Designing Machine-to-Machine (M2M) Prototype System for Weight Loss Program for Obesity and Overweight Patients

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1 2016 7th International Conference on Intelligent Systems, Modelling and Simulation Designing Machine-to-Machine (M2M) Prototype System for Weight Loss Program for Obesity and Overweight Patients Gunawan Wibisono Electrical Engineering Dept. Universitas Indonesia Depok, Indonesia I Gusti Bagus Astawa Electrical Engineering Dept. Universitas Indonesia Depok, Indonesia Abstract - Obesity/overweight patient is a person who has excessive body weight which prone to have serious diseases like heart disease, stroke, diabetes, some types of cancer, and osteoarthritis. In general, obesity/overweight is caused by some factors: excessive food intake, lack of physical activities, and genetics. In 2013, more than 2 billion people suffer obesity/overweight including 40 million in Indonesia. To overcome obesity/overweight, patients should control their food intakes and do physical activities. In most cases, the problem is they don't know whether their foods are good or not for their weights, and in the end, they fail to control their weights. This research helps weight loss program with machine-to-machine (M2M) technology with using special weight scale which can upload data to the server. Website and mobile application are built to give recommendation what food to eat today based on calorie calculation, in order to reduce their weight during the program. Keywords - machine-to-machine; obesity; overweight; weight loss program; food recommendation; calorie calculation. I. INTRODUCTION Obesity and overweight are a medical condition where a person has excessive body weight which can cause serious diseases like heart disease, stroke, diabetes, some types of cancer, and osteoarthritis [1]. A person suffers overweight if his/her body mass index (BMI) is more than 25 (or 23 for Asians) while obesity is a condition where BMI is greater than 30 [2]. BMI formula is weight (kg) divided by square of height (m 2 ). In general, overweight/obesity is caused by some factors: excessive food intake, lack of physical activities, and genetics. Statistical data in 2013 mentioned that more than 2 billion people in the world suffer overweight/obesity, with 40 million of them are Indonesian [3]. To overcome, they need to control their food intakes and doing physical activities [4]. Thus, they should monitor their weight day by day in within their weight loss program. This study aims to help overweight/obesity patients to reduce their weight with machine-to-machine (M2M) technology, i.e. to design a system which includes: 1. A special weight scale which has the capability of sending data to M2M server. 2. A website and a mobile application (Android based) to give information about weight monitoring day by day, and daily food recommendation to the user. The rest of this paper is arranged: Section 2 talks about literature review, Section 3 talks about methodology: system design and algorithm. Section 4 is about the implementation and Section 5 discusses results expected. The conclusion of this research will be written in Section 6. II. LITERATURE REVIEW In the last decades, information and communication technology (ICT) have been blooming in every sector of human life. M2M is one of ICT that attracted huge attention nowadays. Many research about M2M have been done, including in healthcare sector. The popular use of M2M in healthcare is for patient monitoring purpose [5-7]. More specific implementation of M2M in healthcare related to this study is for weight loss program monitoring. [8] discusses the design and implementation of weight and height measurement device to inform people their weight and height. Other research [9] aimed to develop a mobile application to calculate BMI and ideal weight. A more comprehensive study [10] analyzes the effectiveness of Internet-based weight loss program which conclude that Internet use combined with other methods could give positive results. Meanwhile, we can find some commercial products which offer device and application to help weight loss program. One of them is Fitbit AriaTM [11]. It has a smart scale that has the ability to upload data to the server via wifi connection. Even, it has the ability to track patient's activity by using a special armband. Another popular product is WithingsTM [12] which has similar functions /16 $ IEEE DOI /ISMS

2 with Fitbit AriaTM. The shortfall of both products is they don't have food recommendation system, so users don't have any suggestion on what food to eat every day in their weight loss programs. III. METHODOLOGY Referring to those facts, we have formulated a diet which is a number of calories intake per day (in kcal) for weight loss program (Table 1). TABLE I. CALORIES INTAKE TABLE FOR THE WEIGHT LOSS PROGRAM A. System Design The logic flow of the system built in this research is described in Figure 1. First, weight scale measures user's weight and send data via Bluetooth (Wireless Personal Area Network) to user's smartphone nearby. Smartphone receives data from Bluetooth and acts as M2M gateway that sends data through Internet cloud to M2M server. Then next step, the server processes data and produces food recommendation to control user's calories for weight management. It stores data in a database and sends data to the website and mobile application. Website and mobile application in user's side receive data from the server through an Internet connection and display the food recommendation and weight loss program progress. Besides calories intake table, we need to know the length of weight loss program. It depends on how many kilograms of weight a patient should reduce. With normal standard 500 grams/week loss, the duration length (or w) in week, is: weight to be reduced (kg) w (week) =... (1) 0.5 (kg/week) For example, if a patient's height (an Asian) is 170 cm with 80 kg weight (or BMI=27.7), if he wants to have ideal weight (BMI=23), he should achieve 66.5 kg of weight. It means that his weight to be reduced is 13.5 kg, so the length of his weight loss program is 27 weeks. Figure 1. Basic logic flow of M2M system for the weight loss program B. Weight Loss Program Algorithm According to [13], patient who wants to reduce their weight should pay attention to following facts: Every day, a person needs calories about 12 to 15 kcal per kg of weight. It depends on gender and physical activities as well. Typical diet therapy for man: kcal intake per day, and kcal for a woman. With this typical diet, a patient is expected to reduce weight: 70 grams/day or about 500 grams/week. Calories intake cannot be less than 800 kcal per day. IV. IMPLEMENTATION The implementation of this research is focusing on developing a website and an Android application for weight monitoring and food recommendation system. For the weight scale itself, we use off-the-shelf product which can send data to our server. A general flowchart of weight loss program in this study is depicted in Figure 2 below. 139

