| Literature DB >> 33986824 |
Carlos A Tavera1, Jesús H Ortiz2, Osamah I Khalaf3, Diego F Saavedra1, Theyazn H H Aldhyani4.
Abstract
In recent times, there has been a significant growth in networks known as the wireless body area networks (WBANs). A WBAN connects distributed nodes throughout the human body, which can be placed on the skin, under the skin, or on clothing and can use the human body's electromagnetic waves. An approach to reduce the size of different telecommunication equipment is constantly being sought; this allows these devices to be closer to the body or even glued and embedded within the skin without making the user feel uncomfortable or posing as a danger for the user. These networks promise new medical applications; however, these are always based on the freedom of movement and the comfort they offer. Among the advantages of these networks is that they can significantly increase user's quality of life. For example, a person can carry a WBAN with built-in sensors that calculate the user's heart rate at any given time and send these data over the internet to user's doctor. This study provides a systematic review of WBAN, describing the applications and trends that have been developed with this type of network and, in addition, the protocols and standards that must be considered.Entities:
Year: 2021 PMID: 33986824 PMCID: PMC8093056 DOI: 10.1155/2021/5574376
Source DB: PubMed Journal: Comput Math Methods Med ISSN: 1748-670X Impact factor: 2.238
Figure 1Comparison between WBAN and other networks.
OSI model for a WBAN.
| Media access control and security | ||
|---|---|---|
| Physical layer (PHY) narrow band (NB) | Ultrawide band (UWB) | Human body communications PHY (HBC) |
Figure 2WBAN communication architecture.
Table 2 is reproduced from Movassaghi et al. [15], [under the Creative Commons Attribution License/public domain [15]].
| Human body communication | |
| Frequency | Bandwidth |
| 16 MHz | 4 MHz |
| 27 MHz | 4 MHz |
| Narrowband communication | |
| Frequency | Bandwidth |
| 402–405 MHz | 300 KHz |
| 420–450 MHz | 300 KHz |
| 863–870 MHz | 400 KHz |
| 902–928 MHz | 500 KHz |
| 956–956 MHz | 400 KHz |
| 2320–2400 MHz | 1 MHz |
| 2400–2438.5 MHz | 1 MHz |
| UWB communication | |
| Frequency | Bandwidth |
| 3.2–4.7 GHZ | 499 MHz |
| 6.2–10.3 GHz | 499 MHz |
WBAN applications according to IEEE 802.15.6.
| WBAN applications | |||
|---|---|---|---|
| Medical | Nonmedical | ||
| Wearable WBAN | Implantable WBAN | Remote control of medical devices | |
| Asthma. | Cancer screening. | Telemedicine systems. | Entertainment applications. |
Different WBAN applications.
| Reference | Aplicación | Contribution | Medical | |
|---|---|---|---|---|
| Wearable WBAN | Remote control of medical devices | |||
| [ | It uses Bluetooth communication to measure body temperature, heartbeats, and possible falls. | It implements power by solar energy. | x | |
| [ | It uses a GSM module to send heartbeat and body temperature information. | Optical sensor. | x | |
| [ | Maintains constant measurement of different medical patient parameters. | System with first aid assistance instructions. | x | |
| [ | It uses an ARM7 to determine the patient's heart condition. | Uses the android platform to communicate the system with the doctor. | x | |
| [ | It measures the person's heart rate, blood pressure, temperature, and breathing. | It uses a GSM modem to send the information to the doctor. | x | |
| [ | Assesses patient vibrations to determine whether the patient suffers from Parkinson's disease (PD). | The system makes it possible to determine the evolution of the disease. | x | |
| [ | It uses sensors on the cellular phone to analyze the patient's gait and determine if the patient suffers from PD. | Implement a smartphone, database, and web application. | x | |
| [ | It measures the kinematics of the patient's gait to determine if they have PD. | Implement sensors in the lower limbs and upper body. | x | |
| [ | Sensors placed on the soles of the feet to determine whether the patient suffers from PD. | Mobile application was implemented to monitor the patient. | x | |
| [ | Sensors in the lower body to determine whether the patient suffers from PD. | It uses ZigBee technology and protocols. | x | |
| [ | Implementation of inertial sensors to determine whether the patient suffers from multiple sclerosis. | — | x | |
| [ | EEG sensor for assessing different brain activities. | Uses ensemble classifier for epileptic seizure detection for imperfect EEG data. | x | |
| [ | System for real-time detection of epilepsies. | The sensor medium access control (SMAC) protocol is used to reduce delays in the time for sending information. | x | |
| [ | Clock sensor for detecting epilepsies in real time. | — | x | |
| [ | Clock sensor for monitoring seizures in real time. | Implement communication through the cloud. | x | |
Implantable WBANs and nonmedical applications were not considered.
