Mechanical, Electrical and Manufacturing Engineering


Professor Massimiliano Zecca PhD MSc

Photo of Professor Massimiliano Zecca

Current Positions

As of March 2014, he is Professor of Healthcare Technology at Loughborough University, UK, in the School of Mechanical, Electrical and Manufacturing Engineering (MEME), where he leads the Warable BioRobotics research group. He is also a key member of the National Centre for Sports and Exercise Medicine – East Midlands, Loughborough, United Kingdom. He also keeps working with Waseda University, Tokyo, Japan, as Visiting Professor of Robotics.

Scientific Interest

Among social infrastructure technologies, Robot technology is expected to play an important role in solving the problems of both decrease of birth rate and increase of elderly people in the 21st century. The observation and the analysis of the human being, an extreme and exquisite example of robotic system, could lead to the clarification of the simplexity-based mechanisms underlying human's control of their bodies. This, in turn, will be an extremely important and helpful tool for the aging society in order to realize better health-care systems, human-support devices, teleoperation methods, and so on.

My research activities have always been centred on the understanding of the human being. My strong belief, in fact, is that a good research on humanoid robotics (partner robots, assistive technologies, and so on) could not leave out of consideration a better and deeper understanding of the human being and its capabilities, in particular for what concerns motion control in high dexterous tasks in a wide range of applications, such as walking or surgery.

My research goal has been the quantification of the capabilities of human beings in different situations, such as training for laparoscopic surgery, mastication analysis, gait analysis in rehabilitation, as well as human-robot emotional and musical interaction, just to mention a few, and the application of these findings for developing more advanced robots. In particular I focused my attention on the development of extremely small and very accurate motion sensors (inertial measurement units, electromyography sensors, and so on), much less visible and much less obtrusive than the current measuring systems. In addition, I also developed several data processing and analysis methodologies to extract useful information from the raw data flow.

The combination of advanced hardware with advanced software is making it possible to make measurements in situations where it was very difficult to measure before. For example, it allows us to achieve a better and objective understanding of the skills of the trainee, of the effectiveness of the training exercise, to quantify the movements during daily life, or to produce a meaningful interaction with the advanced robots available in the labs. Another example is that this combination allows us to understand the effects of the deformation of the mechanical structures of the robots while walking, thus making it possible for a real-time compensation.

I strongly believe that engineering education in general must be both multicultural and multidisciplinary since the first year; this becomes even truer if we want to have new leaders capable of tackling the advanced challenges our society is providing us.

My goal as educator is to nurture the new “Renaissance Engineer” of the third millennium, intended as an old new- model of engineer, highly inter-disciplinary and not so much focused on high specialization; more open to cultural fertilizations and not strictly oriented towards the technical knowledge, but able to use in design the investigation and synthesis tools provided by the study of Nature and of humanities.

Robotics and Bioengineering are the perfect background disciplines to achieve this goal, as they are both strongly multidisciplinary and extremely broad (horizontal) disciplines, de facto unifying the so-called “two cultures”, Science and Humanities. With their multidisciplinary and active characteristics, Robotics and Bioengineering better prepares the students to tackle the global challenges they will face during their life and future careers.

With my Laurea Degree (equivalent to Bachelor+Master) in Electrical Engineering with a minor in Bioengineering, my PhD in Biomedical Robotics, and my activities as associate professor of robotics, I am confident to be qualified in teaching a wide variety of courses related to Robotics, Bioengineering, Mechatronics, and Medical (Rehabilitation) Engineering, as well as more general courses about Scientific Presentation and Scientific Writing.

As an educator, I am strongly emphasizing active learning during all my courses at all levels, with activities organized in groups, discussion both in class as well as at home, and practical problem solving. I want to expose my students to simplified versions of real-case problems by using bioengineering and robotics as a teaching tool, so that they need to apply their theoretical knowledge to find a practical solution. This approach – as testified by the abundant literature on learning and learning technologies – fixes and strengthens their understanding of the subjects, in particular the most basic ones, such as mathematics and physics. Moreover, this active learning method allows the students to learn how to work in team as well as individually; it also strengthens their ability to uncover and solve problems, stimulates their creative thinking, and improves their communication skills, both written and oral.

At undergraduate level, for example in my courses such as Fundamentals of Robotics, I can show the students the basic concepts for several disciplines (mathematics, physics, electronics, and mechanics, just to mention a few) as well as their practical implementations in real life. My research experience in Robotics and Bioengineering also allows me to present what the current basic topics can lead to; I always emphasize concrete examples and tangible demonstrations, and whenever possible I give examples from my own background. The use of practical Robotics and Bioengineering as teaching aids naturally guides the students to master the basic academic skills; moreover, they act as tremendous motivational agents, as the students are both intrigued and fascinated by the possibilities that are waiting for them in the senior years. I also think it is important to avoid a mechanistic approach, and instead it is important to develop the intuition behind mathematical and programming tools and a good sense of why and when they work. This is why I also liked more practical courses, such as Mechanical Engineering Lab, Mechatronics Lab, or Engineering Practice, and I would like in due time to teach them, too.

