英文摘要 |
The increasing popularity of dining out has led to a rise in obesity and a reduction in exercise among adults. In addition, the increasing consumption of refined foods is resulting in unbalanced diets and elevated risk of various chronic diseases. To reduce these risks, much attention is being paid to methods of weight loss in Taiwan, and there is increasing awareness of the need to monitor caloric and nutrient intake, as well as an emphasis on the healthiness and balanced nature of food intake. Hence, we developed the “personal diet and caloric intake monitoring system” for use on smart phones, which is based on the fuzzy inference method. In this system, a QR code is used to save information regarding nutrients, including calories, protein, fat, carbohydrates, and sodium. Using the data stored in the QR code, the proposed system calculates the total nutrition from individual sessions of food intake. Next, it determines whether the number of intake-calories and intake-nutrition value go beyond the daily recommended allowances. In addition, this system applies the G-Sensor available on most smart phones to measure the rocking motion of users during exercise. Fuzzy inference method infers number of calories burned. The success rate of the system was 90% in terms of the accuracy of calorie burning calculations. Based on comparisons with Nike+ sensor, the calorie-burning value measured by the proposed system was closer to that calculated by the standard calorie-burning formula. In summary, this proposed system was able to help users make food selections and monitor calories, regardless of gender or goal whether it be losing weight or monitoring diet. Users are able to adjust nutritional intake and measure calories burned during exercise to eventually balance nutrients and control caloric intake. |