Human Body Channel Research Articles

Design of high‐speed data transfer turbo code for body channel communication transceivers

SummaryIn this work, a digital differential transmitter based on low‐power wireless compensation transceiver for body channel communication (BCC) is proposed. Further, the proposed transceiver is composed of Touch Status Detection Unit (TSDU), Wireless Status Compensation Unit (WSCU), and a reconfigurable preamplifier. Initially, the human body channel environment for wireless communication is investigated based on properties from 1 to 100 MHz. Further, the turbo code‐based encoding scheme is used to encode the data before transferring the data on the transmitter side. Also, the proposed error‐correcting parallel turbo decoder using a modified step‐by‐step algorithm is presented. The turbo code‐based decoding scheme is used to recover the error‐free transmitted data at the receiver side. Results demonstrate that the proposed BCC transceiver is designed using 90 nm CMOS technology and it is observed that the proposed BCC transceiver has utilized an area of 600mm2. Also, the maximum data rate achieved by a proposed BCC transceiver was 100 Mbps, and the overall transceiver power consumption is 0.42 mW, and energy for communication is 0.02 nj/b.

Understanding the Role of Magnetic and Magneto-Quasistatic Fields in Human Body Communication.

With the advent of wearables, Human Body Communication (HBC) has emerged as a physically secure and power-efficient alternative to the otherwise ubiquitous Wireless Body Area Network (WBAN). Whereas the most investigated HBC modalities have been Electric and Electro-quasistatic (EQS) Capacitive and Galvanic, recently Magnetic HBC (M-HBC) has been proposed as a viable alternative. Previous works have investigated M-HBC through application points-of-view, without exploring its fundamental working principle. In this paper, a ground up analysis is performed to study the possible effects and contributions of the human body channel in M-HBC over 1kHz to 10 GHz, by electromagnetic simulations and supporting experiments. The results show that while M-HBC can be successfully operated as a body area network, the human body itself plays a minimal or negligible role in its functionality. For Magneto-quasistatic (MQS) HBC (frequencies less than ∼30 MHz), the body is transparent to the quasistatic magnetic field. Conversely for higher frequencies, the conductivity of human tissues attenuates Magnetic HBC fields due to induced Eddy currents, preventing the body to support efficient waveguide modes. With this conceptual understanding developed, different modes of operations of MQS HBC are outlined for both high impedance capacitive and 50Ω termination cases, and their performances are compared with EQS HBC for similar sized devices, over varying distances between TX and RX. The resulting report presents a fundamental understanding towards M-HBC operation and its contrast with EQS HBC, aiding HBC device designers to make educated design decisions, depending on application scenarios.

A special view on the method of implication, classification, and decision-making strategies of the human body channels

A special view on the method of implication, classification, and decision-making strategies of the human body channels

Channel-Aware Gait-Cycle-Based Transmission in Wireless Body Area Networks

The use of the Internet of Things has proven to be an alternative for health monitoring, providing less discomfort to patients and good cost-benefit. To fully exploit the benefits of wireless technologies in e-health, the IEEE 802.15.6 standard for Wireless Body Area Networks (WBAN) has been created. However, technical and social challenges must be addressed to enable their adoption. Some factors, such as the use of the human body as a propagation media, and human body movements, make WBAN a new paradigm of wireless communication networks. The human body movement and posture affect the wireless channel quality, which may result in poor communication performance. To meet the requirements of WBAN applications, while preserving the energy efficiency, this paper proposes a Channel Aware Gait-cycle-based transmission mechanism (CAG), a mechanism that uses human body movement and channel response correlation to transmit during good channel conditions, ensuring reliability and energy savings. Our proposal was analyzed in the Castalia Simulator and compared against TDMA-based scheduling and the IEEE 802.15.6 CSMA/CA protocol. Simulation results show CAG significantly improves packet delivery ratio and energy efficiency.

