Monday, January 27, 2020

Developing a Brain Computer Interface

Developing a Brain Computer Interface A Seminar Report On â€Å"Brain Computer Interface† Submitted by: Name: Sachin Kumar Roll No: 1214310301 ABSTRACT Brain Computer Interface allows users to communicate with each others by using only brain activities without using any peripheral nerves and muscles of human body. On BCI research the Electroencephalogram (EEG) is used for recording the electrical activity along the scalp. EEG is used to measure the voltage fluctuations resulting from ionic current flows within the neurons of the brain. Hans Berger a German neuroscientist, in 1924 discovered the electrical activity of human brain by using EEG. Hans Berger was the first one who recorded an Alpha Wave from a human brain. In 1970, Defense Advanced Research Projects Agency of USA initiated the program to explore brain communication using EEG. The papers published after this research also mark the first appearance of the expression brain–computer interface in scientific literature. The field of BCI research and development has since focused primarily on neuroprosthetics applications that aim at restoring damaged hearing, sight and movement. Nowadays BCI research is going on in a full swing using non-invasive neural imaginary technique mostly the EEG. The future research on BCI will be dependent mostly in nanotechnology. Research on BCI is radically increased over the last decade. From the last decade the maximum information transfer rates of BCI was 5-25 bits/min but at present BCI’s maximum data transfer rate is 84.7bits/min. 2.INTRODUCTION Brain-computer interface (BCI) is alliance between a brain and a device that enables signals from the brain to direct some external activities, such as control of a cursoror a prosthetic limb. The Brain computing interface enables a direct communications pathway between the brain and the object to be controlled. For example, the signal is transmitted directly from the brain to the mechanism directing the cursor moves, rather than taking the normal ways through the bodys neuromuscular system from the brain to the finger on a mouse then directing the curser. BCIs Research began in the 1970s at the University of California Los Angeles(UCLA) under an allowance from the   National Science Foundation, followed by a contract fromDARPA. Thanks to the remarkable cortical plasticity of the brain, signals from implanted prostheses can, after adaptation, be handled by the brain like natural sensor or effector channels. Animal experimentation for years, the first neuroprosthetic devices implanted in humans appeared in the mid-1990s. Current brain computing interface devices require calculated conscious thought; some future applications, such as prosthetic control, are likely to work without difficulty. Development of electrode devices and/or surgical methods that are minimally invasive is one of the biggest challenges in developing BCI technology . Though Brain Computer Interface (BCI) facilitates direct communication between brain and computer or another device so nowadays it is widely used to enhance the possibility of communication for people with severe neuromuscular disorders, spinal cord injury. Except the medical applications BCI is also used for multimedia applications, which becomes possible by decoding information directly from the user’s brain, as reflected in electroencephalographic (EEG)signals which are recorded non-invasively from user’s scalp. 3.LITERATURE REVIEW Current Trends in Graz Brain–Computer Interface (BCI) Research Pfurtscheller, C. Neuper, C. Guger, W. Harkam, H. Ramoser, Schlà ¶gl, B. Obermaier, and M. Pregenzer The â€Å"Graz Brain–Computer Interface† (BCI) project is aimed at developing a technical system that can support communication possibilities for patients with severe neuromuscular disabilities, who are in particular need of gaining reliable control via non-muscular devices. This BCI system uses oscillatory electroencephalogram (EEG) signals, recorded during specific mental activity, as input and provides a control option by its output. The obtained output signals are presently evaluated for different purposes, such as cursor control, selection of letters or words, or control of prosthesis. Between 1991 and 2000, the Graz BCI project moved through various stages of prototypes. In the first years, mainly EEG patterns during willful limb movement were used for classification of single EEG trials. In these experiments, a cursor was moved e.g. to the left, right or downwards, depending on planning of left hand, right hand or foot movement. Extensive off-line analyses have shown that classification accuracy improved, when the input features, such as electrode positions and frequency bands, were optimized in each subject. Apart from studies in healthy volunteers, BCI experiments were also performed in patients, e.g., with an amputated upper limb. The main parts of any BCI system are: Signal acquisition system: involves the electrodes, which pick up the electrical activity of the brain and the amplifier and analog filters. The feature extractor: converts the brain signals into relevant feature components. At first, the EEG raw signals are filtered by a digital band pass filter. Then, the amplitude samples are squared to obtain the power samples. The power samples are averaged for all trials. Finally, the signal is smoothed by averaging over time samples. The feature translator: classifies the feature components into logical controls. The control interface: converts the logical controls into semantic controls. The device controller: changes the semantic controls to physical device commands, which differ from one device to another depending on the application. Finally, the device commands are executed by the device. The early work of BCI was done by  invasive  methods with electrodes