Channel modeling and power consumption analysis for galvanic coupling intra-body communication
© Gao et al. 2016
Received: 28 January 2016
Accepted: 4 April 2016
Published: 18 April 2016
Intra-body communication (IBC), using the human body as the channel to transmit data, has lower power consumption, less radiation, and easier linking than common wireless communication technologies such as Bluetooth, ZigBee, and ANT+. As a result, IBC is greatly suitable for body area network (BAN) applications, such as the medical and health care field. Furthermore, IBC can be implemented in wearable devices, including smart watches, sports bracelets, somatic game devices, and multimedia devices. However, due to the limited battery capacity of sensor nodes in a BAN, especially implanted sensor nodes, it is not convenient to charge or change the batteries. Thus, the energy effectiveness of the media access control (MAC) layer strongly affects the life span of the nodes and of the entire system. Certainly, analyzing MAC layer performance in a galvanic coupling IBC is of great importance for the overall system. To obtain the attenuation properties of IBC, in vivo experiments with seven volunteers were performed. Meanwhile, an equalizer was used to compensate the frequency distortion in consideration of frequency-selective fading characteristics of intra-body channels. In addition, a comparison of the bit error rates (BER) of different modulation methods was carried out to obtain the best modulation method. Then, the attenuation characteristics of intra-body channels were applied in a multi-node physiological signal monitor and transmission system. Finally, TDMA and CSMA/CA protocols were introduced to calculate the bit energy consumption of IBC in the practical scenario. With stable characteristics of the intra-body channels, QPSK with an equalizer had a better performance than the tests without an equalizer. As a result, the modulation method of FSK could achieve a lower BER in lower signal-to-noise ratio situations and an FSK method with TDMA for the IBC had the lowest energy consumption under different practical scenarios.
Nowadays, with the development of economy and technology, there is a boom in wearable devices, such as smart watches, smart wristbands, sports bracelets, somatic game devices, and multimedia devices. Generally, these wearable devices were connected through Bluetooth or ZigBee. To increase the integration and communication security, body area network (BAN) was proposed as a new generation of wireless sensor networks which works in the vivo and vitro of the human body. It could be applied in many domains, including health care, medical, military, and consumer electronics . Honeine, P. et al.  indicated using BAN in health care and medical domains to monitor the vital physiological signals. They analyzed the long-term information of physiological sensors which were worn or implanted in the body to provide a health care for some common diseases, such as diabetes, hypertension, and heart attack. In a health care BAN, transmission method should be low power consumption, low radiation, and high transmission efficiency and security. However, with high power consumption and network insecurity, traditional communication technologies (Bluetooth or ZigBee) were not suitable for the BAN. In this regard, intra-body communication (IBC) was identified by IEEE Standards Organization as a physical layer standard for BAN . In intra-body communication (IBC), human body was selected as transmission medium for electrical signal propagation . There are two signal coupling types in IBC, which are capacitive coupling and galvanic coupling, respectively [4–8]. In capacitive coupling IBC, the signal channel is mainly composed of four parts—human body, signal electrode, ground electrode, and the external ground. The ground electrode couples the signal towards the external ground via the electrostatic field. Meanwhile, the surrounding environment has a great influence on the quality of communication, whereas galvanic coupling injects the electric current signal into the body through a pair of electrodes attached to the skin, and another pair of electrodes is used to differentially detect the coupling potential on the skin. The transmission path of galvanic coupling IBC is completely dependent on the human body. Therefore, it does not interact with the external environment which contributes to higher security.
In galvanic coupling IBC, the human body is utilized as the data channel to carry information . The signal transmission is implemented by coupling current signals into the body and picking up the surface potential differentially by two pairs of transceiver electrodes which are attached to the human body. Certainly, human body channel characteristics play a significant role in the data transmission of IBC. The signal attenuations and BER under different carrier frequencies and modulation methods are obtained. Obviously, there are frequency distortions and inter-symbol interference (ISI) existed in human body channels. Thus, the channel model, modulation method, and equalizer should be investigated to reduce the BER and increase the band efficiency of an IBC system.