EQS Res-HBC: A 65-nm Electro-Quasistatic Resonant 5–240 μW Human Whole-Body Powering and 2.19 μW Communication SoC With Automatic Maximum Resonant Power Tracking

Applications like connected healthcare through physiological signal monitoring and secure authentication using wearable keys can benefit greatly from the battery-less operation. Low-power communication along with energy harvesting is critical to sustain such perpetual battery-less operation. Human body channel is known to be a promising alternative to wireless radio wave communication for low power operation through human body communication (HBC), as well as very recently demonstrated as a medium for power transfer through body-coupled power transfer. However, channel length (L) dependency of the received power makes it inefficient for L>40 cm. In this article, we utilize electro-quasistatic resonant HBC (EQS Res-HBC) with maximum resonant power tracking (MRPT) to enable channel length-independent whole-body communication and powering. We design the first system to transfer power and data from a HUB device to wearable energy-harvested NODE through the human body to enable battery-less perpetual operation. Measurement results show 240, 28, and 5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> power transfer through the body in a machine–machine (large devices with strong ground connection), tabletop (small devices kept on a table), and wearable–wearable (small form factor battery-operated wearable devices) scenario, respectively, independent of body channel length, while enabling communication at 2.19 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> . This enables >25 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> more power transfer with >100 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> more efficiency compared to the state of the art for 100-cm body channel in tabletop scenario by utilizing the benefits of EQS operation. The MRPT loop automatically tracks device and posture-dependent changes in the resonance point to maximize power transfer in all cases.

Physically Secure Wearable–Wearable Through-Body Interhuman Body Communication

Human body communication (HBC) has recently emerged as an alternative method to connect devices on and around the human body utilizing the electrical conductivity properties of the human body. HBC can be utilized to enable new interaction modalities between computing devices by enhancing the natural interaction of touch. It also provides the inherent benefit of security and energy-efficiency compared to a traditional wireless communication, such as Bluetooth, making it an attractive alternative. However, most state-of-the-art HBC demonstrations show communication between a wearable and an Earth ground–connected device, and there have been very few implementations of HBC systems demonstrating communication between two wearable devices. Also, most of the HBC implementations suffer from the problem of signal leakage out of the body which enables communication even without direct contact with the body. In this article, we present BodyWire which uses an electro-quasistatic HBC (EQS-HBC) technique to enable communication between two wearable devices and also confine the signal to a very close proximity to the body. We characterize the human body channel loss under different environment (office desk, laboratory, and outdoors), posture, and body location conditions to ascertain the effect of each of these on the overall channel loss. The measurement results show that the channel loss varies within a range of 15dB across all different posture, environmental conditions, and body location variation, illustrating the dynamic range of the signal available at the input of any receiver. Leakage measurements are also carried out from the devices to show the distance over which the signal is available away from the body to illustrate the security aspect of HBC and show its effect on the channel loss measurements. For the first time, a through-body interhuman channel loss characterization is presented. Finally, a demonstration of secure interhuman information exchange between two battery-operated wearable devices is shown through the BodyWire prototype, which shows the smallest form factor HBC demonstration according to the authors’ best knowledge.

Stochastic Bioimpedance-Based Channel Model of The Human Body for Galvanic Coupling.

Human body communication (HBC) uses the human body as the channel to transfer data. Extensive work has been done to characterize the human body channel for different HBC techniques and scenarios. However, statistical channel bioimpedance characterisation of human body channels, particularly under dynamic conditions, remains relatively understudied. This paper develops a stochastic fading bioimpedance model for the human body channel using Monte Carlo simulations. Differential body segments were modelled as 2-port networks using ABCD parameters which are functions of bioimpedance based body parameters modelled as random variables. The channel was then modelled as the cascade of these random 2-port networks for different combinations of probability distribution functions (PDFs) assumed for the bioimpedance-based body parameters. The resultant distribution of the cascaded body segments varied for the different assumed bioimpedance based body parameter distributions and differential body segment sizes. However, considering the distribution names that demonstrated a best fit (in the top 3 PDF rankings) with highest frequency under the varying conditions, this paper recommends the distribution names: Generalized Pareto for phase distributions and Log-normal for magnitude distributions for each element in the overall cascaded random variable ABCD matrix.

