Publications

IEEE VR 2020, OSAKA

Journal Articles

J1. Batmaz AU, Maiero J, Riecke B, Kruijff E, Carman N, Stuerzlinger W (2020, to appear) How Automatic Speed Control Based on Distance Affects User Behaviours in Telepresence Robot Navigation within Dense Conference-like Environments. PLoS ONE, vol. 15, no.11, pp 1-41.

J2. Steed A, Ortega F, Williams A, Kruijff E, Stuerzlinger W, Batmaz AU, Won A, Rosenberg ES, Simeone A, Hayes A (2020) Evaluating Immersive Experiences During COVID-19 and Beyond. Interactions, ACM, 27(4), pp. 62–67.

J3. Batmaz AU, de Mathelin M, Dresp-Langley B (2018) Effects of 2D and 3D image views on hand movement trajectories in the surgeon’s peri-personal space in a computer controlled simulator environment. Cogent Medicine, vol. 4, no.1, pp. 1-16.

J4. Batmaz AU, de Mathelin M, Dresp-Langley B (2017) Seeing virtual while acting real: Visual display and strategy effects on the time and precision of eye-hand coordination. PLoS ONE, vol. 12, no.8, pp 1-18.

J5. Batmaz AU, de Mathelin M, Dresp-Langley B (2016) Getting nowhere fast: trade-off between speed and precision in training to execute image-guided hand-tool movements. BMC Psychology, vol. 4, no. 1, pp. 1-19.

J6. Batmaz AU, Yildiz HU, Tavli B (2014) Role of unidirectionality and reverse path length on wireless sensor network lifetime. IEEE Sensors Journal, vol. 14, no.11, pp. 3971-3982.

J7. Batmaz AU, Elbir O, Kasnakoglu C (2013) Design of a quadrotor roll controller using system identification to improve empirical results. IJMMM 2013, vol. 1, no.4, pp. 347-349.

Conference Articles

C1. Batmaz AU, Stuerzlinger W (2021, in press) The Effect of Pitch in Auditory Error Feedback for Fitts’ Tasks in Virtual Reality Training Systems. In Proceedings of IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Virtual Event, 10 pages.

C2. Batmaz AU, Sun X, Taskiran D, Stuerzlinger W (2020) Eye-Hand Coordination Training for Sports with Mid-air VR. In Proceedings of ACM VRST 2020, Virtual Event, pp. 585-592.

C3. Batmaz AU, Rajabi Seraji M, Kneifel J, Stuerzlinger W (2020) No Jitter Please: Effects of Rotational and Positional Jitter on 3D Mid-Air Interaction. In proceedings of Future Technologies Conference, Springer Verlag, Virtual Event, pp. 792-808.


C4. Batmaz AU, Mutasim AK, Malekmakan M, Sadr E, Stuerzlinger W (2020) Touch the Wall: Comparison of Virtual and Augmented Reality with Conventional 2D Screen Eye-Hand Coordination Training Systems. In Proceedings of IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Atlanta, Georgia, USA, 11 pages.


C5. Batmaz AU, Sun X, Taskiran D, Stuerzlinger W (2019) Hitting the Wall: Mid-Air Interaction for Eye-Hand Coordination. In Proceedings of ACM VRST 2019, Sydney, Australia, 5 pages.


C6. Batmaz AU, Barrera Machuca MD, Pham DM, Stuerzlinger W (2019) Do Head-Mounted Display Stereo Deficiencies Affect 3D Pointing Tasks in AR and VR? In Proceedings of IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Osaka, Japan, pp. 585-592.

C7. Batmaz AU, de Mathelin M, Dresp-Langley B (2018) Effects of image size and structural complexity on time and precision of hand movements in head mounted virtual reality. In Proceedings of IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Reutlingen, Germany, pp. 167-174.


C8. Batmaz AU, Falek MA, Zorn L, Nageotte F, Zanne P, de Mathelin M, Dresp-Langley B (2017) Novice and expert haptic behaviours while using a robot controlled surgery system. In 13th IASTED International Conference on Biomedical Engineering (BioMed), Innsbruck, Austria, pp. 94-99.

C9. Batmaz AU, Tavli B, Incebacak D, Bicakci K (2013) The impact of link unidirectionality and reverse path length on wireless sensor network lifetime. In IEEE International Conference on Communications (ICC), Budapest, Hungary, pp. 1795-1799.


