Health Monitoring System For Rett SyndromeInternet-Of-Things (IOT) Sensing and Cloud Based ProcessingMonisha Gor#1, Shweta Patil#2, Sagar Pednekar#3Student, Final year, Department of Computer Engineering, K.J. Somaiya College of Engineering,Vidyavihar, University of Mumbai, Maharashtra, India#[email protected], #[email protected], #[email protected]—Rett syndrome (RTT) is a severe neurodevelopmental disorder which includes pervasive wakeful respiratory disturbances that include tachypnea, breath-holding, and central apnea. As 60% of the RETT Syndrome patients die due to breath holding, therefore it comes very important to focus on this respiratory disturbance. Health monitoring system will detect the breath-holding disorder in the patient and will also alert the caretaker about patient’s condition. Prediction of such apnea could be done with the help of the previous data stored on the cloud and this prediction will also be alerted to the caretaker. The user will have an access to an android application will help distract the user.Keywords—IOT, Health Monitoring, RETT Syndrome Introduction Rett syndrome is a rare, severe neurological disorder that affects mostly girls. It’s usually discovered in the first two years of life, and a child’s diagnosis with Rett syndrome can feel overwhelming. Although there’s no cure, early identification and treatment may help girls and families who are affected by Rett syndrome. In the past, it was felt to be part of the Autism Spectrum Disorder. Rett syndrome (RTT) is a rare disease but still one of the most abundant causes for intellectual disability in females. Typical symptoms are onset at month 6–18 after normal pre- and postnatal development, loss of acquired skills and severe intellectual disability. The type and severity of symptoms are individually highly different. A single mutation in one gene, coding for methyl-CpG-binding protein 2 (MECP2), is responsible for the disease. The most important action of MECP2 in regulating epigenetic imprinting and chromatin condensation, but MECP2 influences many different biological pathways on multiple levels although the molecular pathways from gene to phenotype are currently not fully understood. Apnea attacks is one of the disorder observed in RETT Syndrome patients. Apnea in medical terms refers to absence of breathing(respiration). This attack can be detected by using body temperature, blood pressure and oxygen level in the blood.Therefore a device could be build to detect the apnea and the caretaker could be alerted using a alerting system.Health Monitoring System basically monitors the health of rett syndrome patients with the help of the hardware device and also has a alerting system which would alert the caretaker about the patient’s condition. In this system the main disorder of rett syndrome which is breath holding is been detected with help of the hardware device and alert is been sent to the caretaker. The continuous monitored data is stored on cloud for further analysis and prediction.The system also provides an android application which helps in preoccupation of patient’s mind. This application also has the feature of remuneration which acts as a delightment to the patient when he/she might complete some task given.Literature ReviewThe existing systems serve only a particular requirement i.e. they only provide service for a particular symptom like, Robotic Biomarkers in RETT Syndrome evaluates only the stiffness of the patient. The persons with RETT syndrome tolerated the evaluation and that a robotic biomarker might be a useful clinical tool to determine the impact of medical interventions in these youngsters.Classification of Respiratory Disturbances in Rett Syndrome patients monitors only the respiratory functions of the patient. The autocorrelation features taken from the respiratory inductance plethysmography chest signal are proposed in the system.ScopeCentralized Alerting system which would alert the caretaker about the patient’s condition. The health monitoring system would monitor all the patients in the ward and whenever a patient gets a traumatic attack it would be alerted to patient’s caretaker.Hardware Module which include sensors to monitor patient’s body pressure and detect breath holding in the patients.A cloud based processing system to analyse the patient’s condition and also predict patient’s condition on the basis of previous history of the patient.A android based application which would have the following features:Distracting user when breath holding is detected by popping up random things on the screen.Reward for the user if he/she completes some tasks.Minimal learningMethodologyThe Proposed System provides monitoring of the rett syndrome patient over the internet continually. The system includes a patient, an analyzation unit with various sensors and devices, cloud for data storage and a caretaker with a network connection. The system functionality is divided into three modules 1) Sensors 2)Analyzation Unit 3)Alerting Unit.1) Sensors: Sensing module is used to perceive the physical state of the rett patient by continually sensing the health data from patient. This data includes temperature, heartbeat and oxygen level.This perceived data then transmitted from the sensors to the analyzation unit. 2)Analyzation Unit: This is a centralized unit. It continually monitors the patient’s health data in order to detect the breath holding condition. whenever a rett patient holds his/her breath his pulse rate starts to decrease. The analyzation Unit identifies breath holding condition by comparing the current pulse rate data with a particular threshold value which would be set earlier in the device.3)Alerting Unit: The health monitoring system would monitor all the patients in the ward and whenever a patient gets a traumatic attack it would be alerted to patient’s caretaker.The Alert will be sent through GSM SMS service on caretaker’s mobile phone comprising patient’s health related data. The system also provides an android application which will notify the caretaker whenever the patient starts breath holding. Figure 1 shows the architecture of our IOT based health monitoring system.The proposed system consist of different health monitoring sensors to sample the physiological signals of the patient1. Heartbeat Sensor – It is a Arduino based plug-and-play sensor for calculating heart-rate. The heartbeat sensor is based on the principle of photoplethysmography. According to this principle, the changes in the volume of blood in an organ is measured by the changes in the intensity of the light passing through that organ. This technique is used to measure heart rate since change in blood volume is synchronous to heartbeat. The heartbeat sensor gives the output in the form of Beats per Minute (BPM) when a finger is placed inside it.2. Temperature Sensor – This sensor is used to measure the temperature. A temperature sensor is a device, typically, a thermocouple or RTD, that provides for temperature measurement through an electrical signal. A thermocouple (T/C) is made from two dissimilar metals that generate electrical voltage in direct proportion to changes in temperature. An RTD (Resistance Temperature Detector) is a variable resistor that will change its electrical resistance in direct proportion to changes in temperature in a precise, repeatable and nearly linear manner.