Far-field characterization of wave oblique incidence on body channel for implant communication by using an analytical model

Characterization of human body channel is a necessity to pave way for the practical implementation of implant communication. Considering there are few investigations on the characterization of incident wave propagating at an arbitrary angle to human tissues, this paper applies an analytical model of wave oblique incidence onto multilayered planar lossy tissues to evaluate the far-field EMFs and PLs of body channel. With this model, EMFs and PLs of both TM and TE wave oblique incidence at different angles and frequencies in out-to-in and in-to-out propagations are calculated. A FEM model and a measurement on porcine tissues are also carried out. Comparing with simulation and experiment, the analytical results of PLs have the maximum differences of 0.03 and 1.0 dB, respectively, in out-to-in propagation and of 0.09 and 1.7 dB, respectively, in in-to-out propagation. Therefore, the analytical model is accurate and indicates the mechanism of EM wave propagation in body channel theoretically.

An approach to detect human body movement using different channel models and machine learning techniques

Worldwide, 16.7 million people die each year due to cardiovascular disease. These statistics raise demand of devices like sensor-based pacemakers (PM) which are not just doing heart rate augmentation but also capable to transmit information via wireless link to on body sensor and support remote monitoring of such patients. As per the world health organization WHO reports there are more than 3 million functioning PMs and about 600,000 pacemakers are implanted each year in world. On an average, 70–80% of PMs are implanted in aged patients around 65 years or older. In addition to continuous monitoring of cardiovascular parameters, detection of physical movement of such patients may be helpful to assess their well-being. This paper has been formulated with an aim to highlight an approach which may be used to detect the physical movement of the patient using information signal received from implanted PM. The transmitted signal will experience a pathloss offered by wireless human body channel, which will affect the link quality parameters namely Signal to Noise Ratio (SNR) and Bit Error Rate (BER) and received signal strength indicator (RSSI). In the current work mathematical model has been formulated considering in body and on body channel propagation conditions and received power, received energy, pathloss, SNR, BER, bit rate, energy per bit and RSSI have been evaluated using IEEE802.15.6 channel models CM2 and CM3. Data set has been created and human body movement has been detected using Machine Learning (ML) techniques. Prediction accuracy of Multilayer Perceptron (MLP), k-Nearest Neighbours (kNN) and Random Forest have been compared. The analysis performed depicts that human body movement can be detected using different channel models and ML techniques such as MLP, kNN and Random Forest with an accuracy of 65.3%, 72.8% and 93.4% respectively. The critical comparison of the result indicates that the performance of Random Forest is better than MLP and kNN. This approach will be helpful in remote detection of human body movement of patients.

Measurement and Analysis of Human Body Channel Response for Biometric Recognition

This paper presents a highly secure and convenient biometric system for user recognition based on body channel characteristics for electric signal transmission. In the proposed framework, the user can provide reliable biometric features of body channel responses (BCRs) simply by touching an electrode surface on the device with a finger. To realize and verify the proposed approach, we acquired the BCR data from 15 subjects for approximately six weeks through experiments conducted in a customized measurement setup suited to the principle of signal transmission in the human body channel. The proposed BCR-based biometric feature (BBF) comprises a series of envelope vectors of the received BCR when applying up- and down-chirp signals to the human body, which is extracted by an interpolative method based on peak detection. The BBFs are effectively separable according to the subjects because the features magnify quantitative differences in the aspect of path losses and power delay profiles of individual BCRs for the frequency range between 1 and 10 MHz. The classification performance was evaluated by splitting the dataset into 80 and 20 % for the training and testing, respectively, using conventional machine learning algorithms with uncorrelated 40 session data sets for the respective subjects. The highest average classification accuracy was achieved by the kernel-based support vector machine approximately 95.8 % without observable and biased misidentification cases among the subjects. In addition, the analysis of receiver operating characteristic curves shows that the proposed classifiers are robust to decision boundaries at various threshold settings.

BodyWire-HCI

Communication during touch provides a seamless and natural way of interaction between humans and ambient intelligence. Current techniques that couple wireless transmission with touch detection suffer from the problem of selectivity and security, i.e., they cannot ensure communication only through direct touch and not through close proximity. We present BodyWire-HCI , which utilizes the human body as a wire-like communication channel, to enable human–computer interaction, that for the first time, demonstrates selective and physically secure communication strictly during touch. The signal leakage out of the body is minimized by utilizing a novel, low frequency Electro-QuasiStatic Human Body Communication (EQS-HBC) technique that enables interaction strictly when there is a conductive communication path between the transmitter and receiver through the human body. Design techniques such as capacitive termination and voltage mode operation are used to minimize the human body channel loss to operate at low frequencies and enable EQS-HBC. The demonstrations highlight the impact of BodyWire-HCI in enabling new human–machine interaction modalities for variety of application scenarios such as secure authentication (e.g., opening a door and pairing a smart device) and information exchange (e.g., payment, image, medical data, and personal profile transfer) through touch (https://www.youtube.com/watch?v=Uwrig2XQIH8).

