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Here is a new concept called RED TACTON which makes the human body as a communication network by name HAN (Human Area Network). Focusing on the naturalness, inevitability and sense of security conveyed by touching which is called as Red Tacton which could let people transfer data to each other handhelds by means of handshake or a physical contact. Using an embedded transmitter a PDA Red Tacton sends a 5 volts pulse along the surface of body. The human body shunts most of electricity to ground resulting in weak electric field that can be modulated to carry signals. As the receiver is located on the part of the body, the components of a hands free handset or in an acquaintance PDA as it senses modulation in the electric field the receiver decodes them to recover the data. Human Area Network is an important over current wireless technologies such as Bluetooth because users can narrowly limit signal recipients rather than broadcasting to all devices within given range. Using Red Tacton enabled devices music from our digital audio player in our pocket would pass through our clothing and shoot over our body to headphones into our ears. Instead of fiddling around with the cable to connect our digital camera to our computer we could transfer pictures just by touching the PC while the camera is around your neck and since data can pass from one body to another you could also exchange electronics business cards by shaking hands.
Human society is entering an era of ubiquitous computing, when networks are seamlessly interconnected and information is always accessible at our fingertips. In the world of computers, networking is the practice of linking two or more computing devices together for the purpose of sharing data. RedTacton enables the first practical Human Area Network between body-centered electronic devices and PCs or other network devices embedded in the environment via a new generation of user interface based on totally natural human actions such as touching, holding, sitting, walking, or stepping on a particular spot. By making Human Area Networks feasible, RedTacton will enable ubiquitous services based on humancentered interactions and therefore more intimate and easier for people to use. RedTacton can be used for intuitive operation of computer-based systems in daily life,temporary one-to-one private networks based on personal handshaking, device personalization, security, and a host of other applications based on new behavior patterns enabled by RedTacton. At last we predicted how Redtacton changes lifestyle in future.
At the end of 2002 the Japanese telecommunications group NTT had announced that it would develop a new data transmission technology that uses the conductive properties of the human body to exchange information between electronic devices. With RedTacton the company has now scarcely two and a half years later presented its first prototype of a Human Area Network (HAN). The basic principle of the RedTacton concept is the creation of minute electrostatic fields that modulated by a code-giver to carry digital information are capacitively transmitted to human skin as a conductor, thence to be transmitted upon physical contact. To read out the data bits NTT makes use of a novel type of opto-electrical receiver equipped with a miniature laser whose light ray is reflected by a crystal. At the receiving end the electrostatic fields evoked by the RedTacton sender cause the electrical field in the environment of the crystal to change, which in turn induces changes in the polarization of the reflected laser light. These changes in polarization the opto-electrical receiver interprets as data bits, which it converts into electrical signals that can be processed by a PDA, for instance. According to NTT this technology - which can also be made to works when door handles, switches or turnstiles are touched - allows bi-directional signals to be sent at rates of up to 10 Mbit/s. The strength of the electrostatic fields evoked the company puts at but a few hundred milliwatts. Prior to the stage planned for 2006 in which the HAN technology is to be ready for the market, NTT intends to conduct a number of field tests this summer, in which it is inviting companies with an interest in the technology to participate . Japanese company Nippon Telegraph and Telephone Corporation (NTT) claims to have developed the first viable Human Area Network (HAN) device, enabling fast data transfer between devices using the human body as a conduit. NTT reckons this latest advance on the wireless Personal Area Network concept - dubbed RedTacton - can transmit data over the surface of the skin at up to 2Mbps. Where it differs, though, from previous offerings, is that a RedTacton-enabled device does not have to be in direct contact with the skin - only within about 20cm. Human society is entering an era of ubiquitous computing, where everything is networked. The practical implementation of ubiquitous services requires three levels of connectivity: Wide Area Networks (WAN), typically via the Internet, to remotely connect all types of severs and terminals; Local Area Networks (LAN), typically via Ethernet or WiFi connectivity among all the information and communication appliances in offices and homes; and Human Area Networks (HAN) for connectivity to personal information, media and communication appliances within the much smaller sphere of ordinary daily activities-- the last one meter. RedTacton is a break-through technology that, for the first time, enables reliable high-speed HAN. In the past, Bluetooth, infrared communications (IrDA), radio frequency ID systems (RFID), and other technologies have been proposed to solve the "last meter" connectivity problem. However, they each have various fundamental technical limitations that constrain their usage, such as the precipitous fall-off in transmission speed in multi-user environments producing network congestion. "With Bluetooth, it is difficult to rein in the signal and restrict it to the device you are trying to connect to. You usually want to communicate with one particular thing, but in a busy place there could be hundreds of Bluetooth devices within range." Furthermore, humans apparently make poor aerials, something which is "good for security because even if you encrypt data it is still possible that it could be decoded, but if you can't pick it up it can't be cracked
Whatâ„¢s RedTacton ?