inserted into the brain tissue to read the signals of a single neuron. Although the spatio-temporal resolution was high and the results were highly accurate, there were complications in the long term. These were mostly attributable to the scar tissue formation, which leads to a gradual weakening of the signal and even complete signal loss within months because of the brain tissue reaction towards the foreign objects. A proof of concept experiment was done by Nicolelis and Chapin on monkeys to control a robotic arm in real time using the invasive method. Recently, less invasive methods have been used by applying an array of electrodes in the subdural space over the cortex to record the Electrocorticogram (ECoG) signals. It has been found that ordinary Electroencephalogram pickup signals are averaged over several EEG signal bands (Hz) square inches, whereas ECoG electrodes can measure the electrical activity of brain cells over a much smaller area, thereby providing much higher spatial resolution and a higher signal to noise ratio because of the thinner barrier tissue between the electrodes and the brain cells. The superior ability to record the gamma band signals of the brain tissue is another important advantage of this type of BCI system. Gamma rhythms (30-200 Hz) are produced by cells with higher oscillations, which are not easy to record by ordinary EEGs. The human skull is a thick filter, which blurs the EEG signals, especially the higher frequency bands (i.e. gamma band). Noninvasive  techniques were demonstrated mostly by electroencephalographs (EEG). Others used functional Hz, Magneto-Resonance Imaging (fMRI), Positron Electron Tomography (PET), Magneto encephalography (MEG) and Single Photon Emission Computed Tomography There (SPECT). EEGs have the advantage of higher temporal resolution, reaching a few milliseconds and are relatively low cost. Recent EEG systems have better spatiotemporal resolution of up to 256 electrodes over the total area of the scalp. Nevertheless, it cannot record from the deep parts of the brain. This is the main reason why the multimillion dollar fMRI systems are still the preferred method for the functional study of the brain. However, EEG systems are still the best candidate for BCI systems spatial as they are easy to use, portable and cheap. The main problems that reduce the reliability and accuracy of BCI and which prevent this technology from being clinically useful, are the sensory interfacing problems and the translation algorithm problems. In order to make a clinically useful BCI the accuracy of the detection of intention needs to be very high and certainly much higher than the currently achieved accuracy with different types of BCI. The intermediate compromise between accuracy and safety is the ECoG based BCI, which has shown considerable promise. The sensory arrays of electrodes are less invasive and provide comparable accuracy and high spatial resolution compared to the implanted type. The ECoG based BCI needs much less training than the EEG based BCI and researchers have shown that highly accurate and fast response. 4.TECHNICAL DETAILS REASON BEHIND WORKING: The reason a BCI works at all is because of the way our brains function. Our brains are filled with  neurons, individual nerve cells connected to one another by dendrites and axons. Every time we think, move, feel or remember something, our neurons are at work. That work is carried out by small electric signals that zip from neuron to neuron as fast as 250 mph. The signals are generated by differences in electric potential carried by ions on the membrane of each neuron. Although the paths the signals take are insulated by something called myelin, some of the electric signal escapes. Scientists can detect those signals, interpret what they mean and use them to direct a device of some kind. It can also work the other way around. For example, researchers could figure out what signals are sent to the brain by the optic nerve when someone sees the color red. They could rig a camera that would send those exact signals into someones brain whenever the camera saw red, allowing a blind person to see without eyes. BCI INPUT AND OUTPUT: One of the biggest challenges facing brain-computer interface researchers today is the basic mechanics of the interface itself. The easiest and least invasive method is a set of electrodes a device known as an  electroencephalograph(EEG) attached to the scalp. The electrodes can read brain signals. However, the skull blocks a lot of the electrical signal, and it distorts what does get through. To get a higher-resolution signal, scientists can implant electrodes directly into the gray matter of the brain itself, or on the surface of the brain, beneath the skull. This allows for much more direct reception of electric signals and allows electrode placement in the specific area of the brain where the appropriate signals are generated. This approach has many problems, however. It requires invasive surgery to implant the electrodes, and devices left in the brain long-term tend to cause the formation of scar tissue in the gray matter. This scar tissue ultimately blocks signals. Regardless of the location of the electrodes, the basic mechanism is the same: The electrodes measure minute differences in the voltage between neurons. The signal is then amplified and filtered. In current BCI systems, it is then interpreted by a computer program, although you might be familiar with older analogue encephalographs, which displayed the signals via pens that automatically wrote out the patterns on a continuous sheet of paper. In the case of a sensory input BCI, the function happens in reverse. A computer converts a signal, such as one from a video camera, into the voltages necessary to trigger neurons. The signals are sent to an implant in the proper area of the brain, and if everything works