C10. Batmaz AU, Elbir O, Kasnakoglu C (2013) Quadrotor roll and pitch stabilization using system identification based redesign of empirical controller. In Proceedings of the 36th IASTED Inter-national Conference on, Modelling, Identification and Control (MIC), Innsbruck, Austria, pp. 1-5.

C11. Elbir O, Batmaz AU, Kasnakoglu C (2013) Improving quadrotor 3-axes stabilization results using empirical results and system identification. In Proceedings of 9th Asian Control Conference (ASCC), Istanbul, Turkey, pp. 1-5.

C12. Batmaz AU, Tavli B, Incebacak D, Bicakci K (2013) Effects of handshake of length of unidirectional links on the lifetime of wireless sensor networks. In Proceedings of 21st Signal Processing and Communications Applications Conference (SIU), Kyrenia, Cyprus, pp. 1-4.

C13. Batmaz AU, Ertin O, Elbir O (2013). Preliminary design of remote mine sweeping and identification systems. In Proceedings of the Mechatronics Engineering Student Congress Conference, Ankara, Turkey, pp. 9-16.

Workshop Papers

W1.Batmaz AU, Stuerzlinger W (2021, to appear) Effects of Different Auditory Feedback Frequencies in Virtual Reality 3D Pointing Tasks. Workshop on Novel Input Devices and Interaction Techniques (NIDIT) 2021, part of IEEE VR 2021, Lisbon, Portugal, Virtual Event, 6 pages.

W2. Batmaz AU, Mutasim AK, Stuerzlinger W (2020). Precision vs. Power Grip: A Comparison of Pen Grip Styles for Selection in Virtual Reality. Workshop on Novel Input Devices and Interaction Techniques (NIDIT) 2020, part of IEEE VR 2020, Atlanta, Georgia, USA, 6 pages.

W3. Batmaz AU, Stuerzlinger W (2019) Effects of 3D Rotational Jitter and Selection Methods on 3D Pointing Tasks. Workshop on Novel Input Devices and Interaction Techniques (NIDIT) 2019, part of IEEE VR 2019, Osaka, Japan, pp. 1687-1692.

Posters

P1. Batmaz AU, Stuerzlinger W (2020) Effect of Fixed and Infinite Ray Length on Distal 3D Pointing in Virtual Reality. In CHI Conference on Human Factors in Computing Systems Extended Abstracts (CHI ’20 Extended Abstracts), April 25-30, 2019, Honolulu, Hawaii USA. ACM, New York, NY, USA, 6 pages, to appear.

P2. Mutasim AK, Batmaz AU, Stuerzlinger W (2020) Gaze Tracking for Eye-Hand Coordination Training Systems in Virtual Reality. In CHI Conference on Human Factors in Computing Systems Extended Abstracts (CHI ’20 Extended Abstracts), April 25-30, 2019, Honolulu, Hawaii USA. ACM, New York, NY, USA, 6 pages.

P3. Batmaz AU, Stuerzlinger W (2019) The Effect of Rotational Jitter on 3D Pointing Tasks. In CHI Conference on Human Factors in Computing Systems Extended Abstracts (CHI ’19 Extended Abstracts), May 4–9, 2019, Glasgow, Scotland UK. ACM, New York, NY, USA, 6 pages.

P4. Batmaz AU, de Mathelin M, Dresp-Langley B (2019). Different sound pitch effects on motor performance of individuals in head-mounted virtual reality. Perception, 48 (ECVP Supplement), Trieste, Italy, pp. 21.

P5. Batmaz AU, de Mathelin M, Dresp-Langley B (2017) Effects of relative target position on ipsilateral and contralateral manual operations in head-mounted virtual reality. European Conference on Visual Perception (ECVP), Berlin, Germany, pp. 83.

P6. Batmaz AU, de Mathelin M, Dresp-Langley B (2016) Effects of indirect screen vision and tool-use on the time and precision of object positioning on real-world targets. Perception, 45 (ECVP Supplement), Barcelona, Spain, pp. 196.

Talks

T1. Virtual Reality challenged by the image guided surgery (Invited) (2013) Réalité Virtuelle Et Réalité Augmentée Au Service De L’ingénieur De Demain, Paris France.

T2. Inside the virtual brain: using OCULUS DK2 for surgical planning (May 2017) The Annual World Congress of Neurotalk, Barcelona, Spain.

PhD. Thesis

I was working with Dr. Birgitta Dresp-Langley and Professor Michel de Mathelin between October 2015 and July 2018 on an IDEX project called “Tactile exploration of complex object space with or without direct visual input” at University of Strasbourg, France.