RedTacton is a new Human Area Networking technology that uses the surface of the human body as a safe, high speed network transmission path. RedTacton takes a different technical approach. Instead of relying on electromagnetic waves or light waves to carry data, RedTacton uses weak electric fields on the surface of the body as a transmission medium. A RedTacton transmitter couples with extremely weak electric fields on the surface of the body. The weak electric fields pass through the body to a RedTacton receiver, where the weak electric fields affects the optical properties of an electro-optic crystal. The extent to which the optical properties are changed is detected by laser light which is then converted to an electrical signal by a detector circuit. -RedTacton uses the minute electric fieldemitted on the surface of the human body. Technically, it is completely distinct from wireless and infrared. -A transmission path is formed at the moment a part of the human body comes in contact with a RedTacton transceiver. Physically separating ends the contact and thus ends communication. -Using RedTacton, communication starts when terminals carried by the user or embedded in devices are linked in various combinations according to the user's natural, physical movements. -Communication is possible using any body surfaces, such as the hands, fingers, arms, feet, face, legs or torso. RedTacton works through shoes and clothing as well.
How RedTacton Works ?
The transmitter sends data based on fluctuations in the weak electric field induced in the body. The electric field is received using super-sensitive electric field sensing technology. - The naturally occurring electric field induced on the surface of the human body dissipates into the earth. Therefore, this electric field is exceptionally faint and unstable. - The super-sensitive electric field sensing technology measures the weak electric fieldsinduced by the super-efficient alternating electric field induction . - Dielectric : Signals pass through materials Conductor + Dielectric : Combinations of travelling along and passing through materials
Potential Applications â€œ
One-to-One services With the ability to send attribute data from personal information devices worn on the body to computers embedded in the environment, one-to-one services could be implemented that are tailored to the individual needs of the user. - Intuitive operation of personal information devices Communication is triggered by totally natural human actions and behavior, so there is no need to insert smart cards, connect cables, tune frequencies, or any of the other inconveniences usually associated with today's electronic devices. - Device personalization Setup, registration, and configuration information for an individual user can all be uploaded to a device the instant the device is touched, eliminating the need for the device to be registered or configured in advance. - New behavior patterns Tables, walls, floors and chairs can all act as conductors and dielectrics, turning furniture and other architectural elements into a new class of transmission medium. For example, a user could have instant access to the Internet merely by placing a laptop onto a conductive tabletop. - Security applications RedTacton could be installed on doors, cabinets and other locations calling for secure access, such that each secure access could be initiated and authenticated with a simple touch. At the same time, all the transaction details and relevant user attributes (personal identity, security clearance, etc.) could be logged by the security system.
The applications of RedTacton are enormous, medical security and data transfer are just the start. Conferencing can be enabled without the use of wiring, and walls and desks and doorknobs can be conduits for data transfer. In education the applications are endless from lesson outlines to administrative forms data could be transfered quickly and easily without pedagogical intervention. This technology seems to be a glimpse into the future. At first it will be limited in use and fairly expensive, but as it becomes more widespread we could see the extinction of the key and ID card as we know them today. Imagine walking up to your house, reaching for a doorknob which automatically unlocks the door, and walking right in. No more fumbling around for keys. Thatâ„¢s a future weâ„¢d like to live in.
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humen area network technology
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This article is presented by:
BY PRATIKSHA P.PATIL
HUMAN AREA NETWORKING
Application & Advantages
Features & Limitations
The transceiver is called as “THE RED TACTON”.
Key features of SENSOR:
measure electric field from device without contacting it.
ultra wide band is possible.
one point contact measurement ,independent of earth.
Medical applications ( eg.selection of bottles).
In touch advertising and receive information.
Instant private data exchange.
In wearable systems (portable music player).
Secure than other broadcasting systems.
In busy areas, there may be hundred’s of blue tooth devices running,this makes transmission a bit tougher .
As body act as aerials data is passed with ease and security.
The transceiver can be treated a standard network device. So software running through ethernet or LAN based network can run unmodified.
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Human Area Networking
Human Area Networking (HAN) is a technology that safely turns the surface of the human body into a data transmission path at speeds up to 10 Mbps between any two points on the body.
1.1 History of HAN
• The concept of intra-body communication was first proposed by IBM in 1996.
• This communication mechanism was later evaluated and reported by several research groups around the world.
