The majority of IoMT systems operate in the following key layers, which incorporate a vast range of technologies, devices, and sensors that are linked to one another by means of wired or wireless connections [35, 36].

Data sources such as health monitoring gadgets and mobile applications are incorporated with sensors, including infrared sensors, medical sensors, radio frequency identification (RFID) cameras, and sensors are included in the perception layer, which is the lowest stratum of the IoMT (GPS). The sensing systems detect changes in their surroundings, identify objects, locations, demographics, and magnitudes, and then convert this data into computerised data using the assistance of dependable, wired or wireless network communications that serve as a higher-performance transport medium.

As was stated earlier, the sensors need communication with the gateway in order to function properly. This connectivity must be created using networks that are capable of sharing and keeping information centralized. The transmission may take place across a wide range and could have a very short or relatively long range. Examples of short-range communication include radio frequency identification (RFID), Zigbee, and Wireless Fidelity. Examples of wide-range communication include cloud computing, blockchain technology, and so on [37].

Many kinds of gateways are listed below Fig. (2).

Fig. (2). Different types of gateways.

The processing of massive amounts of raw data in order to extract meaningful data necessitates the use of tools that comprise the management service that may function at a faster rate employing analytics, safety precautions, process modelling, and device monitoring.

For secure communication, the Secure Sockets Layer Application Programming Interface (SSL API) is used. It makes it possible to collect information, such as detailed electronic medical records (EMRs), from a patient's sports, the Internet of Medical Things, and smartphone tools. This information is then sent to the cloud, where it can be used to help make decisions about treatment interventions [38].

The analysis of the information and the delivery of application-specific services are the two primary responsibilities of the application layer. The application layer makes use of artificial intelligence (AI) and deep machine learning to analyze EMR data and to monitor changing patterns in the obtained data using a number of daily and weekly plots in order to provide decisions regarding possible diagnoses and treatments.

People are capable of transmitting health information from their houses to other locations, such as their primary care providers or hospitals, using a technology called (IoMT).

For example, remote patient monitoring (RPM) is the use of healthcare tools to communicate data such as blood pressure or oxygen levels from recently released patients to their hospital for assessment through their physicians. This may help to prevent hospital readmissions by identifying problems before they become critical.

When it comes to delivering continued therapy outside of the patient's surroundings, the use of IoMT devices in combination with telehealth may also prove to be advantageous. Personal emergency response systems (PERS), for instance, have the ability to detect potentially life-threatening events like cardiac arrest and immediately contact emergency personnel.

Fig. (3). Impact of IoMT.

On-body consumer IoMT devices are wearable devices to measure health indicators for personal use as well as share them with healthcare practitioners. These devices may be purchased by anybody and are available for purchase online. These devices are not only able to monitor a conventional metric, such as heart rate, but they also have the potential to serve as early warning indicators for health problems that are more serious in nature. For example, the Apple Watch can alert users of abnormal cardiac rates.

It is the usage of IoMT technologies in a larger geographical region. Mobility services, for example, are tools that monitor patients while they are travelling in a vehicle. In the same way, first responders and paramedics use emergency response intelligence systems to keep track of patients' information outside of hospitals.

Community IoMT includes techniques that allow medical care to be given remotely, in addition to on-site and emergency care.

Hospitals must maintain the quality and availability of their medical resources throughout time, as well as understand how workers and patients move across the facility. Healthcare personnel utilise IoMT sensors and other monitoring devices to record all of these interactions so that administrators get a complete view of what is happening.

It is a tool that does not require the patient to undergo any invasive procedures in order to check their blood oxygen saturation. Such data may be applied to measure the health of a patient and discover any abnormalities that may be present. Conditions such as asthma, pneumonia, anaemia, and other lung-related disorders, as well as other conditions, may be detected using a blood oximeter. In clinical applications, the pulse oximetry technique has been shown to be an advantageous characteristic for assessing oxygen saturation. SpO2 is often detected using a sensor connected to the patient's finger. There are two methods for measuring SpO2: transmissive and reflected. The transmissive approach is the more prevalent of the two. Such pulse oximeters work by sending light through the blood in the finger and then analysing differences in light penetration in oxygenated or deoxygenated blood to determine the oxygen saturation in the blood (known as the SpO2 level) (Fig. 3).

MAX30102, invented by Maxim Integrated, is the most extensively utilized pulse oximeter sensor [40].

