Internet of Things in Business Transformation. Группа авторов
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list for critical care is as follows:
1 Pulse
2 Temperature
3 Blood Pressure
4 Respiratory Rate
5 Oxygen Saturation
Pulse sensor was chosen as it measured the most important parameters from the human body and thus ideal to be used in a wearable. The system is now modularized to incorporate new sensors [5].
2.3 System Architecture
Hardware Components:
The main hardware components used are:
Pulse Sensor—Pulse Sensor heart rate sensor for Arduino and Arduino compatible boards. It adds amplification and noise cancellation circuitry to the hardware. It’s noticeably faster and easier to get reliable pulse readings. Pulse Sensor works with either a 3 V or 5 V Arduino. A Color-Coded Cable, with a standard male header connector. As we know that the ear lobe and the thumb are the most sensitive areas in the human body, we attach the sensor using the ear clip to the ear lope or using the Velcro we attach it to the thumb of the user. There is a small camera placed in the sensor along with an infrared sensor. Infrared sensors work on the principle of reflected light waves. Infrared light reflected from objects. The reflected light is detected and then the BPM (Beats per Minute) is calculated [6].
Figure 2.1 Hardware components.
Figure 2.2 Pulse sensor connection.
LinkIt One—It is a high performance-development board. It provides similar pin-out features to Arduino boards, making it easy to connect various sensors, peripherals, and Arduino shields. LinkIt One is an all-in-one prototyping board for IoT/wearable devices. The advantage of using this board is that it has inbuilt GSM, GPRS, Wi-Fi, GPS, Bluetooth features. It also has a Lithium ION battery which will ensure the board can be used without being connected to a socket always. This is a very important feature for us as this will not restrict the user’s movement. The users are free to move around with this board unlike other boards (Figure 2.3).
Proposed System: The proposed automatic, IoT system is used to monitor the patient’s heart rate. It is also used to display the same in the form of an ECG (electrocardiogram). The system has the parts:
1 Sensing Sub-System
2 Data Transfer Sub-System
3 Data Display Sub-System
1. Sensing Sub-System
This comprises of the pulse sensor and the LinkIT One. The Pulse sensor is worn on the tip of the thumb or on the tip of the ear lobe (using and ear clip) as these are sensitive parts. It sends pulse signals to the LinkIt One. The LinkIt One performs the programmed operations on the signal and calculates the Inter-Beat Interval (IBI) and hence the beats per minute (BPM). The connections for the Sensing sub-stem are (Figure 2.2): the pulse sensor, ear clip and Velcro (Figure 2.4).
Figure 2.3 The LinkIt One Board.
Figure 2.4 Pulse Sensor kit
2. Data Transfer Sub-System
In this sub-system, using the Wi-Fi module, provided on the LinkIt One, NodeJS runs on the LinkIt One. As the data is collected from the users, this encrypted data is chunked and transmitted to the server. The data is obtained via a periodic fetch. The LinkIT One uses the high performance Wi-Fi MT5931 which is said to provide the most convenient connectivity functions. It is of small size and low power consumption and the quality of the data transmission is very good. We use a MSSQL database to store the data. The advantage of the above is that it can be used in areas with weak Wi-Fi [7].
3. Data Display Sub-System
This sub-system consists of a cross platform app (Android and iOS) which is used to present the data to the doctor. The data is stored on the database which is retrieved onto the app and the data is plotted onto a dynamic plot and is represented as a graph in the doctor phone. If the patient’s parameters go below or beyond the medical parameters then an immediate message is transferred to the doctor, ambulance and patients relatives. We wanted this to be user friendly and hence we designed a cross platform app. Here to secure the data of a particular patient we use MQTT protocol. MQTT is a connectivity protocol. It is an extremely lightweight publish/subscribe messaging transport. It is useful for connections with remote locations where a small code footprint is required and/or network bandwidth is at a premium. Here, it has been used in sensors communicating to a server, request connections with healthcare providers. It is also ideal for mobile applications because of its small size, low power usage, minimized data packets, and efficient distribution of information to one or many receivers.
In the app we have implemented Google OAuth. The confidentiality of each patient is maintained and only the doctor treating the given patient can access his/her details. The app has a framework as follows (Figure 2.5).
The basic flow is as follows (Figure 2.6).
The doctor can sign-in using their Gmail account as depicted (Figures 2.7 and 2.8).
The doctor can view and access his available options (Figure 2.9).
Post login there is a patient-list view page. Here, all the patients the doctor treat are given and can be easily accessed. The list will be provided as follows (Figure 2.10).
The doctor can also input the patient’s ID in a ‘Search ID’ search bar for quicker access of the data. He can also upload a patient’s data the same way. He can select ‘View Details’ to view the details of the given patient as follows (Figure 2.11).
Figure 2.5 Sign-up flowchart.
Figure 2.6 Basic flow.