All those reported technologies had two limitations.
1. The operating range through the body was limited to a few tens of centimeters.
2. The top communication speed was only 40 bit/s!!
These limitations were overcome by NTT (Nippon Telegraph and Telephone
Corporation) located in Tokyo, Japan by using photonic electric field sensors
and finally came up with a human area networking technology called
Overview of HAN
• RedTacton is a new Human Area Networking technology that turns the surface of the human body as a safe, high speed network transmission path.
• Communication is possible using any body surfaces, such as the hands, fingers, arms, feet, face, legs or toes.
• RedTacton works through shoes and clothing as well.
• RedTacton uses the minute electric field emitted on the surface of the human body for data transmission.
NTT developed super sensitive Photonic electric field sensor for detecting minute electric field emitted on the surface of the human body.
The electro-optic sensor has three key features:
It can measure electric fields from a device under test (DUT) without contacting it, which minimizes measurement disturbance.
Ultra wide-band measurement is possible.
It supports one-point contact measurement that is independent of the ground,
Which is the most significant feature in the present context.
NTT utilized this third feature to fabricate an intrabody communication receiver
For its human area networking technology, which is called RedTacton.
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The wireless body area network(WBAN) has emerged as a new technology forHealth care that allows the data of a patient’s vital body parameters and Movements tobe collected by small wearable or implantable sensors and Communicated using shortrange wireless communication techniques. Wireless body area networks(WBAN) hasshown great potential in improving health care quality,and thus has found a wide rangeof applications from Ubiquitous health monitoring and computer assisted rehabilitationto emergency Medical response systems.The purpose of this study is to introduce WBAN and Also give an understandingof what possibilities and challenges there are when Using short range wirelesscommunications in this domain.Here establish a prototype body Area network system using Bluetooth andchoose the electrocardiogram(E C G)Signals to test the data transmission performanceover this system.The wireless body area networks promise to revolutionize Health monitoring.since the sensors collect personal medical data,security and Privacy areimportant components in this kind of networks(WBAN).
Our era is witnessing an increasing pressure on the quality and quantity ofhealthcare due to the increase of aging population, chronic diseases, and healthconsciousness of people. People put more attention in prevention and early riskdetection. A system that can continuously monitor the health condition of elderlypeople and share information with remote care providers or hospitals will be in greatdemand. As an effort of catching up with this trend, wireless body area network(WBAN) as an emerging technology for providing this kind of health information,has been attracting more and more attention recently. WBAN is still at its infancy andthere are a lot of open research problems.One of the emerging issues is how to exploitwireless communications technologies in WBANs. ZigBee is a low-cost low-powerstandard. The drawback of ZigBee is the limited data rate, which is 250 kbps whenoperating at 2.4 GHz band, in order to support heterogeneous medical services. Inaddition, it may suffer from strong interference radios as well as other devices suchas microwave ovens also operate in this frequency band. The backward compatibilityis another matter of concern. Ultra wide band (UWB) has also been considered asa potential wireless technology. However, the UWB wireless chips are not yet wellcommercialized at this moment.On the other hand, the Bluetooth is one of the most promising technologiesfor WBANs, particularly for wireless healthcare . The main advantages are the smallsize, reduced cost, low power consumption, and especially the great market penetration.The system employs a frequency-hopping multi-access scheme, which helps1combat interference and fading, and increase the security in radio transmission. Thedata rate is up to 1 Mbps , adequate for transmitting most real time biomedicalsignals. In addition, diverse prototypes of sensors based on Bluetooth have beendeveloped for different biomedical signals, including ECG, glucometers and evenstethoscopes. For instance, Continua Alliance has adopted Bluetooth as the wirelesslink for their wireless healthcare applications .These commercial Bluetooth terminalspermit a straightforward integration of general purpose devices (e.g., PDAs, smartphones,etc.) into WBAN. Despite the apparent suitability of Bluetooth technology for
medical WBANs,its performance in combination with medical data processing techniqueshas not been studied in the literature. here a case study on wireless ECG monitoringover Bluetooth link in order to evaluate the data transmission quality and howit is affected by the ECG compression. Next propose a very low complexity ECG datacompression method and using this method, the influence of data compression on theECG signal reconstruction performance at the Bluetooth receiver will be studied.The deployment of WBAN for medical and non-medical Applications must satisfythe stringent security and privacy requirements. In case of medical applications,the security threats may lead a patient to a dangerous condition, and sometimes toa death. Thus a strict and scalable security mechanism is required to prevent maliciousinteraction with a WBAN. A secure WBAN should include confidentiality andprivacy, integrity and authentication, key establishment and trust setup, secure groupmanagement and data aggregation. However, the integration of a high level securitymechanism in a low power and resource-constraint sensor increases the computational,communication and management costs. In a WBAN, security and system performanceare equally important, and thus, designing a low power and secure WBAN system is afundamental challenge to the designers .