correctly, the neurons fire and the subject receive a visual image corresponding to what the camera sees. SENSORY INPUT: The most common and oldest way to use a BCI is a cochlear implant. For the average person, sound waves enter the ear and pass through several tiny organs that eventually pass the vibrations on to the auditory nerves in the form of electric signals. If the mechanism of the ear is severely damaged, that person will be unable to hear anything. However, the auditory nerves may be functioning perfectly well. They just arent receiving any signals. A cochlear implant bypasses the non functioning part of the ear, processes the sound waves into electric signals and passes them via electrodes right to the auditory nerves. The result: A previously deaf person can now hear. He might not hear perfectly, but it allows him to understand conversations. The processing of visual information by the brain is much more complex than that of audio information, so artificial eye development isnt as advanced. Still, the principle is the same. Electrodes are implanted in or near the visual cortex, the area of the brain that processes visual information from the retinas. A pair of glasses holding small cameras is connected to a computer and, in turn, to the implants. After a training period similar to the one used for remote thought-controlled movement, the subject can see. Again, the vision isnt perfect, but refinements in technology have improved it tremendously since it was first attempted in the 1970s. Jens Naumann was the recipient of a second-generation implant. He was completely blind, but now he can navigate New York Citys subways by himself and even drive a car around a parking lot. In terms of science fiction becoming reality, this process gets very close. The terminals that connect the camera glasses to the electrodes in Naumanns b rain are similar to those used to connect the VISOR (Visual Instrument and Sensory Organ) worn by blind engineering officer Geordi La Forge in the Star Trek: The Next Generation TVshow and films, and theyre both essentially the same technology. However, Naumann isnt able to see invisible portions of the electromagnetic spectrum. Applications: Applications of BCI are described as follows: Neurogaming: Currently, there is a new field of gaming called Neurogaming, which uses non-invasive BCI in order to improve gameplay so that users can interact with a console without the use of a traditional controller. Some Neurogaming software use a players brain waves, heart rate, expressions, pupil dilation, and even emotions to complete tasks or effect the mood of the game. For example, game developers at Emotiv have created non-invasive BCI that will determine the mood of a player and adjust music or scenery accordingly. This gaming experience will introduce a real-time experience in gaming and will introduce the ability to control a video game by thought. Prosthesis control: Non-invasive BCIs have also been applied to enable brain-control of prosthetic upper and lower extremity devices in people with paralysis. For example, Gert Pfurtscheller of Graz University of Technology and colleagues demonstrated a BCI-controlled functional electrical stimulation system to restore upper extremity movements in a person with tetraplegia due to spinal cord injury. Between 2012 and 2013, researchers at the University of California, Irvine demonstrated for the first time that it is possible to use BCI technology to restore brain-controlled walking after spinal cord injury. Synthetic telepathy/silent communication: In a $6.3 million Army initiative to invent devices for telepathic communication, Gerwin Schalk, underwritten in a $2.2 million grant, found that it is possible to use ECoG signals to discriminate the vowels and consonants embedded in spoken and in imagined words. The results shed light on the distinct mechanisms associated with production of vowels and consonants, and could provide the basis for brain-based communication using imagined speech. On February 27, 2013Duke University researchers successfully connected the brains of two rats with electronic interfaces that allowed them to directly share information, in the first-ever direct brain-to-brain interface. MEG and MRI: Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) have both been used successfully as non-invasive BCIs. In a widely reported experiment, fMRI allowed two users being scanned to play Pongin real-time by altering their haemodynamic response or brain blood flow through biofeedback techniques. fMRI measurements of haemodynamic responses in real time have also been used to control robot arms with a seven second delay between thought and movement. Neural Internet: Access to the internet opens a myriad of opportunities for those with severe disabilities, including shopping, entertainment, education, and possibly even employment. Neural control users cannot control a cursor with a great degree of precision, so, therefore, the challenge of adapting a web browser for neural control is in making links—which are spatially organized—accessible. The University of Tuebingen developed a web browser controller to be used with their thought translation device, but it requires the user to select from an alphabetized list of links, causing problems if the link names are identical. They have developed a neurally controlled web browser that serializes the spatial internet interface and allows logical control of a web application. BrainTrainer—Subject Training: The BrainTrainer project researches the most effective ways of teaching a person the brain-signal control needed to interact with a device. The BrainTrainer toolset allows researchers to compose trials by providing simple tasks, such as targeting, navigation, selection, and timing, that can be combined to produce an appropriate-level task for a particular subject.

