{"id":4249,"date":"2025-07-03T19:54:53","date_gmt":"2025-07-03T17:54:53","guid":{"rendered":"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/?p=4249"},"modified":"2025-07-24T11:17:21","modified_gmt":"2025-07-24T09:17:21","slug":"medical-sensing-systems-norman-pfeiffer","status":"publish","type":"post","link":"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/medical-sensing-systems-norman-pfeiffer\/","title":{"rendered":"Just a Few Steps Away from the Tricorder: How Medical Sensing Systems are Transforming Healthcare"},"content":{"rendered":"\n

Thanks to wearables, we are<\/em> <\/i>increasingly integrating the monitoring, measurement, and analysis of health-related data into our daily lives. However, this represents only a fraction of what medical sensing can achieve in biosignal acquisition and the advancement of healthcare. We spoke with Norman Pfeiffer, Group Leader of Medical Sensing Systems<\/a> at Fraunhofer IIS, about the most fascinating<\/em><\/em> sensors he\u2019s developed, and which portable sensor serves as his inspiration. (Spoiler: It\u2019s handheld and issued by Starfleet.)<\/em><\/p>\n\n\n\n

Norman, you are currently the group lead of Medical Sensor Systems. What is it that you do?<\/strong><\/p>\n\n\n\n

Norman Pfeiffer:<\/strong> In our group, we develop low-power electronics, particularly wearable devices or those integrated into everyday items, to capture biosignals from humans. Our primary goal is to measure various human states and contribute to monitoring and diagnosing diseases. Our focus actually covers the entire range of development, including hardware and firmware, with a particular focus on signal acquisition, processing, and analysis. This involves designing circuits, creating printed circuit boards (PCBs), programming microcontrollers, as well as developing embedded algorithms.<\/p>\n\n\n\n

What are emerging trends in your field and how are they shaping the future of healthcare?<\/strong><\/p>\n\n\n\n

For starters, there is a continuous development of new modalities. For instance, an increasing number of chemical biosensors are now measuring sweat and saliva, providing information on the concentration of specific biomarkers. Another trend is multimodal sensors, meaning that multiple sensors are used to assess various states and evaluate human conditions. Embedded AI plays a big role here, enabling signal processing directly on the embedded system, allowing it to operate independently. This also reduces our dependence on cloud systems.<\/p>\n\n\n\n

Another issue relating to sensor integration is ensuring easy access and making sensor technology more user-friendly. Users no longer need to take extra steps to have their biosignals captured; instead, the technology is seamlessly woven into their daily lives.<\/p>\n\n\n\n

The idea being that we create a healthcare system that extends beyond the doctor’s office or clinic, integrating health monitoring into people’s daily lives?<\/strong><\/p>\n\n\n\n

Exactly. Integrating health monitoring into our daily lives offers numerous advantages. First of all, closer monitoring leads to improved healthcare. Allowing monitoring to take place at home also decentralizes healthcare, making it more accessible to a larger number of people through low-threshold access. Plus, seamless integration also eliminates the common issue of purchasing a wearable, using it for a few weeks, and then setting it aside. Instead, users don\u2019t even have to think about using it.<\/a><\/p>\n\n\n\n

\"Norman
Norman Pfeiffer, Group Leader of Medical Sensing Systems at Fraunhofer IIS (\u00a9Fraunhofer IIS)<\/figcaption><\/figure>\n\n\n\n

What\u2019s the coolest sensor you\u2019ve built so far and what sets it apart?<\/strong><\/p>\n\n\n\n

The coolest sensor I\u2019ve built is one that analyzes saliva samples as part of an EU project. The project’s focus was on using new biomarkers to detect heart diseases through saliva. With this Point of Care Testing device, results were delivered in short time, enabling prompt diagnosis and the initiation of treatment.<\/p>\n\n\n\n