NETWORK ARCHITECTURE OF MEDICAL WBAN
The WBAN architecture under consideration is shown in Figure 2.1. This
architecture consists of two main parts: multiple body sensor units and a body
central unit. The body sensor units are able to perform vital medical data acquisition,
data (pre-processing), actuator control, data transmission and some basic user
feedback. The body central unit links multiple sensor units, performs data collection,
data processing/compression, actuator control, basic event detection/management and
provides external access together with a personalized user interface. In this seminar and presentation
report, the intra-BAN communications between the body sensor units and the body
central unit is based on Bluetooth.
A PROTOTYPE BAN SYSTEM WITH BLUETOOTH
From a general understanding of the BAN and the system requirements, it is evident that possible candidates in implementing BAN should be short range commu¬nication technologies. Bluetooth operates in the 2.4GHz ISM band, from 2400MHz to2483.5MHz .The system employs a frequency-hopping multiple access schemes to combat interference and fading. The symbol rate is 1 M symbol/s supporting a bit rate of 1 Mb/s. For example, ECG signal from each channel are digitized at 360 Hz with 11-bit resolution implying a data rate of 3.84 Kbps per channel, so all 12 channels of ECG data can potentially be transmitted using Bluetooth. In addition, forward error correction (FEC) and automatic repeat request (ARQ) for retransmission are used as authentication of reception to ensure reliable communication. Based on its suitability of BAN, here test a prototype system for BAN using Bluetooth technology. Then will discuss the detailed system in the following .
3.1 A system block diagram
The whole system block diagram is in Figure 3.1. First, the digitized ECG signals are passed through the data compression module in order to reduce the trans¬mission requirement and the needed storage capacity. Then the compressed data are transmitted through the Bluetooth Radio System module. The details of these modules are described in the following sections. At the receiver, the inverse processes are performed to reconstruct the original signals.
3.2 ECG data compression for WBAN
By utilizing the ECG compression techniques, expect to achieve the objective of reducing the amount of digitized ECG data as much as possible while preserving the diagnostic information in the reconstructed signal. The compression ratio (CR) is a measure of the compression performance, defined as the ratio between the number of bits needed to represent the original and the compressed signals. For the error criterion, the percentage root-mean-square difference (PRD) measure is employed. However the clinical acceptability of the reconstructed signal should always be determined through visual inspection by physicians.
However, WBAN applications not only require small reconstruction error (distortion) and high compression ratio (CR), but also require these to come at low complexity. A compression method providing high CR with small distortion can reduce the cost of the wireless data transmission, and make it possible for prolonged local data storage at individual sensors until the detection of an emergency. However, existing ECG data compression approaches either do not achieve both high CR and small distortion, or provide these at very high complexity. On the other hand, low complexity is essential for wireless health monitoring sensors running on batteries, whose power efficiency and endurance can be life-critical. In this section, then propose a simple but highly effective ECG data compression method. Existing data compression techniques for ECG signals can be classified into three main categories:
1) direct data compression methods, 2) transformation methods, and 3) parameter extraction methods.
For the transformation methods, discrete cosine transform (DCT) and wavelet transforms have been widely investigated for lossy data compression. Here proposed method is a 2-stage data compression process that combines a lossy data compression technique and a lossless coding scheme. Both DCT and wavelet transforms have been widely investigated for lossy data compression. Here, the DCT-based transform is used in the first stage of the compression process due to the fact that the frequency of ECG signal concentrates mainly between 0.05 Hz and 130 Hz. Therefore, through DCT transform, we can represent the original ECG signal in a few transformed DCT coef¬ficients, which can achieve higher CR and is in sensitive to noise effect. In addition, the DCT-based method is simpler than wavelet based compression and more flexible to control the CR . After the DCT, the LZW coding is used in order to compress the DCT coefficients in the second stage of the compression process. LZW coding is a lossless dictionary based compression algorithm which looks for repetitive sequences of data and builds a dictionary based on them. Since it is a lossless compression, the percentage root-mean-square difference (PRD) can be well conserved. Therefore, the whole process of the ECG data compression can be summarized as follows:
