to crave more calories as a form of compensation. Wearables that track steps or exercise volume and then tell you, "You didn't move much today," go beyond simply recording exercise. Adding blood sugar or gastrointestinal sensors can capture actual post-meal absorption processes and food intake patterns.

Behavioral and Environmental Data

However, physiological signals alone aren't enough. Lifestyle habits significantly influence what, when, and how a person eats. Apps linked to wearables fill in this gap. For example, if a smartwatch and app automatically record "how many times a day and at what time," an individual's eating patterns can be identified through long-term data.

Food photo analysis is also an interesting example. Rather than simply taking a photo, AI can estimate the type and calorie content of food and automatically fill out a personal "food diary." When combined with external environmental data, this creates a much more comprehensive picture. Location data can predict "fast food restaurants frequented on the way home from work," ambient noise and temperature can predict "quiet night snacks," and even social media usage patterns can predict "late-night snacking on stressful days."

In other words, wearables go beyond a single device to provide a window connecting our daily lives with the outside world, revealing how our unconsciously repetitive behaviors and environments trigger overeating.

The "Map of Possibilities" Created by AI

At this point, the key lies in **"data combination"**. While individual signals are imperfect, observing multiple factors simultaneously can yield surprising insights. Let's take an example.

Let's say you experienced a significant decrease in sleep this morning, your work stress level spiked during the day, and it's currently around 10 p.m., a time when you often overeat. The AI ​​connected to the wearable can synthesize these three signals and predict, "You're at high risk for overeating right now." It's like a perceptive coach sitting next to you, advising, "You might want to cut back on snacking today."

This is the current viable approach. While it's difficult to directly determine "you're overeating right now," by combining body signals (physiological data), habits (behavioral patterns), and environmental factors, it can infer "you're likely to overeat right now." This gives users more time to control themselves before impulsively eating.

Walls Still to Be Overcome

Of course, there are still significant hurdles to overcome. First, wearable sensors inherently measure only indirect signals, making it impossible to accurately interpret emotional conflicts or personal experiences. Second, if the sensor accuracy and device wearing time are inconsistent, the reliability of the data significantly decreases. If the wearer frequently removes the device, crucial moments can be missed. Third, we can't ignore the fact that actual "overeating" is a mixture of subjective experiences. Eating the same amount can be considered overeating for some, while it's just a normal meal for others.

Ultimately, the answer that current technology can provide is clear. While it's difficult to know with 100% certainty whether you're overeating right now, it's quite possible to estimate your likelihood of overeating based on various signals.

The Value We Can Gain

In fact, the value we can derive from this "estimation" alone is substantial. If a wearable could detect subtle signals before we even realize it and alert us that "this is a dangerous moment," those few moments of awareness could be a significant boost in reducing unnecessary calorie intake and maintaining long-term health.

In other words, the goal of wearables isn't to be judges who determine whether we're overeating, but rather to be lifelong advisors who help us better understand ourselves and avoid being swayed by impulses.