EHEALTHCARE ASSISTANT

The project focuses on improving healthcare in developing countries using low power, economic electronics such as the Raspberry Pi (Rpi). As the age profile of many societies continues to increase, in addition to the increasing population of people affected by chronic diseases, including dia

Project Title

EHEALTHCARE ASSISTANT

Project Area of Specialization

Internet of Things

Project Summary

The project focuses on improving healthcare in developing countries using low power, economic electronics such as the Raspberry Pi (Rpi).

As the age profile of many societies continues to increase, in addition to the increasing population of people affected by chronic diseases, including diabetes, cardiovascular disease, obesity, and so on, supporting health, both mentally and physically, is of increasing importance if independent living is to be maintained. Sensing, remote health monitoring, and, ultimately, recognizing activities of daily living have been a promising solution. From a technical perspective, the Internet of Things (IoT) is gaining a rapidly growing attention in many disciplines, especially in personalized healthcare. Meanwhile, body area sensor network (BASN) under the IoT framework has been widely applied for ubiquitous health monitoring, for example. ECG monitoring has been commonly adopted as vital approach for diagnosing heart disease. The WISE (Wearable IoT-cloud-based health monitoring system), for real-time personal health monitoring. WISE adopts the BASN (body area sensor network) framework in the support of real-time health monitoring. Several wearable sensors have been embedded, including the heartbeat, body temperature, and the blood pressure sensors. Secondly, the majority of existing wearable health monitoring systems requisite a smart phone as data processing, visualization, and transmission gateway, which will indeed impact the normal daily use of the smart phone. Whilst in WISE, data gathered from the BASN are directly transmitted to the cloud, and a lightweight wearable LCD can be embedded as an alternative solution for quick view of the real-time data.

Here in our mobile app / website there are 7 tests to help you quickly and easily know if it's time to have a more detailed eye examination with a vision care professional.

Using devices such as the Raspberry Pi, we aim to help create a system where data can be transported between remote locations, where internet connection is limited - a physical network of sorts, if We may.

The system utilizes 3 key components:
1. Nodes that gather data in the field. These are Rpi's used in small clinics in rural towns. Each clinic can have a node, or on a larger scale, each hospital room/wing could have a node. The node is connected to sensors such as heart monitors, blood pressure monitors, etc. We believe we can use biometric sensors, the security of the Helium platform and strength of block chain technology to surface possible anxiety states I only had access to a webcam, so I have modelled this as a sensor to monitor patients’ movement.

2. Hubs that collect all the data from different nodes and upload it online. The hub is located in a major city with internet access.

3. Block Chain Technology - This is where the data is uploaded and processed. An upcoming technology in the Internet of Things.

Project Objectives

eHealth Innovation will develop consensus among stakeholders and produce a detailed eHealth Innovation report towards making interoperable eHealth services deployed at large scale in World, thereby also supporting patients in managing their health.

The resulting requirements for a supportive infostructure and for further innovation measures are further objectives.

The eHealth Innovation TN addresses four main thematic areas

Chronic disease management for an ageing population

Work in this area will focus on identification of good practice and innovative solutions, including reviewing different models of sharing care and management decisions with patients.

From integrated care towards co-production of health

Work in this area will focus on cooperation between patient and health professionals and include topics such as improved information and communication, patients' access to their health data, improved care and care coordination through electronic patient records (EPR), personal health records (PHR) and personal health systems (PHS).

eHealth solutions for patient-centered care

Work in this area will focus on support for patients in managing their health and includes topics such as Personal Health Systems (PHS), Personal Guidance Systems (PGS, part of PHS), chronic disease management (CDM) and integrated care (IC) that goes beyond contemporary models of chronic disease management. This thematic area will focus on innovative solutions and lessons learnt from implementation to be used in the final report.

EU-wide eHealth infostructure

Focus will be on the need for and creation of an information and knowledge infrastructure based on and further supporting the development of existing national infrastructures, and facilitating patient care, public health, health research, health education, (self-)health management. The topics to address in this work domain include questions of semantic interoperability, advanced EHR based solutions, interfaces to the infostructure, knowledge generation (e.g. from patient monitoring) and feedback to patients (and doctors) as well as data re-use.

All mentioned thematic areas will have to deal with issues surrounding the efficient engagement of individuals in managing their health, improved, interactive communication, shared healthcare, improved care coordination

• The user can have an online appointment to the doctor and doctor can recieve his fee through online transaction or may be doctor not charge.
• The doctor can interact with user through video chat in our mobile app and website and all the stats ot the user from can be seen by the doctor and user runtime condition can be seen also by the same sensors.
• The doctor can prescribe them the medicine online through challan which user can download at home and buy medicine from market.

Project Implementation Method

We represent a framework of the Wearable IoT-cloud-based health monitoring system (WISE), which adopts a number of interconnected wearable sensors to observe the health condition of the subject. A set of biomedical signals can be obtained, including the blood pressure, the heartbeat, the body temperature, pulse, sugar level, anxiety level etc. Due to the limited memory and computing capacity of the sensor nodes, as well as to avoid the adoption of a smart phone as a processing unit, the sensor data collected from those wearable sensors will be transmitted to the cloud server directly. The WISE system contains three fundamental components which are the WISE body area network (W-BAN), the WISE cloud (W-Cloud), and the WISE Users.