1. Split the original signal into M blocks, each containing N samples;
2. Transform each block using DCT;
3. Retain K(< N) DCT coefficients;
4. Quantize the K retained DCT coefficients; and
5. Encode the quantized DCT coefficients using LZW coding.
To facilitate comparisons with existing approaches, the PRD is employed to measure the data reconstruction error:where xn is the original data and x~ is the reconstructed data after compression. This method uses a user specified PRD value to find the optimal threshold value for the DCT coefficients via an iterative method, which significantly increases the computational complexity. In general DCTLZW algorithm achieves low PRD and high CR at much lower complexity in comparison with existing alternatives. The low complexity is essential for wireless sensors running on batteries. This is particularly important for healthcare purpose sensors since their endurance can be life-critical. The low PRD and high CR are also important for WBAN. In particular, high CR reduces the cost/energy consumption of wireless transmissions. High CR further allows the sensors built-in memory card to store non-critical data, which can be collected upon the occurrence of an emergency. The high CR allows data storage of a long period pre- and post-emergency .
WIRELESS ECG MONITORING OVER BLUETOOTH
In this section, consider the ECG monitoring over the Bluetooth physical link based on the proposed ECG compression method in the previous section. The overall system block diagram is shown in Fig. 3.1 First, the digitized ECG signals are passed through the data compression module. Then the compressed data is transmitted through the Bluetooth Radio System module. At the receiver, the reverse is performed to reconstruct the ECG signal.
4.1 Bluetooth Radio Link
Here first briefly describe the Bluetooth radio link functions and parameters.
4.1.1 Bluetooth Transmitter
The block diagram of the Bluetooth transmitter is shown in Fig. 4.1. The transmitter uses Gaussian Frequency Shift Keying (GFSK) modulation. A pass band transmitted GFSK signal can be represented as
4.1.2 Bluetooth Receiver
At the receiver,use a simple phase differential demodulator. From the GFSK modulator, we know that bit '1'results in a positive slope in phase and bit '0' results in a negative slope. The phase is extracted by passing the In-phase and Quadrature path of the complex base-band signal to an arc tan block. Then the resulted phase is sampled at T intervals. Denote the phase difference of the nth and (n-1)th samples as A0n . Then the nth transmitted symbol is determined as '1' if A0n is positive and vice versa.
The MIT-BIH Arrhythmia database was used to evaluate the proposed data compression and modulation schemes. In this standard database, the ECG signals were digitized through sampling at 360 Hz with 11-bit resolution. The first 10000 samples of 10 MIT-BIH records have been tested.
4.2.1 ECG data compression performance
For the data record 100, 101, 102, 103, 104, 105, 106, 107, 108, and 109, table 1 gives the simulation results on CR and PRD. As shown in the table, here can achieve a CR of 6:1 to 14.5:1 with the PRD of about 5. The distortion is mainly due to the quantization process in the compression. With the optimization for the quantization and expect to reduce the distortion and achieve a PRD
4.2.2 bit error rate performance
Figure 4.4 shows the plot of BER vs. SNR in the presence of additive white Gaussian noise (AWGN) and the effect of the multipath channel. As we can see in the figures, it takes more than 30 dB SNR to achieve an acceptable BER of the order of 10 3 in the fading channel. This can be potentially improved by designing more optimal and sophisticated receiver schemes.
4.2.3 Overall system performance
Figures 4.5 and 4.6 show the overall system performance with SNR equals to 29dB and 30dB, respectively. Plot (a) in both figures is a segment of the original ECG signal and plot (b) is a segment of reconstructed ECG signal. As we can see, when SNR equals 29dB, the reconstructed signal exhibits severe distortion. When SNR equals 30dB, the calculated PRD is about 95, but the reconstructed signal seems to retain the basic shape and clinical features of the original signal in this case. We can take a close look at one period of the ECG waveform as shown in Figure 4.7, the PRD is relatively high because there are many subtle differences between the original and reconstructed signal, which does not seem to influence the peaks of the general waveform. Therefore, in order to keep the fidelity of the original ECG signal, it appears that the signal to noise ratio must be at least 30 dB, which is fairly high. This will increase the emission power and power consumption and not feasible to BAN with ultra-low power requirement for BAN. A possible solution to this problem is to design more sophisticated demodulation schemes for GFSK modulation in fading channels
ULTRA LOW POWER SENSOR DESIGN FOR WBAN: CHALLENGES, POTENTIAL SOLUTIONS,
A typical sensor node in WBAN should ensure the accurate sensing of the signal from the body, carry out low level processing of the sensed signal, and wireless transmit the processed signal to a local processing unit. The main challenges for successful realization of the sensor nodes can be summarized as follows:
1. The overall size and weight of sensor nodes should be tailored to the human body. It is expected that the sensor nodes could become invisible in order to avoid activity restriction or behavior modification. This requires new integration and pack¬aging technologies.
