27 citations · 64 across the 17 of their papers we have counts for
21 papers
PocketTSLM: Deploying an On-Device Soft-Prompt Time-Series Language Model for Privacy-Preserving Smartphone Reasoning
Max Rosenblattl, Nikhil Krishnaswamy, Leon Nissen +9
Consumer phones and wearables increasingly collect physiological time-series data, yet most mobile systems treat these streams as summaries or text rather than as temporal evidence…
TimeCap: A Scalable Open-Source Pipeline for Captioning Wearable Health Time-Series Data
Max Rosenblattl, Milana Gurbanova, Karl Aurel Deck +16
Time-series data generated continuously across industrial, environmental, and especially health domains produce multimodal signals whose scale and heterogeneity make their processi…
TimeNet: An Extensible Unified Data Infrastructure for Next-Generation Temporal Foundation Models
Martin Maritsch, Timo Stoffregen, Thomas Kaar +36
Temporal Foundation Models (TFMs) aim to generalize across domains, datasets, and tasks. Yet, their development remains constrained by fragmented, task-specific data formats, annot…
TimeRLM: Recursive Language Models Enable Precise Anomaly Localization in Long-Context Time-Series
Nicolas Zumarraga, Lorenzo Steno, Ning Wang +9
Precise anomaly localization over long-context time series is a crucial task in monitoring applications across clinical care, industrial operations, financial services, and logisti…
Patient-Level Multimodal Question Answering from Multi-Site Auscultation Recordings
Fan Wu, Tsai-Ning Wang, Nicolas Zumarraga +8
Auscultation is a vital diagnostic tool, yet its utility is often limited by subjective interpretation. While general-purpose Audio-Language Models (ALMs) excel in general domains,…
TS-Haystack: A Multi-Task Retrieval Benchmark for Long-Context Time-Series Reasoning
Nicolas Zumarraga, Thomas Kaar, Ning Wang +12
Time Series Language Models (TSLMs) promise reasoning over real-world temporal data, but their ability to retrieve and reason over long time-series remains largely untested. We int…
EvoMorph: Counterfactual Explanations for Continuous Time-Series Extrinsic Regression Applied to Photoplethysmography
Mesut Ceylan, Alexis Tabin, Patrick Langer +2
Wearable devices enable continuous, population-scale monitoring of physiological signals, such as photoplethysmography (PPG), creating new opportunities for data-driven clinical as…
OpenTSLM: Time-Series Language Models for Reasoning over Multivariate Medical Text- and Time-Series Data
Patrick Langer, Thomas Kaar, Max Rosenblattl +19
LLMs have emerged as powerful tools for interpreting multimodal data. In medicine, they hold particular promise for synthesizing large volumes of clinical information into actionab…
CosinorAge: Unified Python and Web Platform for Biological Age Estimation from Wearable- and Smartwatch-Based Activity Rhythms
Jinjoo Shim, Jacob Hunecke, Elgar Fleisch +1
Every day, millions of people worldwide track their steps, sleep, and activity rhythms with smartwatches and fitness trackers. These continuously collected data streams present a r…
Digital Scale: Open-Source On-Device BMI Estimation from Smartphone Camera Images Trained on a Large-Scale Real-World Dataset
Frederik Rajiv Manichand, Robin Deuber, Robert Jakob +4
Estimating Body Mass Index (BMI) from camera images with machine learning models enables rapid weight assessment when traditional methods are unavailable or impractical, such as in…
GeHirNet: A Gender-Aware Hierarchical Model for Voice Pathology Classification
Fan Wu, Kaicheng Zhao, Elgar Fleisch +1
AI-based voice analysis shows promise for disease diagnostics, but existing classifiers often fail to accurately identify specific pathologies because of gender-related acoustic va…
HEAPO -- An Open Dataset for Heat Pump Optimization with Smart Electricity Meter Data and On-Site Inspection Protocols
Tobias Brudermueller, Elgar Fleisch, Marina González Vayá +1
Heat pumps are essential for decarbonizing residential heating but consume substantial electrical energy, impacting operational costs and grid demand. Many systems run inefficientl…
Comparative Efficacy of Commercial Wearables for Circadian Rhythm Home Monitoring from Activity, Heart Rate, and Core Body Temperature
Fan Wu, Patrick Langer, Jinjoo Shim +2
Circadian rhythms govern biological patterns that follow a 24-hour cycle. Dysfunctions in circadian rhythms can contribute to various health problems, such as sleep disorders. Curr…
CLAID: Closing the Loop on AI & Data Collection -- A Cross-Platform Transparent Computing Middleware Framework for Smart Edge-Cloud and Digital Biomarker Applications
Patrick Langer, Elgar Fleisch, Filipe Barata
The increasing number of edge devices with enhanced sensing capabilities, such as smartphones, wearables, and IoT devices equipped with sensors, holds the potential for innovative…
Leveraging driver vehicle and environment interaction: Machine learning using driver monitoring cameras to detect drunk driving
Kevin Koch, Martin Maritsch, Eva van Weenen +5
Excessive alcohol consumption causes disability and death. Digital interventions are promising means to promote behavioral change and thus prevent alcohol-related harm, especially…
"Are you okay, honey?": Recognizing Emotions among Couples Managing Diabetes in Daily Life using Multimodal Real-World Smartwatch Data
George Boateng, Xiangyu Zhao, Malgorzata Speichert +6
Couples generally manage chronic diseases together and the management takes an emotional toll on both patients and their romantic partners. Consequently, recognizing the emotions o…
Development, Deployment, and Evaluation of DyMand -- An Open-Source Smartwatch and Smartphone System for Capturing Couples' Dyadic Interactions in Chronic Disease Management in Daily Life
George Boateng, Prabhakaran Santhanam, Elgar Fleisch +4
Dyadic interactions of couples are of interest as they provide insight into relationship quality and chronic disease management. Currently, ambulatory assessment of couples' intera…
Emotion Recognition among Couples: A Survey
George Boateng, Elgar Fleisch, Tobias Kowatsch
Couples' relationships affect the physical health and emotional well-being of partners. Automatically recognizing each partner's emotions could give a better understanding of their…
Detecting Receptivity for mHealth Interventions in the Natural Environment
Varun Mishra, Florian Künzler, Jan-Niklas Kramer +3
JITAI is an emerging technique with great potential to support health behavior by providing the right type and amount of support at the right time. A crucial aspect of JITAIs is pr…
Driver Identification via the Steering Wheel
Bernhard Gahr, Shu Liu, Kevin Koch +5
Driver identification has emerged as a vital research field, where both practitioners and researchers investigate the potential of driver identification to enable a personalized dr…
When Money Learns to Fly: Towards Sensing as a Service Applications Using Bitcoin
Kay Noyen, Dirk Volland, Dominic Wörner +1
Sensing-as-a-Service (S2aaS) is an emerging Internet of Things (IOT) business model pattern. To be technically feasible and to effectively allow for broad adoption, S2aaS implement…