2 Related works
Recently, several papers have reported on IBC investigation. The concept of IBC was initially proposed by Zimmerman in 1995, following the first circuit model for the communication channel of the body . M. Amparo Callejon et al.  proposed a simple model based on a distributed parameter structure which flexibly adapts to both galvanic and capacitive coupling. Furthermore, they verified the effectiveness of the model through an experiment with two methods. Then, the human body channel model was equivalent to a four-terminal circuit to be designed and analyzed by in vivo experiment . M. S. Wegmueller et al.  compared the different electrodes and designed a testing system with up to 1 mA contact current modulated in the frequency range of 10 kHz to 1 MHz. In , they proved that galvanic coupling of IBC was lower power consumption than other wireless technologies. Željka Lucev et al.  analyzed the capacitive IBC channel transmission characteristics in the frequency range from 100 kHz to 100 MHz. In , they used different electrode arrangements, test persons, environments, and body positions and movements. They also used a network analyzer and a pair of baluns to obtain the reliability characteristics of a realistic, capacitive IBC channel. N. Haga et al.  proposed a theory of the equivalent circuit for lossy conductors and addressed the physical mechanism of the communication channels as well. In China, Ruoyu Xu et al.  established an electric-field IBC model based on a finite element method (FEM) model, and studied environmental effects on the electric-field intra-body communication channel. Wang Hao et al.  designed a high-speed IBC receiver, which concentrated on high data speed, 2.5 and 5 Mbit/s, extremely long transmission distances, 170 cm, and applied on an FPGA-based audio player. In , by a simple touch on the transmitter electrode, the data would be sent through one hand to the other hand attached by a receiver electrode. Changjiang Dua, Zedong Nie et al. invented a voice communication system based on human communication [16, 17]. It included an audio transmission device and an audio reception device. The human body was employed as an audio signal transmission medium, where the audio signal transmission was near the ear, and an audio reception device in the ear received and played the audio signal from the human body. This audio communication system used IBC technology and had the advantages of low power consumption, high confidentiality, and less body damage. Xi Mei Chen et al.  studied the IBC channel characteristics through a comparison between theoretical calculations via transfer functions and experimental measurements in both the frequency domain and the time domain. In , Lysis versus different transmission distances. Harmonic distortions were analyzed in both base-band and pass-band transmissions for square input waves. They also explored the BER performance of several common modulation schemes in an IBC system with a carrier frequency of 500 kHz.
The aforementioned researches of IBC channel characteristics were mainly focused on the design of channel circuit models, the experimental design, data analysis, and the electromagnetic characteristics of human tissues. However, they didn’t consider the pros and cons of various modulation methods and the ISI of IBC channel. The research of energy efficiency and low power consumption for a wireless body area network (WBAN) started at the end of the 20th century. In 2008, Omeni et al.  firstly studied the problem of energy efficiency of WBAN from the viewpoint of protocol, and they proposed a new MAC protocol of energy efficiency. In 2012, Prabh  achieved time synchronization and combination with the existing TDMA protocol by its own electrocardiogram (ECG) signal, and proposed a BAN MAC, which was another breakthrough of MAC design for WBAN. In 2013, S. Hayat  proposed an energy-efficient MAC protocol for WBAN. At the same year, Ramona Rosini  researched channel measurement and MAC performance evaluation on the surface of the human body in a WBAN. The majority of MAC protocols were based on TDMA or CSMA/CA according to previous researches on MAC protocols. A multi-node physiological signal monitor and transmission system using the channel characteristics of IBC were assumed as the application scenario, and two common protocols were chosen to calculate and compare the bit energy consumption of IBC at the same application situation.