Thesis cover page

The aim of this study was to understand in which extend the human perceptual system adapts to conditions of multisensorial contains for planning, control, and execution of complex tasks.

My Ph.D. thesis consists of 3 chapters and 9 studies. I was able to publish 9 different publications from my Ph.D. studies.

  1. Batmaz AU, de Mathelin M, Dresp-Langley B (2016). Effects of indirect screen vision and tool-use on the time and precision of object positioning on real-world targets. Perception, 45(ECVP Supplement), 196.  http://journals.sagepub.com/doi/full/10.1177/0301006616671273  
  2. Batmaz AU, de Mathelin M, Dresp-Langley B (2016) Getting nowhere fast: trade-off between speed and precision in training to execute image-guided hand-tool movements. BMC Psychology, 4(1), 55. https://doi.org/10.1186/s40359-016-0161-0 
  3. Batmaz AU, de Mathelin M, Dresp-Langley B (2017) Seeing virtual while acting real: Visual display and strategy effects on the time and precision of eye-hand coordination. PLoS ONE 12(8): e0183789. https://doi.org/10.1371/journal.pone.0183789  
  4. Batmaz AU, de Mathelin M, Dresp-Langley B (2018) Effects of 2D and 3D image views on hand movement trajectories in the surgeon’s peri-personal space in a computer-controlled simulator environment Cogent Medicine, 5(1), 1426232. https://doi.org/10.1080/2331205X.2018.1426232  
  5. Batmaz AU, de Mathelin M, Dresp-Langley B (2017). Inside the Virtual Brain: using Oculus Dk2 for Surgical Planning. NeuroTalk, Barcelona Spain 
  6. Batmaz AU, de Mathelin M, Dresp-Langley B (2017) Effects of relative target position on ipsilateral and contralateral manual operations in head-mounted virtual reality. European Conference on Visual Perception (ECVP), Berlin Germany. http://journals.sagepub.com/page/pec/collections/ecvp-abstracts/index/ecvp-2017  
  7. Batmaz AU, de Mathelin M, Dresp-Langley B (2018) Effects of image size and structural complexity on time and precision of hand movements in head-mounted virtual reality.2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Tuebingen/Reutlingen, Germany, 2018, pp. 167-174. https://doi.org/10.1109/VR.2018.8446217
  8. Batmaz AU, Falek MA, Zorn L, Nageotte F, Zanne P, de Mathelin M, Dresp-Langley B (2017) Novice and expert haptic behaviours while using a robot-controlled surgery system. In 13th IASTED International Conference on Biomedical Engineering (BioMed) (pp. 94-99). IEEE. https://doi.org/10.2316/P.2017.852-022  
  9. Batmaz AU, de Mathelin M, Dresp-Langley B (2018, to appear) Different sound pitch effects on motor performance of individuals in head-mounted Virtual Reality. ECVP 2018 Trieste, Italy

Chapter 1 – Comparison of Real-World Manual Operations Under 2D and 3D Image Guidance

In the first chapter, speed and precision analysis of real-world manual operations are inspected under different visual and tactile feedbacks.

When a surgeon performs a minimally invasive surgery, he/she must look at another source of visual feedback that is provided by a digital camera. The information provided by the natural view with eyes is not the same as looking through a 2D screen. This limitation also affects the perception of users and disturbs the actions and movements in real-world application. Previous research on this topic shows that subjects are slower, less precise and make more task errors under 2D screen conditions.

Furthermore, during a surgical procedure, the surgeon must use a tool to perform the surgery. This tool manipulation disables the direct haptic feedback between the touch sensation of the surgeon and the manipulated object. In this case, the surgeon has to perform movements, maneuvers, and actions according to the tactile information transferred by the surgical tool.

To overcome these major visual and tactile feedback challenges, different approaches have been tried such as: training novices in the use of surgical simulators, trying to find the best screen position for the surgeon to perform surgery, and using different visual feedbacks including stereoscopic 3D vision to create an artificial visual feedback.

In the first chapter of this thesis, different methods used in surgical environments to create a better surgical training system are studied. For this purpose, the “EXCALIBUR” experimental platform was designed with specific hardware and software components.

Chapter 2 – Human-Computer Interaction in Head Mounted Virtual Reality

In the second chapter, speed and precision analysis of real-world manual operations is investigated using immersive virtual reality (VR) and VR head mounted display. Emerging technologies on different visual feedback systems help surgeons to train themselves in different environments. Among these environments, VR became more popular in the last decade thanks to technological and industrial support. New simulator applications on surgical training are starting to develop in VR, but the major downside of these applications is their evaluation techniques. These applications do not perform any cognitive or psychomotor assessment experiments and they only take the execution time into account for performance assessment. This limitation creates a drawback in understanding the psychophysics behind the applications and VR itself.