Sunday, January 19, 2020

Humorous Speech by an Old Friend of the Groom (Bridegroom) :: Wedding Toasts Roasts Speeches

Humorous Speech by an Old Friend of the Groom (Bridegroom) Good afternoon, Ladies and Gentlemen. On behalf of the bridesmaids, I would like to thank Michael for his kind words, and I have to say they were absolutely wonderful and have done an excellent job today - I mean the bridesmaids, not the words. Now, it's customary in these speeches to tell a story about the bachelor’s (stag) party, but in this case it won't be possible. That's because Michael has insisted on having his stag party after the wedding. So instead, I was going to tell you about a night out in the big city that Michael and I recently had, which involved beer, bad food and Michael bent over the toilet all night. But this is Magdalene’s day as well, and I don't want to ruin it with Michael's vulgarity. So I've decided to look elsewhere for my material. I started by writing down everything I could think of that Michael and I have done over the 23 years we've been friends (mates). But even this wasn't particularly fruitful, as a lot of it would have got Michael strung up by his mom (mum), some of it would have got me strung up by my mom (mum) and some of it simply involved Michael stringing himself up with a couple of vacuum cleaners within easy reach. So, as it was quite challenging coming up with anything of real substance to tell you about Michael, I thought I’d explain how our bride and groom got together. ‘The romance began,’ as Magdalene describes it, ‘after an outing to the cinema was arranged with five or six mutual friends. But on the night, only Michael and I could make it. We enjoyed each other's company so much we went out together every evening for the rest of the week.’ ‘The romance began,’ as Michael describes, ‘after Magdalene individually bribed six people to pull out of a trip to the cinema so she could finally have an evening alone with me to curse me with her love spell.’ There also seems to be some confusion over which film they saw together that night. Magdalene remembers it to be 'Demolition Man'. Michael remembers it as 'Free Willy'. Despite meeting Magdalene, Michael didn’t desert me and we pursued our interests in gambling, excessive drinking, Playstation and being sick a lot. For me, the most significant moment during this time was Michael getting his ear pierced - even back then he was preparing for marriage - experiencing pain, hurt and buying jewellery.