The rate of the patient's pulse is observed in order to evaluate the state of the patient 's heart. In the event of a crisis, it may be utilized to pinpoint the source of the problem immediately. APDS-9008 is the pulse rate sensor that is used by the greatest number of people. In order to put it to use as a sensor for determining the rate at which the heart is beating, a green infrared LED with low intensity is employed to identify the pulse via the reflection of light that occurs in each heartbeat [41] (Fig. (4).

Fig. (4). Working of pulse oximeter.

To check proper heartbeat and strength, electrocardiogram (ECG) data is essential. It is vital in the detection and management of heart disease. The AD8232 is a popular ECG measuring module that may be used in a variety of applications, such as a heartbeat sensor, as well as a sensor for the ECG, which means that it serves various functions and is thus extensively utilized. The front end of the device may make use of it as a heartbeat sensor. The system incorporates a rapid circuit restoration capability that decreases the amount of waiting time caused by the high pass filter's low cut-off frequency. It also provides an ECG Android app via which users may examine their data for health monitoring reasons [42].

Fig. (5). Functioning of pulse heart sensor.

Patients diagnosed with diabetes are required to make use of blood glucose monitors in order to maintain adequate control over their blood sugar levels. On the market nowadays, one may choose from a number of different blood glucose monitors. They are desirable in an IoT environment [43]. It emphasises the problems of invasive blood glucose monitoring as well as the possibility of contamination from used needles, which might result in infections. With that in mind, their recommended solution is to design a non-invasive blood glucose level measuring tool. The sensor kit for these monitors includes an infrared LED, a photodiode, and an AT-MEGA328 microprocessor. IR radiation is used in this device to measure blood glucose levels. Furthermore, several systems have smart alerting functions that may notify the patient if an abnormality is identified [44]. iGLU is another system. Using an Intelligent Glucose Meter Using near-infrared spectroscopy and machine learning algorithms, this system analyses the data acquired from patients and identifies any irregularities that may be present in that data. These characteristics enable endocrinologists to remotely monitor the patient [45].

The LM-35, TMP236, DS18B20, and MAX30205 are the temperature sensors that are used the most frequently. The DS18B20 is used to determine the patient 's body temperature in a wearable patient monitoring device. The MAX30205 temperature sensor not only gives an exact reading of the temperature but also acts as an overtemperature alert. The MAX30205 is suited for wearable devices because of its high precision and low operating voltage. Furthermore, its digital capabilities facilitate integration with any system.

The LM-35 is most typically employed in wearable sensor networks. It has a huge temperature range compared to the DS18B20 [46].

The Electromyography Sensor, often known as an EMG, is used for the purpose of determining the electrical impulses of the muscles. With the help of this sensor, physicians and other medical experts are able to track nerve and muscle abnormalities in their patients. These sensors are also utilised in devices that are worn by the patient in order to monitor their behaviour. EMG sensors are essential to the development of emotion-based intelligent information sensing systems. These systems use EMG signals in conjunction with other biomedical sensors in order to identify fluctuations in facial muscles and associate each variation with its associated emotion. This approach can identify the patient's impacted condition of health. Advancer Technologies is also developing an Arduino-powered EMG sensor on the market [47].

Significant research has been conducted on non-invasive methods of measuring blood pressure, such as the modern technique known as the oscillometric method [48], which involves compressing blood vessels with the help of an air-inflated cuff in order to obtain readings of systolic and diastolic pressure. The alternative method involves estimating a patient's blood pressure without the use of a cuff. This process is based on many types of biomedical sensors, such as ECG and PPG sensors. Advances in research and study in ECG and PPG signal analysis have resulted in the creation of a system for estimating and evaluating patients blood pressures. Such an approach is advantageous in the long term since it lowers the system's hardware expenses and makes the patients more comfortable [49].

A new system that utilizes Bluetooth Low Energy (BLE) and Wi-Fi, integrating it with IoMT (Internet of Medical Things) technologies to create a sensor patch This system was made up of a multi-ring-shaped sensor. As the volume of liquid increased, the sensor was able to identify leaks. Additionally, the device had a mapping circuit as well as a Bluetooth low energy module. During manufacture, a signal line was included in the insulating layers; however, the only part of the array that was open to the environment was the sensing point. The following three phases comprised the technique from blood leaking to detection: (1) absorption, in which the gauze absorbed the blood, which then diffused to the patch; (2) reaction, in which the blood diffused into the patch, which caused the detection voltage to rise; and (3) saturation, in which the blood could no longer spread and the voltage remained stable [50].

