Research Associate / PhD candidate (Wearable Mobility Sensing and Digital Biomarkers for Heart Failure Monitoring)
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Responsibilities
- Core project deliverables:
- Validate and adapt actibelt® technologyfor HF patient monitoring in Singapore, extracting and evaluating mobilityparameters (real-world walking speed, stair-climbing ability, gait qualityindices)
- Contribute to the design and executionof a clinical pilot study (35 HF patients + reference cohort) at NHCS/NUHCS
- Contribute to a prototype clinicaldecision support system integrating actibelt-derived parameters with additionaldigital inputs (e.g., digital stethoscope, digital scale)
- Publish findings in peer-reviewedjournals and present at international conferences
- Contribute to the CACOM lecture series(Clinical Applications of Computational Medicine, TUM)
- Research and methodological development:
- Design and pursue original researchquestions within the project's scientific scope
- Develop and evaluate novel algorithmicapproaches for inertial signal processing, activity classification, or clinicalendpoint extraction
- Contribute to the broader actibeltalgorithm development pipeline, including work on reference data collectionmethodology and algorithm validation frameworks
Additional Information
About TUMCREATE TUMCREATE is a multidisciplinary research platform of the Technical University of Munich (TUM) at the Singapore Campus for Research Excellence and Technological Enterprise (CREATE). We are partnering with universities, public agencies, and industry to advance future technologies. Our public-private research partnership program, HEARTwise - Heart Failure Assessment with Reliable Technology using Wearables and In Vitro Diagnostics - is funded by Singapore's National Research Foundation (NRF) and represents a collaborative effort between the Technical University of Munich (TUM), the National University Health System (NUHS), the National Heart Centre Singapore (NHCS), and the National University of Singapore (NUS). As a member of the HEARTwise team, you will collaborate within an interdisciplinary consortium comprising leading experts in cardiology,telemedicine, biomedical engineering, acoustics, data privacy, and industry. Please visit www.tum-create.edu.sg for more information about TUMCREATE. Background & Scientific Context Heart failure (HF) affects 2.5% of Singapore's population and is the leading cardiac cause of hospital admission -presenting a decade earlier and more aggressively than in Europe or North America. The 30% rehospitalization rate within 90 days of discharge is both a major clinical burden and a window of opportunity for early, data-driven intervention. The HEARTwise project is a public-private research initiative funded by Singapore's National Research Foundation, bringing together clinical cardiologists (CADENCE / NUHS, NHCS),engineers from TUM and TUMCREATE, and MedTech partners. The project develops a multimodal platform for non-invasive, early decompensation detection in ambulant HF patients - combining wearable mobility sensing, acoustic environment recognition, and integration with additional digital biomarker sources. This is a fixed-term contract until March 2029. Supervision & Academic Environment The position is jointly supervised by principal investigators at TUM Munich and TUMCREATE Singapore, with close integration into the CADENCE clinical network. The candidate will work within a growing team of researchers across engineering and clinical disciplines in Singapore, with strong links to the Munich ecosystem. The position combines the rigor of TUM's doctoral program with direct access to clinical partners and the unique research infrastructure of TUMCREATE. The Research Position This PhD is embedded in the HEARTwise engineering team at TUMCREATE Singapore and is centered on the actibelt®wearable technology platform - a body-worn 3D accelerometer system with a mature clinical track record, an established algorithm library, and over 64 years of recorded patient data. The core scientific contribution expected is the development, validation, and clinical deployment of actibelt-based mobility analysis in HF patients. The candidate will engage with open methodological questions - including how to extract richer clinical information from inertial data, how to improve reference data acquisition for algorithm development, and what mobility-based signatures may carry predictive value for HF decompensation - as well as with the translational challenge of deploying these methods in a real clinical setting. Central research questions include: Which mobility parameters derivable frombelt-worn inertial sensing are most informative for detecting early functionaldeterioration in ambulant HF patients? What methodological advances in reference data acquisition, sensor placement, or algorithm generalization can improve the quality and scalability of wearable-based gait analysis? How can a prototype clinical decision support tool effectively integrate actibelt-derived mobility markers with additional digital inputs to inform clinical management?
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