In this view, this paper focused on the study of the channel model of IBC systems. The rest of this paper is organized as follows. With the signal analyzer in a constant voltage circuit and a differential probe, we did in-vivo experiments with seven volunteers to obtain the amplitude-frequency characteristics of human body channel. Then, a band-pass filter was designed based on the experiment data to serve as the model of a human body channel. Based on the channel characteristics in Section 3, an equalizer was designed to compensate for the frequency distortion of the human body channel. Following this, BER of different kinds of modulation methods in an IBC base band modulation simulation model were evaluated and compared. QPSK constellation diagrams and the performance of the equalizer were investigated in Section 4 as well. An intra-body communication transceiver based on an FSK method is proposed in Section 5. The transmitter consists of a micro-controller and a modulation circuit, while the receiver contains an AFE (analog front end) which involves a conditioning circuit (amplifier, filter, and comparator), demodulation circuit, and display section. The bit energy consumption of two MAC protocols—TDMA and CSMA/CA, were calculated and compared in an IBC application scenario in Section 6. Finally, the conclusions were drawn in Section 7.
3 Channel modeling of the human body
Signal-noise ratio of different frequency signal
4 IBC base band modulation simulation model
Figure 6a indicated that the BER and band efficiency was considered at the same time. FSK could attain the lowest BER for the IBC system, whereas the band efficiency of FSK was lower than PSK. However, when the SNR was higher than 8 dB, the BER of 8PSK and QPSK were similar. In terms of band efficiency, QPSK is twice as high as of BPSK’s. The 8PSK had the highest BER of these modulation methods as well as higher band efficiency at the same time. Thus, when it comes to requiring higher band utilization, FSK had a lower BER and could better conform to the requirements of an IBC system and FSK was not affected by a change in channel parameters.
5 Implementation of an intra-body communication system
Parameters of Transceiver
20 kHz, 40 kHz
As shown in the Fig. 9, (1) represents the receiver signal, and (2) represents the transmission signal. As a result of the existence of transmission distance and the low data rate, the transmitted signal and the receiver signal exhibit a phase delay. The experimental results show that the IBC system can realize transmission signal.
In this section, an intra-body communication system of point-to-point was implemented. But in the application scenario of medical BAN, multi-node application scenario and the energy effectiveness of system are necessary to be analyzed. Due to the limited battery capacity of sensor nodes in a BAN, especially for implanted sensor nodes, it is not convenient to charge or change the batteries. Therefore, the energy effectiveness of the media access control (MAC) layer strongly affects the life span of the nodes and of the entire system. Certainly, analyzing MAC layer performance in a galvanic coupling IBC is of great importance for the overall system.
6 The energy consumption of the MAC layer
The last section implemented the point-to-point intra-body communication system, and this section focuses on the choice of two common protocols in a multi-node galvanic coupling IBC system.
To investigate the energy consumption of MAC layer based on TDMA and CSMA/CA, using the proposed band-pass filter characteristics of the human body in section 3, designed a multi-node physiological signal monitor and transmission system using a star topology at the fist. The modulation method took advantage of the lower BER of FSK. Each node acquired the signal by STM32 with 12-bit ADC in this system and transmitted to the master node via the galvanic coupling IBC. In order to complete the protocol system function for the medical BAN application, TDMA and CSMA/CA protocols were introduced to calculate the bit energy consumption in the practical scenario.
Among these terms, P r , P t , and P id are the power drawn by the receiver, transmitter, and in the idle state, respectively. The first item of Eq. (9) represents the energy consumption for reception of the polling frame of N sub-nodes. The second one is the consumption of transmitting data of the specified node. The last item is the idle state energy consumption for the remaining (N-1) nodes.
CSMA/CA is a network multiple access method in which carrier sensing is used . The network nodes attempt to avoid collisions by transmitting their packet data in entirety only when the channel is sensed to be “idle.” This collision avoidance mechanism is beneficial to avoid the data loss of certain vital physiological signals in a medical BAN when, for instance, an emergency has occurred. The master node broadcasts a control segment with the packet size information. Each sub-node receives the request and sends a corresponding size data packet to the master through the use of CSMA/CA.
The parameters of IBC based on TDMA and CSMA/CA
S tm (byte)
S cs (byte)
S ds (byte)
S cm (byte)
CW 1 (ms)
All in all, the bit energy consumption of TDMA is obviously lower than the bit energy consumption of CSMA/CA. The reason is that the CSMA/CA access mechanism with larger energy consumption competition, channel and node listens, and packet collisions consumes more network energy. CSMA/CA, however, has balanced each node in the channel, thus increasing the flexibility of the system. Nevertheless, considering its lower power consumption, TDMA may be more suitable for a BAN that is based on IBC.