Dynamic Edge-coded Protocols for Low-power, Device-to-device Communication

Clock and Data Recovery (CDR) has been a foundational receiver component in serial communications. Yet this component is known to add significant design complexity to the receiver and to consume significant resources in area and power. In the resource-limited world of constrained IoT nodes, the need of including CDR in the communication link is being re-assessed and new techniques for achieving reliable serial transmission without CDR have been emerging. These new techniques are distinguished by their use of transition edges rather than bit times for coding and detection. This article presents the design, implementation, and testing of a novel CDR-less transmission protocol that achieves significant improvements in data rate, reliability, packet security, and power efficiency with respect to state-of-the-art CDR-less techniques. The new protocol further tolerates significant jitters and clock discrepancies between transmitter and receiver. An FPGA and an ASIC (65 nm technology) implementation of the protocol have shown it to consume around 19μ W of power at a clock rate of 25 MHz, and to have a small footprint with a gate count of approximately 2,098 gates. In particular, the new protocol reduces area by more than 87% and power by more than 78% in comparison with CDR-based serial bit transfer protocols. Furthermore, the new protocol is shown to be versatile in its applications to available communication media, including wired, wireless, infrared, and human-body channels, under a variety of digital modulation schemes.

Design of a floating-ground-electrode circuit for measuring attenuation of the human body channel.

Recently, health care and disease prevention are more and more important in people's daily life. Human body communication (HBC) is an emerging short distance wireless communication mode, which is quite suitable for the communication between the wearable human health care equipment. However, most research on HBC mainly focuses on the electromagnetic model and the circuit model of equivalent human and the in vivo experiment is based on the commercial equipment. The aim of this paper is to design a circuit device for measuring the attenuation of the human body channel based on a floating-ground-electrode method. This paper proposed a new floating-ground-electrode method so as to solve problems of power and high frequencies interference and impedance matching. A circuit module, including signal generator, analog frontend circuit and MCU, was designed to initially replace the spectrum analyzer to measure the attenuation of the human body channel. The floating-ground-electrode added to the receiving end of the human body channel was connected to the ground of the analog frontend circuit, forming an equal potential circuit. The three-electrodes of the receiving terminal can act as a differential probe, since one electrode is connected to the ground and the other two electrodes achieved signal input and output respectively. The results showed that the experimental data of channel attenuation were similar to the measured value of the spectrum analyzer. The maximum absolute error was 1.148 dB and the relative error was 3.55%. In addition, different sizes of the floating-ground-electrode cannot affect the attenuation path of human body channels. Moreover, the common mode rejection ratio (CMRR) was approximated to the value of the commercial differential probe. This paper proposed a new floating-ground-electrode method for measuring the attenuation of the human body channel. It could provide the possibility for the dynamic measurement of attenuation and take the place of the spectrum analyzer and make the process of experiments simple and efficient.

Design of a human body channel communication transceiver using convolutional codes

This paper presents a wideband signaling body channel communication (BCC) transceiver that uses the convolutional encoding method. The proposed transmitter uses the convolutional encoding method to increase the data reliability, and the modulated data are transmitted directly to a human body through a SMA cable and an electrode. In the receiver side, the oversampling phase detection clock and data recovery circuit with convolutional encoding method recovers the clock and data and increases 1.8x random data jitter tolerance (i.e., 50ns–90ns) at 10−9 BER. The proposed BCC transceiver, except for the pre-amplifier of the RX, can be realized as a synthesizable digital IP. Thus, the proposed design can be ported to different processes in a short time. The feasibility of the proposed transceiver architecture was verified by the FPGA, and no bit errors occurred over 108 bits received at data rate 3.125 Mbps in transmission distance under 140 ​cm, which indicates the transceiver is very suitable for high-performance BCC applications.