2. The total energy consumption of sensor needs to be drastically reduced to allow energy autonomy. This is especially important for implantable sensors. As the energy autonomy of current battery-powered sensors is limited, the energy harvesting tech¬nology could be integrated to significantly extend the operating life of sensor nodes.
3. The security of WBAN should be guaranteed to protect the patient's privacy. The sensed signal from the body should have secure and limited access. It should be very important that the sensed signal from one person cannot be mixed up with that from another person.
4. The reliability needs to be paid special attention. An undetected life critical signal could lead to fatal consequences. The improvement of reliability requires minimizing not only wireless communication errors but also sensing and read-out errors.
5. The intelligence should be added to sensors so that each one is capable of storing,
6. processing and transferring signal continuously or on an event-triggered basis. Intelli¬gence could also be introduced at the network level to deal with issues such as network management, data integration and data interpretation.
7. To address the above challenges, the successful design of WBAN requires expertise in wireless communication, digital signal processing, sensing and read-out, energy harvesting, and packaging and integration. Advances in the above key areas facilitates the rapid development of WBAN  .
8. 5.1 Energy Harvesting
9. One of the key considerations in WBAN design is the energy supply of sensor nodes. The size of the energy supply increases with the required store energy and is typically the largest contributor to the size of the sensor node. Thus, the overall power consumption of the sensor nodes is expected to achieve below 1 mW . This expected power demand is sufficiently low such that the harvested energy technology could start to be integrated in the sensor node to partly or fully replace the battery.
10. Energy harvesting is a relatively young research field and has been developed for about 10 years. It takes the energy - mechanical, thermal, or light - from the ambient environment and converts this into electrical energy, which is stored in an energy storage system (ESS). The energy storage system balances the energy gener¬ation and consumption, subsequently, if the mean generated energy is at least equal to the mean consumed energy, there is no more need to replace or externally recharge and monitor the energy storage system during the complete operational lifetime of the device.
11. 5.1.1 Energy Source
12. A) Harvesting Energy from Motion and Vibration
For converting motion or vibration, the principle of inertia has to be used: the trans¬ducer is inserted in a frame, one part of it is fixed to the frame itself, and the other can move. The frame is attached to the moving or vibrating object and relative motion of the parts of the transducer is controlled by the law of inertia (see Figure). This approach is the most widely used for harvesting energy from vibration;in most cases the system is made resonant by means of suspending the moveable part to a spring.
B) Harvesting Energy from Temperature Differences
Thermal energy harvesters are based on the Seebeck effect: when two junctions, made of two dissimilar conductors, are kept at a different temperature an open circuit voltage develops between them.
C) Photovoltaic Harvesting
Photovoltaic (PV) converts incoming photons into electricity. Outdoor these cells have been used for many years, where power densities are available upto 100 mW/cm2. Efficiencies range from 5% to 30%, depending on the material. Indoor the situation is much different, since the illumination levels are much lower than outdoor (100 to 1000 /lW/cm2). Furthermore, at low illumination levels, the efficiency of solar cells will drop considerably. Much research is therefore needed to optimize these cells for low level illuminations.
D) RF Energy Harvesting
Ambient radio frequency (RF) energy, which is available through public telecommu¬nication services e.g. global system for mobile communications (GSM), wireless local area network (WLAN), is also a possible source for energy harvesting. When harvesting energy in the GSM or WLAN band, one has to deal with very low power density levels. For distances ranging from 25 m to 100 m from a GSM base station, power density levels that ranges only from 0.1 mW/m2 to 1.0 mW/m2 may be expected
. For WLAN environments, power density levels that are at least one order of magnitude lower are found . Therefore, neither GSM nor WLAN are likely to produce enough ambient RF energy for wirelessly powering miniature sensors, unless a large area is used for harvesting. Alternatively, the total antenna surface can be minimized if one uses a dedicated RF source, which can be positioned close (a few meters) to the sensor node, thereby limiting the transmission power to levels accepted by interna¬tional regulations.
5.2 Wireless Communication
The name of WBAN clearly indicates that wireless communication is one of the most important aspects in the design of WBAN. The presence of human body poses many new wireless communication challenges.
5.2.1 Propagation Environments
In general, the human body is not a friendly environment for wireless commu¬nication. It is partially conductive and consists of materials of different dielectric constants, thickness, and characteristic impedance. Therefore, the human body can significantly influence the behavior of propagation and lead to high losses. Furthermore, the movement of the body when combined with wave obstruction can lead to significant signal fluctuations.