Summary of filtered articles.
| Keywords | Year and type filter | Title | Abstract | Chosen | |
|---|---|---|---|---|---|
| IEEE | 750 | 572 | 84 | 76 | 18 |
| Springer | 2,415 | 678 | 51 | 40 | 10 |
| ScienceDirect | 1,107 | 900 | 34 | 10 | 6 |
| Total | 34 |
Wearable WBAN applications in health.
| Reference | Sensors used | Pathology or type of measurement | Communication method | Sensor reliability | Errors when sending data | Security | Energy saving | Real-time |
|---|---|---|---|---|---|---|---|---|
| [ | Biompedance | Chronic kidney disease | Bluetooth | X | ||||
| [ | MEMS inertial sensors [ | Osteoporosis, osteoarthritis, dementia, Alzheimer's, Parkinson's | Bluetooth | X | ||||
| [ | Heart sound sensor | Cardiovascular disease (CD) | Bluetooth 4.0 | X | ||||
| [ | Flow, accelerometer, microphone, strain, skin impedance, ECG, pulse, VOC, ozone, humidity/temp | Chronic respiratory disease | BLE | X | X | |||
| [ | ECG, accelerometer [ | CD | NFC | X | X | |||
| [ | ECG signal monitoring | CD | Bluetooth 4.0 | X | ||||
| [ | Capacitive electromyography (CEMG) | Chronic inflammatory myopathies | Wire | X | ||||
| [ | Microsoft Band [ | Autonomic Dysreflexia (AD) | Bluetooth | X | ||||
| [ | Inertials and carbon dioxide concentration detection device | Respiratory disorders | Wire | |||||
| [ | Inertials, magnetometer | PD | Bluetooth | |||||
| [ | Any ECG sensor | Cardiac care | Bluetooth/wifi/3G | X | X | |||
| [ | Near infrared spectroscopy (NIRS) | Cerebral vascular diseases (CVDs) | Bluetooth | X | ||||
| [ | ECG | CD | BLE | X | ||||
| [ | ECG | Sleep apnea | BLE | X | X | |||
| [ | Light-based sensor | Daily blood pressure measurement | WIFI | X | ||||
| [ | Humidity capacitance | Irregular respiratory diseases | Bluetooth | X | ||||
| [ | Heart rate, temperature sensor, pressure | Physical parameters | WIFI | X | ||||
| [ | Photoplethysmogram (PPG), ECG | Arising heart disease and stroke or any emergency condition | WIFI | X | ||||
| [ | ECG, accelerometer | Sleep apnea syndrome (OSAS) | Bluetooth low energy (BLE) | X | ||||
| [ | Heart rate, temperature, blood pressure | Continuous supervision | Bluetooth | X | X | X | ||
| [ | Pressure system | Chronic venous disorder | Bluetooth | X | ||||
| [ | Measurement units | Breathing frequency monitoring | BLE | X | ||||
| [ | ECG | Long-term homecare | ZigBee | X | X | |||
| [ | Inertial sensors | Home monitoring of motor fluctuations in PD | BLE | X | ||||
| [ | ECG | Telemonitoring and cloud | NRF24L01 | X | X | |||
| [ | EMG device | Masticatory muscle activity | BLE | X | ||||
| [ | Pulse oximetry | Sleep apnea detection | WIFI/Bluetooth | X | X |
WBAN trends.
| Reference | Application | Novelty | Sensors |
|---|---|---|---|
| [ | Long-term continuous medical monitoring | Autonomous system, by means of solar energy | Inertials, temperature, and pulse |
| [ | PD | Holistic system | Microsoft band, speech analysis, finger tapping |
| [ | Classification of physical activity | Classification method using smartphones | Inertial |
| [ | Peripheral artery disease | Passive wearable skin patch sensor measures | Electromagnetic resonant sensor |
| [ | Detection of abnormalities, as well as intrusions, such as forgery, insertions, and modifications in the ECG data | Identify anomalies in ECG signals | Dataset |
| [ | Proposal for emergency classification transmission | Priority data transmission | Oxygen in blood, pulse, and position measurements |
| [ | Stroke, PD, and epilepsy | Garment with integrated sensors, user needs such as design and comfort are identified | Accelerometer, gyroscope, and ECG |