Intelligent and smart sleep behavior monitoring system for patient using IOT

Getting quality sleep is important for every person to get better physical health. Sleep illnesses can be an indication of a disease or may also be a sign of future disease such as depression. For these causes sleep valuation is a vital component of healthiness check but in this age of hectic life,

Project Title

Intelligent and smart sleep behavior monitoring system for patient using IOT

Project Area of Specialization

Internet of Things

Project Summary

Getting quality sleep is important for every person to get better physical health. Sleep illnesses can be an indication of a disease or may also be a sign of future disease such as depression. For these causes sleep valuation is a vital component of healthiness check but in this age of hectic life, it is a challenge to provide quality health care facilities to people with inexpensive instruments and technology. The development of the internet of things technology offer prologues to build reliable and cost-effective system to monitor sleep quality. So we proposed a mechanism through which we can effectively monitor patient’s sleep using commercial off the shelf (COS) sensors. Proposed system work with measuring patient’s bio status and sending this to the computer system. This data includes patients on bed movement, heart rate and snoring patterns. Through this, we can easily measure the sleep patterns of patients and provide them with better treatment by using this simple technique. This study shows that we can implement this easily on any number of population by using this simple technique.

Several devices are also available which are currently used for home-based sleep assessment. Some of these devices are directly available for purchase. The brain comprises of a headband records a single frontal lead EEG. Zeo is another device which consists of an elastic headband with fabric sensor on the forehead which measures electroencephalogram (EEG), frontalis muscle electromyogram (EMG), and electrooculogram (EOG) signals and broadcast signals wirelessly to mobile phone. The Heally system consists of a shirt with a combination of embedded sensors and wired adhesive electrodes that measure respiratory and cardiac physiology, as well as ports for optional EMG and EOG electrodes. The SleepTracker device is a wristwatch that records movement based on actigraphy. WakeMed is a wristband device that transmits actigraphy data to a smartphone to report basic sleep metrics such as total sleep time, sleep latency, number of awakenings, and a “sleep quality” score based on movements.

Nowadays, mobile devices are commonly used in everyday routine. These devices provide several apps and a mechanism to monitor sleep. A system called ubiquitous architecture uses heart rate signals, sound signals and accelerometer data for sleep monitoring. This idea works with combining the monitoring system with a smartwatch and smartphone. This project proposed a novel algorithm for signal management. Ubiquitous architecture is very useful and feasible in sleep monitoring mechanisms.

Project Objectives

Main objective of this project is to develop a cheap and affordable sleep monitoring system through which doctors can determine the patient’s condition of sleep easily. A key objective the proposed study is use of a smart method for monitoring sleep quality with low-cost sensors and technology that helps a patient’s sleep behaviour analysis. The proposed approach will be economical as compared to other sleep monitoring technologies:

The proposed methodology has the following objectives.

• To design an approach that is cost-effective as compared to other technologies of sleep monitoring.
• To use machine learning technique (such as Random Forest) for decision making delivers as much precision as it is essential in the analysis procedure.
• To design and develop a system that is more capable and effective in determining the sleep quality.
• To identify sleeping syndromes using this cost-effective method.

Project Implementation Method

This cost-effective method for sleep monitoring was executed in Rapid Miner. This system implemented in the lab practices the Arduino mega (2560) controller as a central microcontroller. This controller takes data from sensors in real-time and forwards the data to the random forest model. This model is fundamentally on the main computer which is attached to the microcontroller. A brief explanation of the sensors and techniques used in this approach is below.

Proposed Hardware for Implementation:

The projected sleep monitoring technology use different sensors to collect data from the patient’s body. For body movement, we used ADXL345 accelerometer which perceives the physical movement of the body. For heartbeat and SPO2 level, we used pulse oximeter and heart rate sensor module MAX30100. For snoring detection, we have used the MAX9814 Microphone Amplifier. Detail of these sensors is given below.

ADXL345 Triple Axis Accelerometer module: This sensor is used to perceive physical body movement of a human being. It offers improved readings than other accelerometers. It is simple and easy to use. It is also a cost-effective sensor which is certainly available in the market. Following are the main features of the ADXL345 sensor module.

MAX30100 Pulse oximeter and Heart Rate Sensor Module: The MAX30100 is a combined pulse oximeter and heart rate monitor sensor solution. It combines two LEDs, a photodetector, improved optics, and low-noise analogue signal processing to perceive pulse oximeter and heart-rate signals.

MAX9814 Microphone Amplifier: The MAX9814 is a low-cost, high-quality microphone amplifier with automatic gain control (AGC) and low-noise microphone partiality. The device features a low-noise preamplifier, variable gain amplifier (VGA), output amplifier, microphone-bias-voltage generator, and AGC control circuitry.

Benefits of the Project

• Seminars, advertisements, and literature will be used for commercialization of the product and to communicate benefits to the end-user.
• A booklet will be provided along with wound care app commercially in which environmental factors role in wound healing will described for awareness of end-user.
• An android base wound care app will be commercially available for patients to monitor wound healing at their home.

Technical Details of Final Deliverable

Project will result in an IOT based monitoring system which consist of sensors and a mobile application which can be easily used on mobile phones in hospitals to monitor patient’s sleep conditions.

• Physically connected devices will generate data for classification. Which will result in identifying the sleep patterns of patients.
• Resulting Random forest model can be used for diagnosing of patients for different psychological patients.
• Resulting model will provide deep knowledge of patient’s sleep
• Resulting model provide easy to use and implement methodology of sleep analysis.
• Higher accuracy will provide more accurate diagnosis of patient’s problem.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

IT

Other Industries

Health

Core Technology

Internet of Things (IoT)

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com