In this research, to obtain the attenuation properties of IBC, in vivo experiments with 7 volunteers were carried out in a frequency band range from 10 kHz to 500 kHz, and the results have indicated that human body channel attenuation can be equivalent to a band-pass filter characteristic. In addition, the equalizer which effectively reduced ISI was designed according to the frequency-selective fading characteristic of the human body channel. Then an IBC base band modulation simulation model was established based on human body channel characteristic, and the BER of different modulation methods were also evaluated and compared with each other. The results indicated that when higher band utilization was not required, FSK had lower BER and could better conform to the requirements of an IBC system. Moreover, FSK would not easily be affected by a change of channel parameters. To investigate the energy consumption of the MAC layer based on TDMA and CSMA/CA, a multi-node physiological signal monitor and transmission system was designed using the proposed band-pass filter characteristics of the human body to compare the power consumption of MAC layer based on TDMA and CSMA/CA. An FSK modulation-demodulation method was applied in the system. The outcome showed that TDMA had lower power consumption, but the number of nodes was easier to change under CSMA/CA because each node had the same priority. Considering the different priorities of human physiological signals and the lower power consumption, an FSK method with TDMA is more suitable for human communication in health care systems.
This work was supported by the Project of Chinese Ministry of Science and Technology 2013DFG32530, the National Natural Science Foundation of China U1505251 and 61201397, the Funds of the Department of Education of Fujian Province, China, JA13027 and the Project of the Department of Education of Fujian Province, China,JK2014001.
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- IEEE 802.15 is the Working Group for WPAN & Task Group 6 is the group responsible for BANs. http://www.ieee802.org/15/pub/TG6.html.
- P Honeine, F Mourad, M Kallas et al., Wireless sensor networks in biomedical: Body area networks, Systems, Signal Processing and their Applications (WOSSPA), 2011 7th International Workshop on, 2011, pp. 388–391Google Scholar
- IEEE Standards Association. 802.15. 6–2012 IEEE Standards for Local and Metropolitan Area Networks–Part 15.6: Wireless Body Area Networks[J].Google Scholar
- TG Zimmerman, Personal area networks: near-field intrabody communication[J]. IBM Syst. J. 35(3.4), 609–617 (1996)View ArticleGoogle Scholar
- JE Ferguson, AD Redish, Wireless communication with implanted medical devices using the conductive properties of the body[J]. Expert Rev. Med. Devices 8(4), 427–433 (2011)View ArticleGoogle Scholar
- SH Pun, YM Gao, PU Mak et al., Quasi-static modeling of human limb for intra-body communications with experiments[J]. Inform. Technol Biomed, IEEE Transact 15(6), 870–876 (2011)View ArticleGoogle Scholar
- Y-m Gao, P Siohang, D Min et al., Quasi-static model and transceiver design for galvanic coupling intra-body communication. J Electron. Meas. Instrum. 26(8), 732–737 (2012)View ArticleGoogle Scholar
- Y-m Gao, P Siohang, D Min et al., Model and analyze for the intra-body communication of the implantable medical sensors. Chin. J. Sci. Instrum. 33(12), 21–26 (2012)Google Scholar
- M Amparo Callejon, D Naranjo-Hernández, J Reina-Tosina et al., Distributed circuit modeling of galvanic and capacitive coupling for intrabody communication [J]. Biomed. Eng., IEEE Trans. 59(11), 3263–3269 (2012)View ArticleGoogle Scholar
- K Hachisuka, Y Terauchi, Y Kishi et al., Simplified circuit modeling and fabrication of intrabody communication devices[J]. Sensors Actuators A Phys. 130, 322–330 (2006)View ArticleGoogle Scholar