Coming back to the issue of low-threshold access \u2026 We recently made some developments that illustrate this point quite well. In collaboration with Hamberger Medical, we created a sensor that integrates ECG electrodes into a toilet seat<\/a>. This allows for ECG monitoring during bathroom visits. The system automatically detects arrhythmias  \u2013 to be more precise, atrial fibrillation \u2013 and users can share the results directly with their doctor. This integration makes heart monitoring a regular part of daily life, enabling more consistent observation of one\u2019s health status.<\/p>\n\n\n\n

Another example is a research project<\/a> we\u2019ve had with our colleagues from Fraunhofer ISC and Fraunhofer EMFT to develop a pressure measurement stocking. We integrated pressure sensors into the textile of the sock to detect pressure peaks and, in turn, identify early signs of pressure ulcers. This is crucial for diabetics, who often lose sensitivity in their feet. With our smart sock, they get early feedback to alert them if there\u2019s a stone in their shoe, for example.<\/p>\n\n\n\n

Walk me through the process: I have an idea or a need for an integrated sensor solution and reach out to you. What happens next?<\/strong><\/p>\n\n\n\n

Depending on how much groundwork you have already done, we can start at different points. If you have a basic idea and we can replicate the sensor modalities in our lab, the first step would be to conduct a feasibility study using our lab equipment. We might even start with healthy test subjects to assess whether we can accurately measure what we intend to measure. If the feasibility study is successful, requirements, system specifications, and the interface will be elaborated. Then, we can start the development phase \u2013 always in collaboration with our clients. This includes, as I mentioned earlier, hardware, the embedded system, firmware, communication, algorithms, and maybe even user interfaces or GUIs on a smartphone, for example. Depending on the context, we can validate the system again in a so-called other clinical investigation. In these investigations, we might also be able to generate data for developing algorithms further. Especially in machine learning, we need data from the target device to effectively train the corresponding model. If the context is medical device development, we continue with a clinical trial so that the product can successfully be brought to market.<\/p>\n\n\n\n

What role does data analysis play and how do you include it in the project workflow?<\/strong><\/p>\n\n\n\n

Data analysis is, in various aspects, a very significant topic. On one hand, it allows us to evaluate the measurement system itself through data collection and analysis, which is crucial for validating the system. On the other hand, we need data to develop machine learning-based algorithms. This is particularly important in the context of multimodal measurements, where multiple sensors are used to gather extensive information from an individual. In this regard, consistency and high data quality are essential. In the case of maphera\u00ae<\/sup><\/a>, for instance, we have developed a sensor network that enables very high synchronization accuracy between sensor nodes wirelessly.<\/p>\n\n\n\n

Another asset of our team is our ability to conduct subject studies for our clients, covering the entire workflow. This includes everything from application documents, such as ethics submissions or potentially even BfArM (Federal Institute for Drugs and Medical Devices<\/em>) applications, to participant recruitment and data analysis. Furthermore, we benefit from our close connection to the university hospital in Erlangen, where medical experts are available to serve as our counterparts.<\/p>\n\n\n\n

Let\u2019s conclude the interview with a vision: Where will medical sensor technology lead us and what type of application would you like to develop if you could?<\/strong><\/p>\n\n\n\n

Ultimately, portable medical sensor systems are all about finding new modalities. Multimodal measurement involves developing new measurement principles, providing us with even more opportunities to capture signals. Our hope is to gain a deeper understanding of physiological processes through wearables, enabling earlier and more accurate detection of health conditions, which in turn leads to much better therapeutic options.<\/p>\n\n\n\n

But actually, when you ask people in medical technology or in the field of medical and portable sensor systems about their vision, you’ll receive a similar answer from almost everyone: They dream of developing a tricorder like in Star Trek, with which you can do a complete scan of a person in just seconds, revealing any existing health conditions and determining their overall health. This will probably take a few more years (laughs)<\/em>, but that is certainly the ultimate goal.<\/p>\n\n\n\n

\n\n\n\n

Image copyright (cover image): Fraunhofer EMFT \/ Bernd M\u00fcller<\/a><\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Thanks to wearables, we are increasingly integrating the monitoring, measurement, and analysis of health-related data into our daily lives. However, this represents only a fraction of what medical sensing can achieve in biosignal acquisition and the advancement of healthcare. 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