Digital (smart) drugs with integrated IoMT sensors in each tablet may be utilised to assess antibiotic concentrations in bodily fluids and dose tracking will offer more accurate data on treatment effectiveness on a personalized basis [51]. Naik et al. also showed the usage of an ingestible sensor that was designated with a CE-mark in order to evaluate individuals with chronic high blood pressure [52].

Diagnostic tools that are self-powered and linked to the IoMT are currently being developed. These tools have the potential to enable real-time monitoring of biomarkers in bodily fluids such as sweat, urine, blood, and so on. Because of this, it may be easier to distinguish between illnesses caused by bacteria and those caused by viruses. This can be very useful. In addition, the patients' response to therapy may be carefully tracked. This would indicate whether or not the patients is actually responding to therapy and could possibly indicate that resistance is present. [53-63, 37]

Wessels et al. (2021) used complicated neural networks to make a new smart biomarker that can find lymph node metastasis [64].

Testing and tracking are the primary concerns for disease spread management over the globe, especially in order to slow transmission. Several different devices that are based on IoMT have been put to use in order to test and track people who are infected with the illness, as well as to identify the location of patients in order to track the possibility of disease transmission. Infectious disorders such as malaria, dengue fever, influenza A (H1N1), human papilloma virus, Ebola virus disease, Zika virus and coronavirus (COVID-19) may be treated more effectively with the use of point-of-care testing (POCT) devices that are based on IoMT [37] shown in Fig. (5).

Bibi et al., 2020, established an IoMT-based system that allowed for real-time testing that was both fast and secure, as well as the diagnosis and management of leukaemia using cloud computing [65].

Stress and anxiety problems are becoming more widespread in today's society. Poor stress management may result in stress disorders, psychological anguish, and physical diseases. According to preliminary studies, people who recovered from COVID-19 experienced an increase in anxiety problems and other mental illnesses. It is a low-cost anxiety disorder monitor based on IoT that extracts emotion characteristics from physiological measurements in a semi-immersive environment. The data on a user's heart rate and physical activity is gathered by an Internet of Things node and then sent to a Raspberry Pi 3 for preprocessing before being uploaded to an Internet of Things cloud. The results of this system's validation showed that it had an accuracy rate of 90 percent in recognizing anxiety disorders [66].

A seizure is a rapid electrical disruption that occurs in the brain. As a result, it is of the utmost importance to recognize or detect it in a timely manner in order to give appropriate care and therapy to the patients.

An IoMT-based approach may detect seizure onset using a patient's electroencephalography (EEG) data. The system analyses neurological data obtained from an EEG sensor and continually processes it in order to extract hyper-synchronous pulses from the brain. Such information collection is then utilized to identify seizure incidence [67].

Ozone treatment has a distinct benefit due to its simplicity of creation. Ozone may be artificially created (through UV-light) within small portable units carried by the patients, providing for low-dose continuous therapy regimens while minimizing the negative impacts of increased concentrations on normal skin cells [68]. Ozonated air promotes wound healing by subjecting the wound to oxidative stress, which in turn causes a rise in the generation and migration of wound healing components as well as an increase in the amounts of oxygen at the wound site [69]. A wearable ozone production technology would enable patients to get ozone therapy topically outside of a clinical environment. Design, manufacturing, and testing of a portable and wearable platform administer ozone to the wound site locally.

Tele-thermographic systems (TIS) contain an embedded thermal infrared camera with a temperature reference that is able to correctly determine an individual's skin temperature without making any kind of direct physical contact with that person. These easy-to-use technologies that don't need any intervention are quite helpful for detecting elevated body temperatures in heavily crowded locations. Mohammed et al. (2020) used thermal images to detect elevated temperatures associated with coronavirus infection utilising an IoMT-based drone technology [70].

The Raspberry-Pi 3 is used, which is not only inexpensive but also versatile. Information about four of the body's vitals is gathered and shown on the website with a camera that streams live video in order to do a continual examination. For the purposes of live monitoring, there are two different login keys: one is reserved for the physician, and the other is given to the patient's relatives. A message is provided to the physician through the GSM module whenever a sensor detects any instability or abnormality. When physicians see that insulin injections are necessary, they may do it from anywhere by pressing a button, which enables the release of a limited dosage of insulin into the patients [1].