Thus, a good understanding of the characteristics of propagation environments on, in, or around the body is critical to the design of wireless communication for WBAN. However, for propagation inside the human body, physical measurement and experimental study is hardly to be feasible. One alternative in the current stage is to use a three-dimensional (3D) simulation and visualization scheme . Simulated results in this study have shown that the path loss attenuates much faster with longer distance compared with a free-space transmission scenario as expected. However, as the human body is too complicated and composed of varied components that are non-predictable and will change with a person's age, weight, postures, etc., further vali¬dated results are expected in the future.For propagation on the surface of the human body, or propagation from the surface of the human body to the external device, the physical measurement and experimental study is easier to be performed.
5.2.2 Power Consumption
The wireless communication is often a major power consumer in the sensor node of WBAN. typical commercial chipsets consume in the order of 10 to 100 mW for data rates of 200 to 2000 kbps, leading to a power efficiency of roughly 50 to 400 nJ/bit. The Nordic nRF24L01 achieves less than 20 nJ/bit, but to the expense of a limited set of functionalities. Consider the chipset with the lowest achievable transmission power of 10 mW, a typical battery with a capacity of 1250 mAh and a voltage of 1.5 V could only continuously supply it for around 1 week. The need for replacing or recharging batteries in such a high frequency is normally undesirable for wearable WBAN and unacceptable for implantable WBAN. Thus, the current available wireless technology is already a major bottleneck to impede the further development of WBAN whose expected overall power budget is below 1 mW . For this reason, new ultra low power wireless technologies are required, which could consume one to two orders of magnitude less than today's wireless technologies In IMEC/Holst Centre, the target is to reach an energy efficiency of 1 nJ/bit, which, at a nominal rate of 200 kbps, translates into an average power consumption of 200 /lW. Complemented with novel network and protocol schemes, these ultra-low-power transceivers have the potential to virtually eliminate standby power while still providing the robustness and reliability required for WBAN applications.
One of the widely known solutions to achieve low power consumption is the duty cycling, which means that the signal is transmitted only at a fraction of total transmission time. The duty cycling allows switching on the radio front-ends only for the instants where signals must be transmitted or received, and could thus significantly reduce the average power consumption. In principle, the duty cycling requires that the bandwidth should be larger than the symbol rate. The larger ratio of the bandwidth over the symbol rate could result in the more significant power consumption reduction. Thus, the impulse radio (IR) based ultra-wideband (IR-UWB) is one of the suitable choices. The first full integration of a carrier based IR-UWB transmitter in a standard logic 180 nm complementary metal-oxide-semiconductor (CMOS) technology.
5.3 Digital Signal Processing
As shown in the previous section, wireless communication is a significant power consuming component in the sensor node of WBAN. Typically, the reduction of data rate could result in the reduction of power consumption of wireless communi¬cation. For this reason, the sensor node should be equipped with sufficient intelligence and processing capabilities to extract important features of the raw data sensed, and thus to minimize the amount of data being transferred through wireless communi¬cation. studies showes that for ECG signal monitoring, using ECG delineation algo¬rithm to process the data locally, reduces the data transmission rate and hence the power consumed by the wireless communication by more than 50%. However, this on-node processing will consume additional power to extract and compress information, and thus create a tradeoff between signal processing and wireless communication. To get a positive net power saving, the on-node processing must be done efficiently. For this reason, one of research directions is to design application specific instruction-set processors (ASIP) for body area network applications. We have recently developed an ASIP that consumes 200 /lW tailored for processing 24-channel EEG signal processing in 90 nm technology. Another research direction is to facilitate low power operation of digital part of wireless communication, e.g. MAC protocols and baseband algorithms, by using power management to efficiently control the power distribution of the processors.
5.4 Sensing and Read-Out
The sensing and read-out of the signals may draw a significant part of the power budget in today's sensor nodes in WBAN, especially when the number of signals or channels is increasing. Thus, reducing the power required for signal extraction is an important challenge here. In addition, the acquisition of bio-potential signals, namely
EEG, ECG, EMG and EOG signals, presents an interesting challenge as the signal amplitudes are in the //V range. Various noise sources, such as electrode offset voltage and interference from power-lines, requires high-performance readout circuit design that is capable of rejecting such aggressors while amplifying the weak bio potential signals. Addressing the above challenges, a family of ultra-low-power front-ends for the read-out of bio-potential signals has been developed . The key achievements in these ASICs are their high performance with ultra-low power dissipation. The prior leads to the extraction of clean biopotential signals while the latter ensures the compat¬ibility with battery operated systems. In addition, an important feature of these readout circuits is their programmable gain and filter characteristics enabling their use for different applications that may require the monitoring of different biopotential signals.
