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Yen Tzu Chang, Fraunhofer MEVIS, Ars Electronica

Biographie

Yen Tzu Chang ist taiwanesische Medienkünstlerin. Sie lebt und studiert in Linz, Österreich, seit 2014. Sie hat einen Bachelor-Abschluss des New Media Art Instituts an der Taipei National University of Art. Seit 2011 arbeitet sie in verschiedenen Bereichen wie interdisziplinäre Kunst und experimentelle Performances, die auf Sound-Installationen basieren. Ihre frühen Arbeiten beschäftigten sich mit audiovisuellen Inhalten und Installationen, gemischt mit Videokunst. „One kind of language…“ handelte als eine Art Wissenschaftsvideo über einen Tausendfüßler, der über zwei Bildschirme spazierte. In dieser Zeit entdeckte sie immer mehr ihr Interesse an Installationen, das sie mit ihrer Erfahrung auf der Bühne kombinierte. Sie begann, eigene elektronische Instrumente zu bauen. „Time Travel“ und „Self-luminous“ gehörten zu einer Serie an sehr erfolgreichen Lichtinstallationen in ihrer bisherigen Karriere.

Credits STEAM Imaging

Das Projekt “STEAM Imaging” wurde anfangs von Fraunhofer MEVIS in Zusammenarbeit mit SPACE in London im Jahr 2016 entwickelt.

Yen Tzu Chang: Whose scalpel

Whose scalpel is a sound performance combined with visual and 3D printed installation, realized with an application framework for medical image processing. Mixing several methods from art and science, it is an imagination of the future and presents the issues of the relationship between human and machine during heart surgery. The concept is developed from three different areas—the application of sound in medical science, coronary artery bypass surgery, and machine learning. The background story of the performance is based on the assumption that in the near future a surgeon works with the machine that can give advice during surgery. Sound is chosen as the media of the performance because it helps to create a scene and atmosphere. On the other hand, sound plays an important role in medicine. For instance, it is well known that the heart pumps blood through the whole human body with a regular frequency, which can be used to help diagnosis. Another famous application of sound in medicine is the stethoscope, which was invented in the 19th century for auscultation and allows listening to the internal sound of organs in the chest such as lungs and heart. Another state of the art example is the video from the Fraunhofer MEVIS YouTube channel, Auditory guidance prototype for navigated liver surgery1. The video shows that if the scalpel deviates from the correct cutting path, the device will make a different sound to notify the surgeon.

The heart as one of the most important human organs—both from the perspective of biology or symbolism in the society is the focus of the surgery. The heart is an installation, which is built according to the performer’s real heart from MRI scans, but is larger than its actual size. It is printed out by a 3D printer and surrounded by aluminum structures. To make the heart installation like a musical instrument, the inner part of it is equipped with Arduino, LED, and electronic components and the surface is covered with silicon and transparent vessels. It is designed to interact when the performer plugs in audio cables and bridges connections, similar to the method of coronary artery bypass surgery. Coronary artery bypass surgery is a type of heart surgery used for treating coronary artery disease, caused by the inner wall of arteries becoming blocked by fat. To supply enough oxygenated blood to the heart muscle, the doctor takes the blood vessels (or grafts) from the patient's leg, chest, or wrist and places it above and below the end of the blocked area so that the blood can go through the new grafts to reach the heart muscle.2 This method enables blood to flow through the new path, and it is a similar approach with operating a modular synthesizer to some extent, which is about letting the signal go through one modular to the other to produce the sound. In the heart installation, plugging in the cables, as a similar act, triggers the sound from Pure Data.

The AI is another character in the performance. It is created according to the technology trend. Since Alan Turing, an English computer scientist, submitted his article “Computing Machinery and Intelligence,”3 a new era began and the question: “Can machines think?” was raised. One large topic in artificial intelligence is machine learning, which, according to American pioneer Arthur Samuel means, “giving computers the ability to learn without being explicitly programmed”.4 The theory of it is, by designing algorithms to analyze portions of data, insights may be discovered and predictions may be made. Machine learning has been applied in many fields. In the medical field, machine learning is applied in diagnosis. According to Fraunhofer’s 2016 press publication, it can help physicians to distinguish tumors from CT and MRI scans.5

In the performance, an artistically imagined AI will be in charge of more important medical tasks such as analyzing the patient’s body condition and giving doctors suggestions with sound and visuals in future surgery. The storyline is led by the sound and the mixed video of medical images and live performance from the webcam. The goal of the performer as a surgeon during surgery is to cure the heart, which symbolizes human consciousness and faith. The AI, which is regarded as a perfect model, gives instruction to the performer. Maybe the question “If machines can reason even better than humans, will we as humans lose some abilities and not even believe ourselves anymore?” is worth thinking about since the issue is already present.

1 Christian Hansen, David Black, Christoph Lange, Fabian Rieber, Wolfram Lamadé, Marchello Donati, Karl J. Oldhafer, and Horst K. Hahn. Auditory guidance prototype for navigated liver surgery. Computer Support for Image-Based Medicine, Fraunhofer Institute for Medical Image Computing MEVIS. URL: https://youtu.be/gCg5nJSI2pY [accessed 2017-02-07].
2 Johns Hopkins Medicine, Health Library, Coronary Artery Bypass Graft Surgery. URL: http://www.hopkinsmedicine.org/healthlibrary/test_procedures/cardiovascular/ coronary_artery_bypass_graft_surgery_cabg_92,P07967/ [accessed 2017-07-02].
3 Turing, Alan M. “Computing machinery and intelligence.” Mind 59.236 (1950): 433-460.
4 Munoz, Andres. “Machine Learning and Optimization.” URL: https://www. cims. nyu. edu/~ munoz/files/ml_optimization. Pdf [accessed 2016-03-02][WebCite Cache ID 6fiLfZvnG] (2014).
5 Fraunhofer. Machine learning to help physicians. URL: https://www.fraunhofer.de/en/press/ research-news/2016/november/machine-learning-to-help-physicians.html [accessed 2017-07-02].

(Source: The Practice of Art and Science, p. 53-55)