3 Breakfast: about 20% from total calories for a day. Lunch: about 40% from total calories for a day. Afternoon snack: about 15% from total calories for a day. Dinner: about 25% from total calories for a day. For each menu, we provide 5 sets of food, so the user has choices to eat what he/she prefers, to avoid getting bored in weight loss program. The system will rely on the database built in the implementation. Figure 3 gives the excerpt of database structure, where the database is built in MySQL format. Figure 3. Excerpt of the system database Figure 2. Flowchart of the weight loss program application The flowchart describes the process in weight loss program. First if a patient's BMI is higher than 23 then he/she should do the weight loss program. He/she should calculate how many kg should be reduced to achieve BMI = 23. Then he/she must do the diet therapy based on gender, weight, and physical activities (food recommendation will be provided by the system). Diet therapy length (in weeks) is determined by how many kg of his/her excessive weight divided by 0.5. Weekly evaluations will be required to assess whether he/she successfully reduced the weight by 0.5 kg. If he/she fails to achieve, the program must be restart again. This cycle will be ended when therapy schedule is finished. For food recommendation, it is given in daily basis, which split daily menu into 4 menus: breakfast, lunch, afternoon snack, and dinner. The calories composition for each menu is: V. RESULTS The results of this paper are the website and Android application designs since at the time this paper is written, we are still in the middle of the development. The website or Android application basically contains 4 main pages: Home, History, Food Calories, and Personal Information. The Home page displays most recent user's weight and food recommendation for today, as depicted in Figure 4a and Figure 4b. 140

4 Figure 4a. Home page of the website application Figure 5a. History page of the website application Figure 4b. Home page of the Android application Then the History page contains statistics of user's weight for specific time range: last 7 days, last 1 month, last 3 months, or the entire program. It contains the weight target and target time as well (Figure 7a and Figure 7b). Figure 5b. History page of the Android application The third page is Food Calories list (Figure 6a and Figure 6b), simply displays various kind of food (Indonesian and Western) and the calories contained. This list is taken from food database and used for daily food recommendation in Home page. 141

5 Figure 6a. Food Calories page of the website application Figure 7a. Personal Information page of the website application Figure 6b. Food Calories page of the Android application And the last is Personal Info page, it displays user's information such as username, first name, last name, , password, gender, height, initial weight, weight target, daily activity level, and user's picture as well. This information is filled in user registration previously, and can be updated through this page (Figure 7a and Figure 7b). Figure 7b. Personal Information page of the Android application VI. CONCLUSION This research aims to help obesity/overweight patient to reduce weight with weight loss program, with the help of M2M technology using smart weight scale which can upload data to the server. Along with it, we build a website and an Android application to monitor the weight every day and give food recommendation based on calorie calculation. The calorie intake refers to some variables: 142

6 patient's gender, weight, and physical activity level. Meanwhile, the duration of weight program loss depends on the excessive weight a patient wants to reduce. Eventually, this system is expected to help patients to successfully reduce their weights in weight loss program by monitoring their daily weights and this system recommends how many calories they can eat every day as well. REFERENCES [1] Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng L, INTERHEART Study Investigators. (2004), "Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): Case-control study". Lancet 364 (9438): doi: /s (04) PMID [2] Haslam DW, James WP (2005). "Obesity". Lancet 366 (9492): doi: /s (05) pmid [3] Lusia Kus Anna (June 2, 2014). "Indonesia Masuk 10 Besar Orang Gemuk Terbanyak" ( suk.10.besar.orang.gemuk.terbanyak). [4] Kopelman and Caterson 2005:324. "Clinical Obesity in Adults and Children". [5] Enriko, I., Gunawan Wibisono, and Dadang Gunawan. "Designing machine-to-machine (M2M) system in health-cure modeling for cardiovascular disease patients: Initial study." Information and Communication Technology (ICoICT), rd International Conference on. IEEE, [6] S. Jung, J. Y. Ahn, D.-J. Hwang, and S. Kim, "An optimization scheme for M2M-based patient monitoring in ubiquitous healthcare domain," International Journal of Distributed Sensor Networks, vol. 2012, [7] C. E. Turcu and C. O. Turcu, "Internet of Things as Key Enabler for Sustainable Healthcare Delivery," Procedia-Social and Behavioral Sciences, vol. 73, pp , [8] Thomas, Thomas. "Sistem Pengukur Berat Dan Tinggi Badan Menggunakan Mikrokontroler AT89S51."TESLA Jurnal Teknik Elektro UNTAR 10.2 (2010): pp-79. [9] Pinandita, Bijak Jati Kusuma Tito. "Rancang Bangun Aplikasi Mobile Perhitungan Indeks Massa Tubuh dan Berat Badan Ideal (A Design of Mobile Application to Measure Body Mass Index and an Ideal Weight)." JUITA 1.04 (2011). [10] Tate, Deborah F., Rena R. Wing, and Richard A. Winett. "Using Internet technology to deliver a behavioral weight loss program." Jama (2001): [11] Smarter scale. Better results. (n.d.). Retrieved December 27, 2015, from [12] Withings. (n.d.). Retrieved December 27, 2015, from [13] Panel, NHLBI Obesity Education Initiative Expert. "Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults." (1998). 143