The WISE is developed based upon Arduino sensor platform integrated with the abovementioned sensor nodes. In addition to the sensors that embedded in WISE, several components are adopted as well. Firstly, a portable RFID reader is connected to the Arduino platform, which facilitates the identification of different users, thus a RFID tag should be amounted to each individual user. A lightweight LCD is included as an alternative option for the user to access the data. Furthermore, WISE is also empowered with a Wi-Fi module, which enables the transmission of the data to the cloud and then allows the authorized users to access the real-time data from anywhere at any time

The implementation of the WISE-Cloud is based upon a HTTP server and a storage server that of the MySQL database. A web-based GUI is developed; an example of the interface that displays the real-time heartbeat and body temperature data is depicted in Fig. 6. Once the power supply is given, the temperature from the thermistor and heart rate from the pulse meter sensor are determined. Same information is uploaded to the WISE-Cloud database server, and then displayed on the webpage in real time. A similar mechanism is also applied to the blood pressure sensor and data. Such information is fundamental for users to self-monitor their health condition, and for doctors to diagnose potential diseases. If any abnormal condition is detected, an alert will be generated to a certain stakeholder, which include a text message to the doctors or family members, and an alert is displayed on the LCD for the users themselves.

Furthermore, long-term historical data can also be visualized on the cloud, which demonstrates the heartbeat and body temperature data for a period of a few weeks for a particular user. In addition, the similar approaches are also adopted for the blood pressure sensor data.

Data mining module is the key component for diagnosis of heart disease. After extracting valuable features from the heartbeat and body temperature data, machine learning-based approaches are applied, such as SVM and neural network, to establish the decision models.

Authorized users can log in to the cloud server to visualize the data from the web.

Benefits of the Project

A need for real-time health and activity recognition with wearable sensors is a prerequisite for assistive paradigms. We present a brief overview of existing health and behavior-monitoring approaches based on wearable IoT technologies. The Device measures several parameters and sends the combinations securely via our Helium Channel to Google Cloud for analysis. We can then visualize the interpreted results and flag patterns that we believe match a state of Anxiety. Secondly, it illustrates a novel health monitoring system framework WISE, which enables the real-time monitoring of the patients or elderly users and allows the information to be accessed from the cloud. By taking this concept on a product journey we would be able to provide direct benefits to the individuals and careers and system benefits for government and health organizations. The project focuses on improving healthcare in developing countries using low power, economic electronics such as the Raspberry Pi (Rpi). Using devices such as the Raspberry Pi, we aim to help create a system where data can be transported between remote locations, where internet connection is limited - a physical network of sorts, if we may.

• The user can be notified about his/her condition.
• If user is in alarming condition than he/she will be refered to the doctor online.
• The user can have an online appointment to the doctor and doctor can recieve his fee through online transaction or may be doctor not charge.
• The doctor can interact with user through video chat in our mobile app and website and all the stats ot the user from can be seen by the doctor and user runtime condition can be seen also by the same sensors.
• The doctor can prescribe them the medicine online through challan which user can download at home and buy medicine from market.
• So in this way user or patient can get his treatment from home not even travelling to clinic.
• Another benefit is this device will be implemented in rural areas in health care center where poor people can get the checkup from the doctors belonging to cities without moving to the cities creating a node which connects to hub which is our city.

Technical Details of Final Deliverable

The W-BAN consists of different categories of sensors which are elaborated as

The heartbeat sensor data indicates the regularity of the heartbeats, which can also reflect the myocardial activities. Such sensors have been commonly applying for monitoring patients with heart disease

The temperature sensor in the circuit will read the temperature from the surroundings and shown the temperature in Celsius (degrees).

The blood pressure sensor is a non-invasive sensor designed to measure human blood pressure. It measures systolic, diastolic, and mean arterial pressure utilizing the oscillometric technique

Galvanic skin response (GSR), is a method of measuring the electrical conductance (Actually resistance!) of the skin. Strong emotion may cause stimulus to your nervous system, resulting more sweat being secreted by the sweat glands. 

Heart rate is a critical indicator of many physical and mental conditions. Anxiety is generally likely to result in faster, or irregular Heart rates.

Gulco Meter will measure the sugar level of the body.

Brain Emissions

The Human Brain is an amazing and complex organ that has been studied and marveled for centuries. Significant Electroencephalography (EEG) research has repeatedly shown that the brain produces low frequency emissions that vary in frequency and amplitude according to activities and mental state. A very high-level overview generally categorizes these frequencies into five distinct bands.

0.5-4 Hz: Delta waves are associated with deep sleep and are known for triggering healing and growth hormones, hence the reason why sleep is so important!

4-8 Hz: Theta waves apparently occur mainly in children during early sleep stages, in emotionally stressed adults, or are somehow involved with learning and navigation

8-13 Hz: Alpha waves occur when a person is relaxed, but alert

14-30 Hz: Beta waves occur when a person is focused, alert and engaged

above 30 Hz: Gamma waves are associated with sensory perception or perception of consciousness. Considerable research is still being done on all of these.

We measure Brain emissions using the innovative Neurosky Mindwave Mobile 2 Headset, which uses a TGAT Application Specific Integrated Circuit (ASIC) to perform Network edge calculations prior to our Helium Channel Transport. We found Neurosky incredibly helpful to us, and they have an excellent set of Developer tools to enable Arduino connectivity.

Headset connectivity is achieved via Bluetooth at 57600 baud. This is accomplished by pairing a BlueSmirf Module with the Headset, restarting, and then piping all RX / TX direct between the Mindwave Mobile 2 and the Arduino/Atom.

Final Deliverable of the Project

HW/SW integrated system

Type of Industry

Medical

Technologies

Internet of Things (IoT), Blockchain, Wearables and Implantables

Sustainable Development Goals

Good Health and Well-Being for People, Industry, Innovation and Infrastructure, Sustainable Cities and Communities, Partnerships to achieve the Goal

Required Resources

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