International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017
p-ISSN: 2395-0072
www.irjet.net
Eating Habit and Health Monitoring System Using Android Based Machine Learning Avinash Palve1,Snehal More2, Shivani Chaudhari3, Akshay Katke4, Kartike Kampassi5 1Professor,
Avinash Palve, Dept. of Computer Engineering, TCOER, Pune, Maharashtra, India. More, Department of Computer Engineering, TCOER, Pune, Maharashtra, India 3Shivani Chaudhari, Department of Computer Engineering, TCOER, Pune, Maharashtra, India 4Akshay Katke, Department of Computer Engineering, TCOER, Pune, Maharashtra, India 5Kartike Kampassi, Department of Computer Engineering, TCOER, Pune, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------2Snehal
Abstract – Now a days, there are many threats to human
health. Nutrition-related diseases are now becoming a dangerous threat to human health. Balancing energy intake and expenditure is crucial step to maintain healthy lifestyle. To collect the acoustic signals during eating and chewing, a wearable device is to be worn around the person's neck . An embedded hardware prototype will collect the food intake data. Signals collected will be processed by the hardware . blue tooth signal will send to Smartphone where food types are recognized. We use hidden Markov models to detect chewing or swallowing events. Developed an application on the Smartphone, which verifies the food intake results and gives relevant suggestions on healthier habits. It notifies the user by giving notification to the user.
3. PROPOSED SYSTEM
Key Words: Health, Signal, Food, Smart phone, Acoustic, Bluetooth etc..
1.INTRODUCTION It is Important to maintain a healthy lifestyle in our day to day life. Daily food intake must be worth neither it may lead to various diseases and other consequences. If proper care isn't taken then severe disorders may become threat. Present solutions to measure calorie expenditure are, such as Fit-bit, Philips Direct Life, etc. However, continuously and non-invasive monitoring on calorie intake remains a challenge. Currently present solutions rely on self-reports, which are not convenient because the food intakes differ from person to person or to different age groups. To develop easy-to-use solution to detect the daily food intake and its expenditure endorse Android Based Healthcare System Using Machine Learning. We propose this system as it is desirable to develop more accurate and more easy methods to monitor the food intake. It is user friendly, easy to use, interactive with any smart phone which can handle it and understand its working in detail properly.
2. RELATED WORK Advances in wearable devices continues to play a major role in improving human healthcare as it provides several opportunities which help to balance food intake and energy © 2017, IRJET
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Impact Factor value: 5.181
consumption. Advancement in wearable devices which help to monitor body organs, movement and action. Many sensors are being deployed in the system to collect the health related data of user. Interpretation of data plays the major role. Real-world degradation of signals are more prone to noise which lowers down the quality of system performance in speech recognition systems. Hidden Markov Model is used for construction of speech components which are spectral whose performance is degraded by unwanted noise. At each step there is discrete state among the number of possible states which are finite. In the frequency domain encoding of speech parameters is done by number of speech analysis.
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Main goal of this Technology is to make user aware of his/her daily food intake. Provide the suggestions according to it. Provide customized suggestions to individual regarding healthier eating habits. Develop an application food recognition results information in a most user-friendly way. Design of an Health Monitoring System which can be interfaced with an android Smartphone. The embedded system give updates the user by using Smartphone regarding its health.
3.1 Body Mass Index and Calorie Intake To measure the daily calorie intake of a person we use one of the most easiest method. The method is to measure your body mass index (BMI). The BMI is a calculation of your weight in relationship to your height.
Calculating your BMI 1. 2. 3.
Measure and record your height(in cm). Measure your weight(in kg). Calculate your BMI by using formula: BMI = Weight (kg)________ / Height (m2) ________ = __________
Result will be either Underweight Normal Overweight Obese. ISO 9001:2008 Certified Journal
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