Master's thesis presentation. Mohammad is advised by Abu Shad Ahammed (University of Siegen), Prof. Dr.-Ing. habil. Roman Obermaisser (University of Siegen) and Prof. Dr. Felix Dietrich.
SCCS Kolloquium
The SCCS Colloquium is a forum giving students, guests, and members of the chair the opportunity to present their research insights, results, and challenges. Do you need ideas for your thesis topic? Do you want to meet your potential supervisor? Do you want to discuss your research with a diverse group of researchers, rehearse your conference talk, or simply cheer for your colleagues? Then this is the right place for you (and you are also welcome to bring your friends along).
Upcoming talks
Mohammad Asif Ibna Mustafa: Wearable device-based human activity recognition
SCCS Colloquium |
Human Activity Recognition (HAR) is the process of identifying and monitoring physical activities through wearable sensor data, providing real-time insights that enhance patient care, personalized fitness planning, and lifestyle interventions. With the growing adoption of wearable devices, demand for reliable HAR systems capable of operating in diverse, free-living environments has increased, as these systems must handle varied data quality. Wearable device-based HAR, leveraging multimodal data, holds significant promise for applications like health monitoring, fall detection, and rehabilitation, where precise, continuous activity tracking is critical.
This study evaluates HAR performance using multimodal data from two wearable devices: the Cosinuss° C-Med° Alpha (an in-ear device) and the Garmin Venu 2 (a wrist-worn smartwatch). Data were collected from eight participants in a free-living setting, with Cosinuss° capturing continuous physiological metrics, including heart rate, blood oxygen saturation, body temperature, and accelerometer data. Garmin also recorded physiological data, such as heart rate and oxygen saturation, in addition to an extensive motion dataset comprising accelerometer, gyroscope, and GPS altitude readings. By independently assessing motion-only and motion plus physiological data, this study investigates how multimodal data integration, specifically adding physiological signals, impacts model performance, particularly for complex activities.
Various machine learning models (KNN, SVM, Random Forest, XGBoost) with handcrafted features and deep learning models (LSTM, ConvLSTM, Transformer) using raw features were evaluated. Machine learning models performed well with motion-only data for both simple and complex tasks, while deep learning models showed notable gains with the addition of physiological data. XGBoost achieved the highest accuracy among machine learning models, while Transformer led in deep learning across single and multi-subject datasets. The LSTM model showed a 30\% improvement in weighted F1 score when using both motion and physiological data from Cosinuss°. Zero shot learning revealed that Cosinuss° performed better than Garmin in motion-only classification, while Garmin’s combined motion and physiological data exhibited superior cross-subject generalization.
The results highlight the value of multimodal data integration in enhancing HAR for complex activities and suggest that Transformer and XGBoost models are particularly suited for robust healthcare and fitness applications. Future work may explore transfer learning and cross-subject training to broaden HAR’s adaptability and generalizability.
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Contribute a talk
To register and schedule a talk, you should fill the form Colloquium Registration at least four weeks before the earliest preferred date. Keep in mind that we only have limited slots, so please plan your presentation early. In special cases, contact colloquium(at)mailsccs.in.tum.de.
Colloquium sessions are now on-campus. We have booked room MI 00.13.054 for WS24/25. You can either bring your own laptop or send us the slides as a PDF ahead of time. The projector only has an HDMI connection, so please bring your own adapters if necessary.
Do you want to attend but cannot make it in person? We now have a hybrid option. Simply join us through this BBB room: https://bbb.in.tum.de/shu-phv-eyq-rad
We invite students doing their Bachelor's or Master's thesis, as well as IDP, Guided Research, or similar projects at SCCS to give one 20min presentation to discuss their results and potential future work. The time for this is typically after submitting your final text. Check also with your study program regarding any requirements for a final presentation of your project work.
New: In regular times, we will now have slots for presenting early stage projects (talk time 2-10min). This is an optional opportunity for getting additional feedback early and there is no strict timeline.
Apart from students, we also welcome doctoral candidates and guests to present their projects.
During the colloquium, things usually go as follows:
- 10min before the colloquium starts, the speakers setup their equipment with the help of the moderator. The moderator currently is Ana Cukarska. Make sure to be using an easily identifiable name in the online session's waiting room.
- The colloquium starts with an introduction to the agenda and the moderator asks the speaker's advisor/host to put the talk into context.
- Your talk starts. The scheduled time for your talk is normally 20min with additional 5-10min for discussion.
- During the discussion session, the audience can ask questions, which are meant for clarification or for putting the talk into context. The audience can also ask questions in the chat.
- Congratulations! Your talk is over and it's now time to celebrate! Have you already tried the parabolic slides that bring you from the third floor to the Magistrale?
Do you remember a talk that made you feel very happy for attending? Do you also remember a talk that confused you? What made these two experiences different?
Here are a few things to check if you want to improve your presentation:
- What is the main idea that you want people to remember after your presentation? Do you make it crystal-clear? How quickly are you arriving to it?
- Which aspects of your work can you cover in the given time frame, with a reasonable pace and good depth?
- What can you leave out (but maybe have as back-up slides) to not confuse or overwhelm the audience?
- How are you investing the crucial first two minutes of your presentation?
- How much content do you have on your slides? Is all of it important? Will the audience know which part of a slide to look at? Will somebody from the last row be able to read the content? Will somebody with limited experience in your field have time to understand what is going on?
- Are the figures clear? Are you explaining the axes or any other features clearly?
In any case, make sure to start preparing your talk early enough so that you can potentially discuss it, rehearse it, and improve it.
Here are a few good videos to find out more:
- Simon Peyton Jones: How to Give a Great Research Talk (see also How to Write a Great Research Paper)
- Susan McConnell: Designing effective scientific presentations
- Jens Weller: Presenting Code
Did you know that the TUM English Writing Center can also help you with writing good slides?
Work with us!
Do your thesis/student project in Informatics / Mathematics / Physics: Student Projects at the SCCS.