- MS Wegmueller, M Oberle, N Felber et al., Signal transmission by galvanic coupling through the human body [J]. Instrum. Meas., IEEE Trans. 59(4), 963–969 (2010)View ArticleGoogle Scholar
- Ž Lucev, I Kroisd, M Cifrek, A capacitive intrabody communication channel from 100 kHz to 100 MHz [J]. Instrum. Meas., IEEE Trans. 61(12), 3280–3289 (2012)View ArticleGoogle Scholar
- N Haga, K Saito, M Takahashi et al., Equivalent circuit of intrabody communication channels inducing conduction currents inside the human body [J]. Antennas Propag, IEEE Trans 61(5), 2807–2816 (2013)MathSciNetView ArticleGoogle Scholar
- R Xu, WC Ng, H Zhu et al., Equation environment coupling and interference on the electric-field intrabody communication channel [J]. Biomed. Eng., IEEE Trans. 59(7), 2051–2059 (2012)View ArticleGoogle Scholar
- W Hao, CS Choy, A 170 cm transmission distance, high speed IntraBody Communication receiver design and its application to FPGA audio player[C]//TENCON 2013–2013 IEEE Region 10 Conference (31194). IEEE, 2013: 1–4Google Scholar
- Changjiang Dua, Zedong Nie, et al. Audio Communication System: China, 103888194 A[P].2014.06.25.Google Scholar
- N Zedong, G Feng, H Jin et al., Low power single-chip RF transceiver for human body communication [J]. China Commun. 9(9), 1–10 (2012)Google Scholar
- XM Chen, PU Mak, SH Pun et al., Study of channel characteristics for galvanic-type intra-body communication based on a transfer function from a quasi-static field model [J]. Sensors 12(12), 16433–16450 (2012)View ArticleGoogle Scholar
- O Omeni, A Wong, AJ Burdett et al., Energy efficient medium access protocol for wireless medical body area sensor networks [J]. Biomed. Circuits Syst., IEEE Trans. 2(4), 251–259 (2008)View ArticleGoogle Scholar
- KS Prabh, F Royo, S Tennina, et al, BANMAC: an opportunistic MAC protocol for reliable communications in body area networks[C]//Distributed Computing in Sensor Systems (DCOSS), 2012 IEEE 8th International Conference on. IEEE, 2012: 166–175Google Scholar
- S Hayat, N Javaid, ZA Khan, et al, Energy efficient MAC protocols[C]//High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems (HPCC-ICESS), 2012 IEEE 14th International Conference on. IEEE, 2012: 1185–1192Google Scholar
- R Rosini, F Martelli, M Maman, et al, On-body area networks: from channel measurements to mac layer performance evaluation[C]//European Wireless, 2012. EW. 18th European Wireless Conference. VDE, 2012: 1–7Google Scholar
- XZ Zeng, YM Gao, SH Pun, Effects of muscle conductivity on signal transmission of intra-body communications[J]. J. Electron. Meas. Instrum. 27(1),21-25 (2013)Google Scholar
- D Hua, MATLAB simulation and communication application example explanation[M], (Posts & Telecom Press, 2003)Google Scholar
- S Chapman, MATLAB programming for engineers[M], (Nelson Education, 2015.)Google Scholar
- J Proakis, M Salehi, G Bauch, Contemporary communication systems using MATLAB[M], (Cengage Learning, 2012)Google Scholar
- ER Hapeman, WR Zeuch, JA Crandall et al., Telecom Glossary 2000–American National Standard T1, 2001, pp. 523–2001. http[J]Google Scholar
- Z TANG, L FENG, D XIE et al., Analysis and research of volume conduction channel [J]. Comput. Simul. 2, 035 (2010)Google Scholar
- Y Li, X Qi, M Keally et al., Communication energy modeling and optimization through joint packet size analysis of bsn and wifi networks [J]. Parallel Distrib. Syst., IEEE Trans. 24(9), 1741–1751 (2013)View ArticleGoogle Scholar
- G Zhou, Q Li, J Li et al., Adaptive and radio-agnostic qos for body sensor networks[J]. ACM Trans. Embed. Comput. Syst(TECS). 10(4), 48 (2011)Google Scholar
- J Liu, Engineer experience-said STM32, (Beijing University of aeronautics and astronautics press, 2011)Google Scholar