One of the biggest advantages of the VR system is the ability to create virtual objects in any size, dimension or scale, and giving individual’s an ability to interact with these objects using different input devices. Different size, orientation, scale, and even the position of the designed virtual objects can affect the motor performance of the individuals and the effects of these features on human cognition need to be studied within the framework of psychophysics. On the other hand, the human interaction with these virtual objects in the VR is not the same as real-world real target interactions since the feedbacks are artificially created. To overcome this problem, designers and engineers work on the visual, tactile, and auditory feedbacks to enhance the perception and to assist users to focus in VR, which causes variations in human performance and decision. Nevertheless, the effects of these non-real-world feedbacks and pseudo-feedbacks on human motor performance are still not well known.

In the first chapter, the importance of the precision assessment in surgical training and effects of different methods used to enhance motor performance of the novices in image guidance systems were studied. In the second chapter, motor performance of novices in VR medical training applications with manual hand operations [68–70] are analyzed by using human-computer interactions. For his purpose, the “NoTouch” system is developed to collect data from the complete novices.

Chapter 3 – Grip-Force Analysis in Tele-Manipulated Operations

In the third chapter of the thesis, hand grip force analysis is performed on human manual operations. In the first two chapters, visual and tactile feedbacks used in medical training applications were analyzed together with the motor performance measurements of the individuals. In the last chapter of the thesis, the research is expanded into a minimally invasive surgical robot system, STRAS. To be able to measure the grip force variations on STRAS, a special glove was designed to collect data. The aim of this glove was to record grip-force signals from different loci of measurement in the palm, the fingers, and the fingertips of the dominant and nondominant hand.


When the surgeon loses haptic information caused by reduced-access conditions in robot-assisted surgery, it may compromise the safety of the procedure. This limitation must be overcome through practice and, in particular, surgical simulation training for specific hand-tool interactions. Using biosensors for the measurement of grip force variations during surgical simulation training with hand-tool interaction provides valuable insight into surgical skill evolution. Biosensor systems for measuring hand and finger grip force intensities need to be calibrated for the specific purpose as they are to serve in the context of surgical tool manipulation with sensory feed-back interaction. Using a tool effectively requires sufficient grip force to prevent it from dropping or slipping and, at the same time, avoiding excessive force that could damage the tool or the tissue it is applied to. Visually guided somatosensory learning is particularly important to the fine-tuning of fingertip forces applied to specific shapes of specific objects or tools.
In the last chapter of the thesis, task execution time and grip forces variations are analyzed by using a biosensor system on STRAS robot-assisted surgical system with a novice user and an expert user [101].

M.Sc. Thesis

I was working with Professor Cosku Kasnakoglu and Professor Bulent Tavli between September 2011 and August 2013 at TOBB Economy and Technology University, Ankara/Turkey. The thesis title was “Design of multi-rotor unmanned aerial vehicle and optimization of resource allocation in wireless sensor networks”. You can access the manuscript from the following link:

In this thesis, I worked on two different topics:

  • Drones
  • Wireless sensor networks

Drones

I worked with Professor Cosku Kasnakoglu and Ovunc Elbir to fly our own drone which we designed and built from scratch. The purpose of this research was to show a novel method to improve the stability of commercial drones. First, we manually adjusted drone controller coefficients. Then. we used Matlab to create a system transformation matrix from drone’s pitch, yaw and roll data. We optimized the PID controller of the drone by using Matlab and system identification.  Afterwards, we used new PID controller coefficient on the drone, and compared the stability of drone, e.g., how fast the drone reaches to the reference angle. The optimized controller was reaching to reference input (stable hovering) faster than the manually adjusted controller.    

You can reach my first drone flight on YouTube:

Wireless sensor networks

Wireless Sensor Networks (WSN) was another topic that I was interested in during my M.Sc. studies. I was working with Professor Bulent Tavli on link unidirectionality and reverse path length. By using mixed integer programming, we were calculating optimum routes for data and acknowledgment packages. The aim of this research was to decrease the energy consumption between the nodes to improve the life-time of the network.  

MscWSN

Mixed integer programming example from the MSc thesis

MsCWSNlink.png

Example optimum mixed integer programming results

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