"I develop measuring devices that detect muscle or brain activity.”
As an Application Engineer at TMSi, I deal with technical applications and measurement solutions for electrophysiological research. I play a part in the development of measuring amplifiers that allow researchers to measure muscle or brain activity. Before we can make a prototype, I first have to investigate the end user's wishes. I do this by talking to the researchers and asking how they want to use the amplifier and also how we can ensure its’ user-friendliness. A product must not only display clean data (= noise-free); often small measuring devices the size of mobile phones are requested. As an Application Engineer, I’m not only involved in identifying the desired applications, but am also working as a Software Engineer for the end-users’ measuring applications.
During both my bachelor's and master’s studies, I learned about measurements of muscle activity. For example, the muscle’s electrical activity, called electromyography (EMG), can be recorded when lifting a weight. You can also look at how muscles react to holding a weight steady and what happens when the weight is increased, which can give insight into the muscle’s varying responses. With appropriate signal processing, it is even possible to control a robotic limb based on EMG. My enthusiasm for learning about electromyography/EMG during my bachelor’s studies led me to choose the specialisation Physiological Signals & Systems (PSS) for my master's degree. Within my specialisation, I focused on the signal processing, machine learning and how electrical stimuli can restore disturbed body function.
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The brain makes a muscle move
I carried out my master's assignment at Roessingh Research and Development. The aim was to investigate whether a prosthetic limb could be used intuitively by using the body’s own mechanisms. Using muscle activity, I investigated if joint positioning could be estimated. Muscle activity can be measured because there are nerve tracts running from the brain to a muscle, containing the electrical control signal. Before taking a step, I saw that muscle activity could be detected, indicating that the brain sent a control signal to the muscle. This allows you to predict the angle of the ankle and knee in advance to make sure that the rehabilitating patient places his/her foot correctly and intuitively.
As a Physiological Signals & Systems expert, I feel at home at TMSi. Together with my colleagues, we continue to search for the right measurement solutions for researchers, so that they can advance electrophysiological research and sometimes even save lives. The field of electrophysiological signals is a wonderful research subject and it gives me great satisfaction that I can actively contribute to technological applications and innovations.