## 6 Result and Discussion
### Estimation of Food Weight and Caloric Intake  
In our proposed method, the weight of food is measured from the number of swallows. The users were asked to swallow a bolus of food weighing about 1 g by taking a 1-g bite. Although lower than the natural food-bite size, this bite size helped the user to digest the food easily. Estimating the food weight based on the number of swallows is a novel idea and is simpler than previously employed food-weighing systems [26; 27]. The estimation error was lower for foods with a discrete nature (chips, peanuts, and cookies) than for foods with a composite nature (pizza and water). Because the discrete foods were ingested easily by the users in appropriate bites, such foods could be estimated with high accuracy. In contrast, it remained very difficult for users to take 1-g sips of water or bites of pizza, so the errors for these items were large. Fortunately, water has zero calories, so it has no role in calorie estimation for the goal of weight control. The weight estimation using the proposed approach is shown in Figure 9. However, the calorie measurement estimation for pizza was degraded, as shown in Figure 10. The weight estimation for the other solid foods was highly accurate. High accuracy for weight estimates is important because it is the basis for caloric measurements. Figure 9 displays the swallow-size comparison among different users for each food class. The horizontal line at 1 g represents the swallow-weight condition and acts as a reference for users over all foods; users were asked to take 1-g bites so that we could implement the stated strategy of weight estimation. Most of the foods shown in Figure 9 have short whiskers, indicating that all users swallowed similar amounts. However, pizza has large whiskers, indicating that different users swallowed different amounts. The estimated ingestion behavior of users exhibited error for swallow size, as graphically shown by boxes deviating from the reference line in Figure 9.  
Figure 9: This figure describes the deviation of the estimated food weight from the actual weight of the consumed food. Missed or undetected swallows and bites larger than 1 g were two sources of error in the estimation of food weight from swallow counts. Swallows greater than 1 g were the main contributor to the total error, while the remaining percentage of error was caused by missed swallows (21.3%, 13.4%, 12.5%, 16.1%, and 24.7% of the total error for chips, cookies, nuts, pizza, and water, respectively). For example, the overall error for water volume or weight was estimated as 29.26%, which can be further partitioned into 75.3% for large swallows and 24.7% for missed swallows. The percentage of error from missed swallows was smaller for the remaining foods, while the percentage of error from large swallow sizes was larger. All the participants in this experiment were young and were observed to take bites larger than the instructed 1 g for weight and calorie estimation. Thus, the weight and calorie estimation could be improved through careful selection of the amount of food for each bite. The number of calories in each food is measured as the estimated weight of the food multiplied by its calorie weightage (the number of calories in 1 g of that food). As previously stated, the calorie weightage can be entered into the developed smartphone application in two ways: manually by the user, or automatically as the application default value, which is generalized over food varieties. The manual method requires a little effort from the user to enter the calorie value correctly and achieve the goal of calorie estimation. Alternatively, the user can avoid the extra burden of manually entering the calorie weightage by instead selecting the default value. For the automatic selection of calories, many varieties of the same food are considered, and the mean value is fixed as the default in the application (this was completed prior to the experiment).