Most recently, the design of a complete low-power EEG acquisition ASIC targeted to miniaturized ambulatory EEG acquisition systems . The ASIC consists of eight readout channels, an 11-bit ADC, a square-wave oscillator and a bias circuit. In addition to the acquisition mode, the ASIC has calibration and electrode impedance measurement modes. The prior enables the remote testing of circuit operation, where as the latter is useful for remote assessment of biopotential electrode quality. Both of these features are important in terms of the reliability of sensor nodes in WBAN .
This report carried out a case study on wireless ECG data transmission using Bluetooth technology. To facilitate such a study, first proposed a low complexity ECG compression algorithm by combining DCT and LZW. Although both DCT and LZW are existing techniques, the combination is new. And when compared with existing alternatives, the proposed method gives superb compression performance with very low complexity and high flexibility. These make it very suitable for WBAN applica¬tions with low power and high performance requirements. Then investigated the ECG signal reconstruction performance over a wireless Bluetooth link in fading channels with AWGN. Through this study,found that directly transmitting the raw ECG data is not advantageous compared to the transmission of compressed data. In addition, there exists an optimum ECG compression ratio for the wireless link.
Then overviewed different technologies in the field of energy harvesting, wireless body area networks with the focus on wireless communication, digital signal processing, and sensing and read-out circuits. With the increasing improvement of miniaturization, cost and power consumption of the wireless sensor nodes, we can expect that the autonomous, unobstructed, pervasive, and invisible wireless body sensor network could be commercially realized in the future.
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BODY AREA NETWORK.docx (Size: 1.87 MB / Downloads: 91)
The field of computer science is constantly evolving to process larger data sets and maintain higher levels of connectivity. At same time, advances in miniaturization allow for increased mobility and accessibility. Body Area Networks represent the natural union between connectivity and miniaturization. A Body Area Network (BAN) is defined formally as a system of devices in close proximity to a persons body that cooperate for the benefit of the user. The BBC's Jo Twist gave a more informal definition of Body Area Networks in her article title When technology gets personal Inanimate objects will start to interact with us: we will be surrounded – on streets, in homes, in appliances, on our bodies and possibly in our heads by things that "think". Forget local area networks - these will be body area networks. Twist makes the possibility of BAN sound more like science fiction than a real possibility, but several experts in the field expect to see BAN in production for general use by 2010. While this might seem like an aggressive estimate, when put into context with the history and development of BAN up to this point it becomes a much more achievable goal. In the paper we will start off introducing the reader to the history and development of BAN. We will cover the medical heritage of BAN and how the technology grew from a simple generalization of the concept of Body Sensor Networks (BSN). We will investigate current applications of BAN with an emphasis on applications in the medical sector. As we cover applications of BAN, we will spend a portion of the paper identifying some of technical problems facing BAN. Finally, we will conclude the paper with several solutions currently in development and how they hope to address and overcome the challenges inherent to BAN.
2. History and Development of BAN
BAN technology is still an emerging technology, and as such it has a very short history. BAN technology emerges as the natural byproduct of existing sensor network technology and biomedical engineering. Professor Guang-Zhong Yang was the first person to formally define the phrase "Body Sensor Network" (BSN) with publication of his book Body Sensor Networks in 2006. BSN technology represents the lower bound of power and bandwidth from the BAN use case scenarios. However, BAN technology is quite flexible and there are many potential uses for BAN technology in addition to BSNs. Some of the more common use cases for BAN technology are:
• Body Sensor Networks (BSN)
• Sports and Fitness Monitoring
• Wireless Audio
• Mobile Device Integration
• Personal Video Devices
Each of these use cases have unique requirements in terms of bandwidth, latency, power usage, and signal distance. IEEE 802.15 is the working group for Wireless Personal Area Networks (WPAN).The WPAN working group realized the need for a standard for use with devices inside and around close proximity to the human body. IEEE 802.15 established Task Group #6 to develop the standards for BAN. The BAN task group has drafted a (private) standard that encompasses a large range of possible devices. In this way, the task group has given application and device developers the decision of how to balance data rate and power. Figure 1, below, describes ideal position for BAN in the power vs data rate spectrum.
Figure 1 - Data Rate vs Power
As you can see the range of BAN devices can vary greatly in terms of bandwidth and power consumption. The BAN draft requirements, displayed below, add a common set of requirements as to ensure that all devices conform to a similar set of behaviors yet still encompass a wide variety of devices as previously mentioned.
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THANKS ITS VERY GOOD PLZ TELL ME ANY GOOD MAGZINE TO BE UP TO DATE??
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to get information about the topic Human area Network full report ppt and related topic refer the link bellow