Impulse response analysis of an ultrasonic human body channel

Ultrasounds have been successfully and safely employed in underwater communications and for health diagnosis in the last 60 years because of their good performance in environments with high water concentration. Recently it has been proposed also to employ them for supporting intra-body communications; however exploitation of ultrasounds inside the body calls for a deep understanding of their features and a full characterization of the impulse response inside these challenging channels. In this paper we provide a complete experimental characterization of the impulse response inside a human body communication channel, composed for more than 65–70% of water. To this purpose we developed a testbed which employs a human phantom of ballistic gel to emulate the human body propagation features and performed a set of measurements to fully discuss the channel behavior as a function of different parameters such as the employed frequency, the channel composition and the distance. Our results show that, it is possible to clearly identify the three main components generated by multipath propagation inside the human phantom, i.e. the direct, lateral and reflected waves. Also, it is possible to observe that the excess delay which measures the time elapsed between the first and the last arriving waves, increases approximately as 10 μs per cm. Our analysis provides interesting has strong implications on the design of communication protocols for intra-body scenarios.

Evaluation of Human Body Characteristics for Electric Signal Transmission Based on Measured Body Impulse Response

Human body communications (HBCs) have recently emerged as an innovative alternative to the current radio frequency communications for realizing wireless body area networks (WBANs) using the human body as a transmission channel without wired or wireless connections. This article addresses the provision of reliable modeling of the human body as a passage of the electric signal delivery based on the impulse response measurement through the proposal of a measurement setup and signal processing techniques applicable to wearable devices for healthcare and biosignal acquisition. In the experiments, customized impulse signals were applied to the body using battery-powered devices isolated to the earth ground for the operating environments of wearable devices. The impulse responses passed through the body were measured by considering 52 measurement conditions determined by the device locations from the head to ankle and the body postures. Body channel transfer functions (BCTFs) for the respective conditions were derived by an adaptive filter approach using an iterative algorithm to minimize the mean squared error between the measured and modeled impulse responses. The channel analysis parameters, such as mean path loss, root-mean-square delay spread, and mean and maximum excess delays, were analyzed based on the measured body impulse responses. In addition, the practical bit-error-rate performance for HBC based on the BCTFs reproducing intersymbol interference effects caused by the delay spreads of the body channels was explored to verify communication reliability in terms of the transmitter structures adopting digital transmission, sorts of human body channels, data rates, and operating frequencies.

A Body Channel Communication Technique Utilizing Decision Feedback Equalization

This article presents the body channel communication technique that first adopts decision feedback equalisation. For the first time, we characterised post-cursor intersymbol interference of a single-bit pulse response of a human body channel for decision feedback equalisation achieving the first body channel communication faster than 100 Mb/s. In the proposed technique, an 8-tap decision feedback equaliser is utilised at the receiver to compensate for intersymbol interference of the body channel. The experimental results show that the proposed prototype transceiver achieved the highest data rates of 150 Mb/s and 10 Mb/s along 20-cm and about 100-cm body channels, respectively. Compared to the previous best result measured for the same body-channel distance of about 100 cm, the data rate is improved by ten times, showing that the proposed technique can significantly increase the speed of body channel communication.

Energy efficient low density parity check scheme for body channel communication using FPGA

An arrangement of an on-body to on-body thin-ranging channel along with various issues is deliberated. Time-area appearances of body channel communication (BCC) of human are considered by using a Field Programmable Gate Array (FPGA) at variable transmission distances and signal frequencies. In Human body channel communication (HBCC), wide band signaling (WBS) technique is characterized as well as correlated with existing devices and are more stable and expend very less power. But based on the movement of human body, wide band signaling is more sensitive. The WBS constructed BCC is established in FPGA platform at diverse broadcast distances and signal frequencies by using Non Return to Zero (NRZ) encoded information. In this strategy presented, the information encoded by NRZI data at the transmitter part are driven accurately to the human based BCC. At the receiver part, the FPGA enhanced the conventional signals and in addition, the proposed LDPC technique circuit enhances the accepted frequency decoded point information from irregular nodes. The presented LDPC technique based wide band signaling BCC transceiver is acknowledged in the typical 65 nm CMOS executing process. The core region is found as 0.133 mm2. Power consumption of LDPC technique based WBS- BCC transceiver is 1.07 mW at 40Mb/s. The bit energy is 0.02 nJ/b.