At graduate level I can build on the skills learned during the undergraduate years, and tackle more advanced topics. It is very important at this stage to guide the students to develop the ability to frame a problem and to look at it in new ways. At this level I can propose more complex courses on robotics (such as the course on “Advanced Topics in Robots and Systems” I am currently teaching in Waseda University), as well as to explore new ways of teaching. Another key issue is the combination of tools and insights from different fields, which are often separated by disciplinary boundaries.

For example, in the past years I have been running a journal club (i.e. a regular meeting in which all participants take turn in explaining a paper related to the participants’ research) with graduate students, PhD students, and post-doc researchers. This regular meeting was extremely well accepted by the students, so I proposed to transform it into a regular course. During this course (currently named “Analysis and discussion of papers on advanced robotics”) both master and PhD students read, analyse, and review recent papers on advanced robotics (with its widest interpretation). This allows the students to keep track and stay updated about what other groups in the world are doing, and learn new methodologies and ideas to be applied to their own research. The uniqueness of this course and its success among the students are testified by the fact that I always have several unregistered students, and some students are taking the course again even if they do not need it for the academic credits, because every year the contents of the course are new and the students can keep learning new things.

At all levels I always encourage the students to explore original research for final projects, after completing introductory assignments and paper reviews. This model has proven extremely successful for me in the past as an incubator for new ideas, and it is very beneficial to students, in particular at PhD level, in obtaining publications and experience in areas not directly related to their PhD research. The process of solving real-world problems through designing and controlling mechatronic systems has always inspired me in both classes and research, and I look forward to sharing this excitement with students.

One common problem when teaching to people coming from different nations, especially at undergraduate level, is that their ability to understand English, and to express themselves in a language which is not their mother tongue, can be limited. To overcome this problem and simplify the learning process of the students I have been videorecording all my lectures, and made them available to the student for off-line checking. In this way the students are able to repeat my lectures over and over when something was not clear, thus improving their understanding. In due time I plan to use the “flipped classroom” model, so that the students can check the lectures in advance at home, and we can use the class time for discussion and exercises. In this way I can spend more time interacting with my students instead of just lecturing them.

Selected Publications

Z. Lin, M. Uemura, M. Zecca, S. Sessa, H. Ishii, M. Tomikawa, M. Hashizume, and A. Takanishi, “Objective Skill Evaluation for Laparoscopic Training Based on Motion Analysis,” IEEE Transactions on Biomedical Engineering, vol. 60, no. 4, pp. 977–985, 2013.

This study proposes a methodology of defining a processing model that objectively evaluates surgical movement performance in the routine laparoscopic training course, based on the analysis of kinematic data describing the movements of surgeon’s upper limbs. Experimental results show that the proposed methodology can be efficiently used both for quantitative assessment of surgical movement performance, and for the discrimination between expert surgeons and novices.

G. Trovato, M. Zecca, T. Kishi, N. Endo, K. Hashimoto, and A. Takanishi, “Generation of Humanoid Robot’s Facial Expressions for Context-Aware Communication,” International Journal of Humanoid Robotics, vol. 10, no. 01, p. 1350013-1–1350013-23, 2013.

In this manuscript, we present a system that based on relevant studies of human communication and facial anatomy can produce thousands of combinations of facial and neck movements. The wide range of expressions covers primary emotions as well as complex or blended ones, and communication acts that are not strictly categorized as emotions. Results showed that the recognition rate of expressions produced by this system is comparable to the rate of recognition of the most common facial expressions.

S. Sessa, M. Zecca, Z. Lin, L. Bartolomeo, H. Ishii, and A. Takanishi, “A Methodology for the Performance Evaluation of Inertial Measurement Units,” Journal of Intelligent & Robotic Systems, pp. 143–157, 2013.

This paper presents a methodology for a reliable comparison among Inertial Measurement Units or attitude estimation devices in a Vicon environment. The misalignment among the reference systems and the lack of synchronization among the devices are the main problems for the correct performance evaluation using Vicon as reference measurement system. We propose a genetic algorithm coupled with Dynamic Time Warping (DTW) to solve these issues.

T. Chaminade, M. Zecca, S.J. Blakemore, A. Takanishi, C.D. Frith, S. Micera, P. Dario, G. Rizzolatti, V. Gallese, M. A. Umiltà, “Brain Response to a Humanoid Robot in Areas Implicated in the Perception of Human Emotional Gestures”, PLoS ONE 5(7), 2010.

By using fMRI we assessed how brain areas activated by the perception of human basic emotions (facial expression of Anger, Joy, Disgust) and silent speech respond to a humanoid robot impersonating the same emotions, while participants were instructed to attend either to the emotion or to the motion depicted. Increased responses to robot compared to human stimuli in the occipital and posterior temporal cortices suggest additional visual processing when perceiving a mechanical anthropomorphic agent. In contrast, activity in cortical areas endowed with mirror properties and in the processing of emotions is reduced for robot stimuli, suggesting lesser resonance with the mechanical agent. Finally, instructions to explicitly attend to the emotion significantly increased response to robot, but not human facial expressions in the anterior part of the left inferior frontal gyrus, a neural marker of motor resonance. Motor resonance towards a humanoid robot, but not a human, display of facial emotion is increased when attention is directed towards judging emotions