Smart Systems for Industrial Applications

Figure 1.5 Wearable devices in the health monitoring system (Adopted from [21]).

Since the nodes are placed inside and outside the human body, it requires less power consumption as the devices are battery operated. So, it is essential that for the battery to work longer, power consumption should be less. As communication deals with bio-signals in the medical field, the Quality of Service (QoS) plays an important role. So, the user can detect proper information and treat accordingly.

As the network deals with information transmission related to vital parameters of human beings, the security of data is critical to avoid unauthorized accessibility. In the case of biosensors, the threshold value is set. So, if any parameter increases or decreases below the threshold value, then it generates an alarm, so fewer false alarms are required. Wireless Medical Telemetry Service (WMTS) and UWB are technologies that are used for body monitoring systems because of their low transmission power.

In this section, we discuss the architecture of WBAN, which is divided into the three-stage process to depict the working mechanism of WBAN as shown in Figure 1.6[25].

Stage 1: Intra sensor communication

The communication among the sensors around the human body is considered in this stage. A personal server acts as a gateway, which is used by communication signals within the human body. Gateway transfers the data to the next stage of architecture.

Stage 2: Medium

This stage enables the data transfer between the personal server and user through an access point, which is considered as a central unit of the network, which can make decisions in case of emergencies.

Figure 1.6 Architecture of WBAN communication.

Stage 3: Beyond WBAN

Smartphones are used to interlink between the access point and medical server, in which patient historical data could be stored. The medical environment database is a very sensitive part of stage 3. Security against this stage is fulfilled to protect the personal history of the patients.

Internal communication among the sensors and measured parameters from the human body are processed using deep learning algorithms. AI-based data processing models analyze massive amounts of data from the sensors and extract useful information from them. Figure 1.7shows the role of AI in WBAN. The extracted features are used to diagnosis the disease, wherein the proposed model is trained with related data. CNNs are used for feature extraction; based on the inputs, CNN generates the possible, reliable outputs.

Figure 1.7 AI-enabled WBAN architecture.

WBAN technology improves the efficiency of the activities from patient to doctor, like monitoring the patient’s health regularly and notifications or emergency calling in a flexible way. It offers automatic medical services through remote monitoring of the patient’s vital parameters. All the information is stored from the control unit. It helps the patient to stay at home and get continuous support remotely. In case of any emergency, the sensors implanted in the patient’s body raises the alarm of urgent notification, which will be notified by nearby healthcare provides healthcare services over a distance with the help of communication technology. This can be done by online video consultation with doctors, the transmission of reports and images, and remote medical diagnosis. E-prescription is provided after monitoring the patient’s health conditions. Pulse oximeters are used to measure the amount of oxygen level in the blood bypassing the beam of red and infrared into the human body. Color differentiation is the fundamental concept of oximeters; oxygenated blood is more red, where deoxygenated is purple-blue.

In non-medical applications, WBAN is used in sports where devices can be wearable. It is effective to monitor the physiological activities of the wearer like heart rate, temperature, blood pressure, and posture of any attitude in sports. Navigation, timer, and distance can also be measured with the help of WBAN sensors.

Medical sensors are used to monitor a patient’s body continually and collect information so they should be active all the time; hence energy consumption is high. In body communication, sensors are implanted in vital areas of the body, so if the batteries are consumed fully, the patient has to undergo body surgery to replace a new one. Since the collection of data requires more energy than sending data through wireless time out Mac protocol, which is used in WBAN. Transmission of data is affected by jamming, bit error rate, and link quality. This can be minimized by using Cooperate Network Coding (CNC) since it does not require any retransmission when there is any failure in any of the nodes.

Table 1.4 Role of AI in wireless body area networks.

The major challenge is the security and privacy of the patient’s medical information. Data confidentiality should be maintained to avoid unauthorized access. So, to make sure that the data is sent by appropriate user authentication is necessary. It is also essential to see that received data is not manipulated so that data must be protected for proper medical diagnosis.

The applications and impact of WBAN in healthcare are summarized in Table 1.4.

Healthcare providers around the world are a huge source of data, starting from patient history to drug trials. With digitization as a backdrop, many of these records are converted into electronic forms enhancing its utility and enabling vital care decisions. This data has innumerable applications like reviewing the past, understanding the current, and helping predict future trends in the healthcare of patients. AI algorithms, when paired with healthcare data, can drive remarkable insights into intelligent reasoning, quicker analysis of data, provide informed acumen into patient’s healthcare and even extend into decisions on investments in healthcare infrastructure.