Theoretical Analysis of AM and FM Interference Robustness of Integrating DDR Receiver for Human Body Communication.

Prolific growth of miniaturized devices has led to widespread use of wearable devices and physiological sensors. The state-of-art technique for connecting these devices and sensors is through wireless radio waves. However, wireless body area wireless body area network (WBAN) suffers from limited security (wireless signals from energy-constrained sensors can be snooped by nearby attackers), poor energy-efficiency (up conversion and down conversion), and self-interference. Human body communication (HBC), which uses human body as a conducting medium, has emerged as a new alternative physical layer for WBAN, as it can enable communication with better energy efficiency and enhanced security. Broadband (BB) HBC uses the human body channel as a broadband communication medium and can enable higher energy efficiency compared to narrowband HBC. However, due to the antenna effect of human body, ambient interferences get picked up from the environment, proving to be one of the primary bottlenecks for BB-HBC systems. In this paper, we analyze the performance of an integrating dual data rate (I-DDR) receiver, which enables interference robust BB-HBC, under continuous wave (CW), amplitude modulated (AM), and frequency modulated (FM) interferences. Theoretical derivations along with simulations provide key insights into the behavior of I-DDR receiver under different interference scenarios, highlighting the efficacy (>22dB improvement in SIR tolerance for both FM and AM) of the technique. Finally, measurements are carried out by applying the I-DDR principle on signals transmitted through the human body and captured on an oscilloscope. Measurements from an I-DDR receiver fabricated in TSMC 65nm technology shows <10-4 BER in presence of CW, AM, and FM interference with -21dB SIR further demonstrating the efficacy of the I-DDR method in interference rejection.

The remember regeneration therapy method: An overview of new therapy protocol to approach diseases

Epigenetic mechanisms, which cannot be explained by genotypic changes, but reveal the phenotype formation differences of genes, take part in the whole cellular process throughout our life. Recent advances in today’s rapidly evolving technology have shown that erroneous epigenetic regulations can contribute to serious biological consequences and diseases in human. Human is the smallest model of the universe with its memory, which is processed into DNA codes within the cell, which is the smallest building block. All the phenomena we see as causal relationships in the human body are a reflection of “balance and harmony” relationship. We can see the intersection point of the quadruplet body (human body, energy body, electrical body, and energy channels) as a homeostatic system that produces continuous “balance and harmony” for the coordination of the inheritance DNA. As known, therapeutic approaches that are called as holistic or complementary medicine mainly target to the causes underlying basis of the diseases by using natural therapeutic agents and methods. Thus, it is primarily aimed to protect physiological mechanisms of the body. Also, such therapeutic methods allow medicine to avoid possible side effects of the modern therapeutic approaches. Probably, these are benefits of holistic or complementary medicine methods. On the other hand, many complementary and alternate medicine methods are commonly available, reasonable, and regularly used in many countries. And, these therapies are maintained by practical evidence on protection and efficacy. A growing amount of scientific clinical studies nowadays maintain the usage of definite these therapies. The Remember Regeneration Therapy Method (RTM) is a holistic medicine that describes the anatomical and physiological aspects of physiopathological changes in quadruplet body structures (QBSs), which is unique treatment system where phytotherapy is at its center and integrated with traditional and complementary applications. In the RTM model, diseases are seen as the reflection of epigenetic changes in the phenotype resulting from the gene-environment mismatch. The treatment strategy is based on the recovery of health by essentially improving the deteriorating structures. Considering that many of the epigenetic changes that cause disease can potentially be reversed, it has been clinically observed that epigenetic changes and irregularities improved when appropriate treatment protocols were applied, as in the RTM model. In conclusion, the main aim of this review is to introduce a new model of diagnosis and treatment to medical literature and to demonstrate the efficacy of RTM, which has been characterized by clinical experience (nearly 130,000 individuals suffering from several disorders) over a long period (approximately 25 years) and the reviewing of previous scientific knowledge.