Saturday, January 11, 2020

Channel Conflict Analysis of Schwinn Essay

With Schwinn’s recent expansion into many large-scale retail stores (i. e. Wal-Mart, Toys-R-Us, Target, etc. ), they began to shift into a dual channel marketing strategy. Often times, if not handled properly, this type of approach can result in significant problems for some or all of the distribution channel partners. Fortunately for Schwinn however, they were able to make many critical decisions which ensured that each of the partners’ distinct interests was narrowly aligned with their own. This proactive plan not only motivated many of their smaller independent bicycle dealers to continue carrying their products but it also allowed Schwinn to effectively reach a much larger segment of their target market. By closely analyzing this case, we can learn many valuable lessons regarding the overall importance of strong channel management. Product differentiation was one of the primary ways that Schwinn managed to avoid channel conflict. Schwinn segmented the market and delivered to the different segments of the market through different channels. The product line delivered through the mass market channel consisted of completely different bicycles than those found at the independent bicycle dealers. This segmentation reduced the likelihood of conflict between the two channels, since the two product lines were targeted at segments with little to no crossover. Additionally, Schwinn introduced products like the Sting Ray which had nostalgic appeal and stretched beyond the traditional customer base of the independent bicycle dealers. These types of bicycles provided them with a unique product and furthermore a healthy margin to bolster profits. By maintaining distinct product lines for their two channels, Schwinn was able to minimize multi-channel conflict. The key to motivating channel members is to provide value and benefits to each partner in order to align interests and thus achieve the ultimate goal: satisfy the customer’s needs. Schwinn used both push and pull strategies effectively. By offering a relatively higher margin level than other high-end manufacturers catering to independent bicycle dealers, they were able to restore the confidence and interest of their long term retailers in spite of going for a dual channel strategy. Moreover, as mentioned in the article, unlike most companies in the industry, there was no complicated loyalty formula required to get the best prices from Schwinn. In addition, Schwinn did not require specific pre-order sales in order to carry their products. Instead, suppliers were granted flexible purchasing options so they did not have to unnecessarily stock inventories during their off-seasons (i. e. winter months in cold climates). This push strategy not only reduced the administrative cost of the retailers, but also improved the inventory turnover and ultimately the retailers’ bottom line. Conversely, Schwinn was also able to simultaneously create a pull strategy after they utilized the extensive media exposure of products, such as the Sting Ray, to increase the brand recognition among customers thus drawing them to the independent bicycle dealers. In addition to this, the specialty storeowners found significant profits lying in the repairing of these bikes and selling of parts/accessories. This proved to be a great factor for specialty bike owners to remain in business while selling Schwinn. They had a clear edge over other big retailers like Wal-Mart who did not provide any after sales service to its customers. Because they were making money by servicing the bikes sold at the mass market stores, the independent bicycle dealers were more tolerant of losing some sales on the edge of their segment to Wal-Mart, Target, Toys-R-Us, etc. Schwinn has done a good job of heading off any channel conflict by keeping the incentives aligned for its two main distribution channels. By expanding its product line into major retailers, the company has been able to target a new segment of casual bike riders. With Schwinn’s new line of entry-level bikes, big-box stores can satisfy the needs of casual bike riders by offering a large selection of affordable bikes at convenient locations. Meanwhile, Schwinn still provides a number of incentives to local bike shops, which form the company’s other main distribution channel. These shops still profit from service and repair, which large retailers do not offer. Additionally, some of Schwinn’s higher-end models are exclusively available in bike shops. Finally, Schwinn is flexible with its inventory requirements and offers good margins. By offering different incentives to each of its distribution channels, Schwinn has been able to target more customers while also keeping its retailers happy.

Friday, January 3, 2020

Psychological State of Madness - 1088 Words

Madness is the psychological state of someone who has severe emotional or behavioral problems that require intervention. It is the spectrum of behavior characterized by mental or behavioral patterns deemed abnormal by societal norms, manifesting as violations of acceptable actions, roles, and beliefs of society. The Yellow Wallpaper by Charlotte Perkins Gilman centers on the deteriorating mental condition of the female narrator. Gilman demonstrates the progression of her madness through the restriction of her self-expression. As a woman in the 19th century, the narrator exists in a subservient role to her husband and has inferior social status to men. Her social standing dictates that she is not allowed to participate in her own treatment or diagnosis and is completely forced to succumb to everything in which her doctor, who is her husband, dictates. This lack of control contributes to her descent into madness. 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